TW200305088A - System and method for order group planning with attribute based planning - Google Patents

Abstract

A system and method for planning the use of supply chain network resources in order to meet demand as defined by one or more groups of orders. The system and method is an attribute based rather than an order or stock keeping unit based system and method allowing for greater flexibility and improved simplicity in obtaining planning solutions. The system and method defines and uses stock keeping unit attribute definition groups, which allows orders to be prioritized and organized into slices of orders such that an optimal planning solution is generated. During the planning process, the system and method may determine whether the supply chain network resources used to fulfill the orders are replenishable by purchase. The system and method recognizes time events and takes into account the exact sequence of the events in order to obtain an optimal solution.

Description

0) 0) 200305088 发明 Description of the invention (the description of the invention shall state: the technical field, prior art, content, implementation and drawings of the invention are briefly explained) The relevant application cross-references this application and claims December 27, 2001 Priority of U.S. Provisional Patent Application Serial Nos. 6 0/3 42,404 and 60/3 77,243 filed on May 3, 2002 and their respective disclosures are hereby incorporated by reference in their entirety. This application also claims the priority of the following non-tentative U.S. applications, which are awaiting determination and general assignment: Application dated November 5, 2002, serial number 10/2 87,788, agent file number 82001.0350, etc. Order Group Planning System and Method Based on Attribute-Based Planning "; Application of 'No. 1 0 / 287,775, Agent Document No. 8200 1.0390, etc. by Crampton et al. Supplementary Systems and Methods Manufactured by Planning "; Application of November 5, 2002, Serial No. 10 / 287,805, Agent Document No. 82001 · 0 391 by Crampton et al." Purchased by Attribute-Based Planning "Supplementary systems and methods"; "Application Group Planning System and Method with Attribute-Based Planning," by Cramp ton, etc., applied on November 5, 2002, with serial number 10 / 287,773, agent file number 82001.0392, etc. ". DESCRIPTION OF THE INVENTION TECHNICAL FIELD The present invention relates to a system and method for planning the utilization of manufacturing resources. More particularly, the present invention relates to an attribute-based planning system and method that can operate in a highly complex and dynamic environment. And there will be plans for the utilization of multiple resources to meet the requirements. Prior Technology For any business with significant manufacturing capacity and / or multiple sources (2) 200305088, planning the use of manufacturing resources, a reduced task. Today's competition becomes more real, because today's business philosophy, such as just in time source planning. The problem of satisfying demand is always in a frightening environment. The business trend of planning the use of resources has forced many businesses to follow the concept of a certain room. This requires highly disciplined resources ~ a large network of suitable farms, a sound bank, Transportation and sales and other production / transportation positions consisted of Cao Yuyun's price and real estate. In addition, these locations one contains some resources, such as the mother 4, assembly, spring, and all storage equipment that will interact and work together to produce TO to customers. The complexity of making a separate network from time to time often makes it very difficult, and a huge number of resources that usually make up a U or supply chain network are only / originally listed in the plan. Many other factors will make attempts to plan planning, and to include resources in the manufacturing or supply chain network into the planning table Φ; 4 Μ < increased complexity. For example, companies usually receive reel from various customers together, w is a variety of bites, each order and each customer have different priorities and its two advantages are better. In addition, the company will need to be able to plan for the predicted future orders, and use it to determine when the materials must be ordered and reserved for the expected customers > ~ 田 — / 、 户 w 丁 早 < Guli. For example, car manufacturers may receive orders from fleet owners, car rental companies, individual residents, or any number of large and small customers. Each order will contain many items. For A car manufacturers, these may be different styles of cars with different options. Each of these orders can also include other important information such as the date and range of dates the customer wants to receive or be able to obtain the order item, the location where the item is available, such as the location of the specific operator, the customer's choice of packaging, And a viable alternative configuration. Therefore, each order typically has 200305088 with many parameters that define how, what, when, and where the order must be completed. Many manufacturers today adhere to one or more business philosophy, such as the principle of just in time, to reduce costs. Unfortunately, each of these principles can be an obstacle to another principle that manufacturers may also want to follow. In addition, such a philosophy would increase the complexity of trying to plan the completion of orders and make it more difficult to plan the use of resources in the supply chain network. For effective and correct planning, preferably, the planning system will be able to take into account the various constraints that can be associated with each network resource. These restrictions can be based on factors such as time, quantity, quality, type of items available, and the like. Preferably, any model used to represent a resource network will also be robust so that the dynamic characteristics of many resource networks will be considered. In any model using a planning system, these increases in flow restrictions increase the overall complexity of the planning process. In addition, the model used for planning must take time into consideration. In order to plan network resources, real timing requirements must be considered. This means a real time delay. For example, when parts are really needed, the additional time needed to order the component parts for the assembly line needs to be considered. In addition, in any effective planning system, the time availability of the project (such as a finished product), the operation of the process, and the raw materials need to be considered. For various reasons, some of which have been described above, the cost of planning the use of resources to meet demand can be prohibitive. In order to efficiently and effectively meet the planning needs of today's business, it is very robust, and can identify and accommodate many constraints and sometimes business conflicting goals. Planning systems and methods (4) (4) 200305088 method is very desirable . Therefore, the present invention is directed to a system and method for planning the optimal use of commercial resources to fulfill orders. More specifically, the present invention provides a system and method for generating and maintaining restriction and attribute-sensitive planning of the use of multiple resources located in multiple locations to form one or more orders. Traditional planning systems for placing orders on schedules and allocating resources are often driven by inventory holding units (SKUs). Another approach is to use a property-based approach. The constraints and business rules that govern supply chain planning are often driven by certain basic characteristics (attributes) of the product, market, and operating environment. Therefore, the representation of the model should be achieved from the perspective of these attributes. According to a specific embodiment of the present invention, there is provided a system called an attribute-based planning (ABP) system. This system may include a computerized storage device for the transfer of the ampoules. If one or more subscriptions with attributes a scare the need, they can be entered into the system, which will generate a plan for the use of resources within the network. The order can be an internally or externally generated order, or it can even be the customer demand as shown in Table 2. After processing the order, the ABP system will immediately plan for the utilization of network resources to complete the demand. According to another specific embodiment of the present invention, inventory holding. Thousands of 70 attribute definitions D) Groups are generated and defined. The ABD group according to the present invention uses SAD groups to provide various system functions. For example, the " m ^ group can take orders in priority order, and organize resources into parts such as food and / or bill of materials (BOM), and groups of similar things ~ and *, called 1 *, , And. In order to fully enter the various functions, various tables will be produced. For example, the table 200305088 (5) will protect Wifi including temporary tables for unplanned orders, BOM and configuration tables, SAD groups, and the like. In addition, a transportation matrix will be created to track and consider transportation issues.

According to another specific embodiment of the present invention, the program for planning the use of resources to meet the requirements includes an initialization program. The initialization procedure may include many steps, which may include steps to generate and / or generate a static model. To model the network of resources, various projects are better defined. These include available resources, locations, various types of restrictions including capacity and ancillary restrictions, time buckets, business rules, user and customer preferences, configuration, transmission matrix and beta, and the like. The initialization step will include a step of initializing the bucket interval. The initialization of the bucket interval can be achieved by combining one or more restrictions with the bucket interval. The initialization procedure will also include steps to place the initial distribution and configuration materials. The initialization process will also include steps to generate temporary tables and tables for unplanned orders.

According to another embodiment of the present invention, a procedure for processing an order is included in a procedure for planning the use of network resources. The second procedure will include selecting a set of orders based on the SAD group, loading a window with a set of orders and their related information, prioritizing each order in the window, and processing each order in the window according to its attributes Steps for each order. The ABP system is planned by processing orders in groups, one group at a time. Orders for each group processed are placed in the window. Orders in the window are processed in order of priority and planning is handled based on their attributes. The data related to each order is also loaded into the window. Such information may include, for example, a SKU-based BOM, a configuration, a inventory holding unit for a minor item, a -10-200305088 counterfeit inventory holding unit, and the like. According to another specific embodiment, the procedure used to process the order will include processing each unplanned order in the window—hours, hours, and hours, and into a premature < step. Before planning unplanned orders, the company prepares for the initial allocation of resources to consolidate the capital used for specific orders. Once the initial allocation has been generated, it is used for Planning meeting Αβρ system will re-check BOM, group sense, related finished product inventory silly surnames ^ "Bei keep early, secondary item inventory holding unit, SAD group, and similar ,, wo, '' to plan each order .Each configuration (, related SAD group, minor project SKU) related to each n will be re-examined and inspected to determine the location / resource / barrel interval opportunity The best opportunity. According to another embodiment of the present invention, the combination of ▲ # “仏 embodiment, judging the best opportunity for each order will be achieved by the following step H_. First, the configuration will be selected and the allowed position will be processed according to priority ^ f 0. ^ The highest priority location / finished product holding unit is then selected. Ϋλ Ά ^ m Initialize the finished product inventory holding unit ’and judge it for the highest priority ^ ^ ^ 2 Set only the set of allowable resources. The decision will be made on the material ARP used for each resource. In determining the feasible surnames of the materials, the ΑBP system first checks the assets σ && +, # # 'to determine whether the inventory is available and the quantity required. If according to the specified parameters defined by the user or customer (such as the date), q ^ reward source inventory can not completely supply the goods, the system will check another — # ^ ^ -A feasible method to meet the needs of this source. Other methods to meet the demand M $, and I include, for example, replenishment by the manufacturer, replenishment by the purchase of supplements, and / or supplementation by replacement. Once the nature of the materials used in the resource is determined, the ABP system will make restrictions on

⑺ Evaluation of performance and check of material capacity compatibility. These steps are repeated for each acceptable location / resource / bucket interval opportunity. Then each location / resource / barrel interval opportunity is evaluated based on various goals and customer preferences. Then the best location / resource / barrel interval opportunity is selected for the purpose of planning the use of network resources, and the output will be generated. According to another embodiment of the present invention, freezing the SAD group is generated and used to freeze one or more orders. This can be used to confirm that the order has been planned, even if the order is not feasible. According to another specific embodiment of the present invention, the ABP system recognizes a multi-level objective function to determine the optimal location / resource / barrel interval opportunity. Multilevel objective functions provide the criteria to achieve the desired planning results. Preferably, the ABP system incorporates a multi-stage objective function to determine the optimal placement of orders for planning purposes. If the ABP system identifies multiple opportunities for planning an order, the ABP system ranks each opportunity and selects the best opportunity based on multiple goals. According to another embodiment of the present invention, various tables are generated to provide some functions. These tables include, for example, a predetermined allocation table, a BOM table, a SAD group table, and the like. According to another specific embodiment of the present invention, a group of orders will be selected and planned by generating one or more SKU attributes, where the SKU attribute group is related to one or more orders by attributes, based on one Or multiple SKU attribute groups to prioritize orders, select one or more orders, select orders from the window, and plan the use of resources based on the priority of orders loaded in the window to achieve From -12-200305088 (8) Select the order in the window. According to another specific embodiment of the present invention, the decision to supplement the manufacturing resources can be achieved by determining the attribute data about the order, where the data includes an inventory holding unit related to the order, and one or Multiple configurations are combined into the order, where the configuration includes one or more minor item inventory holding units, evaluating the configuration based on each configuration and determining whether each configuration is feasible, and selecting to use based on the evaluation of the configuration A viable configuration for planning the use of resources. According to another specific embodiment of the present invention, the decision of supplementing the purchased resources can be achieved by determining a time item, wherein the time item is a specific point in the time or period of the order and is determined based on the time item Time events, generating a timeline including time events and time items, selecting an available scheme from a group of predetermined schemes based on the timeline, and generating an output based on the available schemes. According to another embodiment of the present invention, the schedule control can be used to obtain the optimal resource usage plan. Inclusion plan control is a scheme used to influence the search of bucket-like intervals to find feasible opportunities for placing orders. "There are many types of incorporation plan controls available, including forward, backward, and just in time. Internal, frozen, and excluded from the schedule. According to another specific embodiment of the present invention, what is provided is a method for planning the use of network resources to fulfill the requirements as defined by the order. The order system has attribute data, and the method includes defining parameters of the order, combining one or more configurations to the order based on the order attribute data, and determining an acceptable location-resource-barrel interval opportunity based on the configuration, where the group ( 9) (9) 200305088 State includes one or more inventory holding units, evaluates each location-resource_ barrel interval opportunity, and selects location-resource · barrel based on the evaluation of each location · resource_ barrel interval opportunity One of the interval opportunities is regarded as the most position, resource-bucket interval opportunity step. According to another embodiment of the present invention, what is provided is a method for planning the comparison of network resources to fulfill the requirements as defined in the bill. This method includes first identifying orders that are related to order-based attribute data. The finished product inventory unit, the finished product inventory holding unit #, the initial-based ... inventory holding unit, determines the set of allowable locations and the set of allowable resources for the parent allowable locations, and evaluates for each A position resource, a permutation opportunity, and a combination of permissible position and permissible resource are selected as the best position-resource-barrel interval opportunity based on evaluation. Other features and advantages of the present invention will be presented in the following description. One of them can be understood from the description, or the purpose and other benefits of the present month can be learned by implementing the present invention. Explain and apply for the scope of the patent, as well as the structure specifically indicated in the drawings to achieve and achieve. To achieve these and other advantages, and in accordance with the purpose of the present invention, specific implementations and extensive descriptions will be made. It must be understood that the previous general description of the present invention and the following detailed descriptions are exemplary and illustrative, and are intended to provide further explanation of the invention as claimed. DETAILED DESCRIPTION Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The invention disclosed herein takes the contents of the US non-tentative application incorporated into the common waiting judgment and general assignment as reference: November 4, 2002, the application 'No serial number has been assigned, agent file number 82001.0350 of Crampton et al. "Order group planning system and method with attribute-based planning"; applied on November 4, 2002, has not yet specified a serial number, agent document number 82001.0390, "by using attribute-based planning Supplementary systems and methods manufactured ";" Applications made on November 4, 2002, and not yet assigned a serial number 'Agent Document No. 82001.0391 "by Crampton et al.," Supplementary systems purchased through attribute-based planning and Method ";" Application system and method for ordering group planning with attribute-based planning "by Cramp ton et al., Who applied on November 4, 2002 and has not yet assigned a serial number, agent file number 82001.0392, etc .; July 13, 2001 "Application of Strategic Transportation Planning System and Method" by Weber et al., Application No. 09/903, 8 5 5 and Agent Document No. 8200 1 -0 1 48; and Application No. 09/965, October 1, 2001, 8 54, Z are foss of agent file number 82001-0189, etc. "Order group planning system and method including attribute-based planning of supply chain management systems and methods for joint research". The present invention is a system and method for providing optimal planning and planning of resources in a manufacturing or supply chain network. This system, called the Attribute Basic Planning (ABP) system, models SKUs and attributes. The ABP system and procedures implemented by this system produce outputs that are used to define the planning for the use of resources in the supply chain. The output can be text, raw materials, graphics, or any other form useful for planning purposes. The ABP system can work with 200,305,088 00 other business plans, plans, purchases, joint research, and available types of systems and applications (including all network strategies commercially available from Manugistics) , Network sequencing, and network research) as interfaces. The various functions related to the AB system can be best understood by following the accompanying drawings that describe various concepts used to implement the novel aspects of the present invention. The following description of the invention will refer to various items, some of which are clearly defined in the following terms.

Terminology ABP system: Attribute Basic Planning (ABP) system. A planning system to plan the use of resources to meet demand. BOM: Bill of Materials. A structure that describes the various ways in which SKUs can be manufactured. Each record typically combines parent items with child items, and the pull amount tells how many child units are needed for each parent unit. In addition, attribute restrictions exist, which inform when this record is available.

Bucket interval: A time interval, usually used to limit and configure things. In the supply chain optimization system, the planning scope is usually divided into many bucket intervals. The barrel interval can be the same length or it can be shortened when the duration of the barrel interval increases. For example, a bucket interval can be defined as a week of the day, three weeks of the week, and three months of the month. The following will give 13 barrel-shaped intervals covering 4 months. If the bucket interval is modeled on a 4-month scale, about 120 bucket intervals will be modeled. Because the fewer bucket intervals the system models, the smaller the model and the faster the algorithm, the number of bucket intervals is important. -16- 200305088

(12) Configuration ·· — A group of BOM records, which fully define the specified configurable configuration for SKU orders. Constraints: Any kind of restriction placed on any entrance, such as resources, will be identified by the ABP system. Limitations can be hard (a solution that should never evaporate) or soft (a solution that should attempt to match). Constraint Bucket • Restricted buckets have a capacity limit. There will usually be a maximum. There will also be # information to inform how much capacity may be overused and the cost of doing so. Constraint Rules:-A short way to define the capacity of the bucket interval. For example, calendars can be combined with restrictions that are distinguished by week level, where each unit available is converted into a quantity of capacity. For example, if there is a labor restriction related to one person that is distinguished by week, and there is a way to define the work that can be performed on a shift, the second shift is from Monday to Thursday (1 person * 4 days * 2 shifts / day * 8 Hours / shift = 64 hours), and one shift on Friday (1 person * 丨 day * 丨 shift / day * 8 hours / shift = 8 hours), then the capacity of a week will be 64 + 8 = 72 person hours . Demand: The requirements on the system include external requirements and dependent requirements. External demand includes customer orders and forecasts. Dependent needs are the additional requirements needed to meet independent needs. Dependant demand: This is a set of orders generated by the system. It is the result of arranging materials and capacity in the direction of independent demand. Effective Need Date: This need date is less than the shipping time required to deliver the item to the designated location. FGSKU: Finished Product Inventory Holding Unit. SKU is a finished product. -17- 200305088

(13) Flag: A flag is used to indicate the existence of specified conditions, preferences, restrictions, and the like. Flags can also be used to control the planning process. For example, the ‘flag’ is used to indicate that schedule opportunities are not feasible, so the ABP system needs to look at other schedule opportunities. Freeze Group: —Sad group, by which every order related to this group will be frozen. This is used to plan the cycle to determine if the order is not feasible, the order will be included in the schedule. Freeze Group Table: This table is used to confirm that it should be considered as the SD Group of East End. Independent Demand: This is a group of orders that are shipped to the system relative to the dependent demand, which are related to the orders generated by the ABp system. Initial Assignment: An assignment transferred to the system, which indicates that the previous assignment should be fulfilled regardless of whether it is feasible or not. Each time the planning process is executed, the initial allocation will be placed in a bucket interval before any other order planning. The configuration of the initial allocation confirms that frozen orders are always in the same location as planned. Location: Location is somewhere in the supply chain. Each location will have a name. Need Date: The most desired date for order delivery and / or availability. Maximum Earliness: The time period before the date on which the requested item will be accepted. This value is specified by the SAD group. Maximum Lateness: The date when the requested item will be accepted • 18- 200305088

(14) Later time interval. This value is specified by the sad group. Multi-level Objective Function: The standard used to achieve the desired planning result. Preferably, the ABP system will incorporate multi-level objective functions to determine the optimal position of the order on the plan. If the ΑBP system finds multiple opportunities to plan an order, Αρ will classify each opportunity and select the best opportunity based on multiple goals. These goals include, for example, 'late (a relative to the date of the demand for the order) Measurement of planned orders), full utilization (a measurement of how to fill the barrel-shaped interval of the planned order's capacity limit), and transportation (transportation costs between the location of the resources of the manufacturing order and the location of the customer on the order ). Order: Each order contains reservation and user-defined attributes. Reservation attributes can include, for example, identity, SKU, quantity, start date (optional), demand date, customer, priority, and valid demand Date. Note that both the order and the SKU can have values for user-defined attributes. If both have values, the value of the order always takes precedence ^ For example Orders < Blue truck with sunroof and alloy wheels for a customer named Joe Dealer, so the 'finished product (i.e. order) is a truck with the following attributes (blue, 夭 ® gold wheels and Joe Dealer).% H Parent Item: — a kind of B0M record, related to the parent item and / or 0 See B0M. In Plan (Plan): — a kind of demand for resource allocation over time ^,; a certain period of time (also That is, planning scope) to satisfy one or more customer orders. Period Maximums: can be used to specify the barrel area -19- 200305088 (15) to take a large number of products. Resource Can be any physical resource, which is the source of items including assembly lines, manufacturing machines, warehouses, storage locations, storage cabinets, suppliers, and the like. Usually each resource can be uniquely identified by its name and location SAD Group: SKU attribute description group. SAD group is related to various modeling concepts and informs the order is available. Each SAD group can have a list of SKUs, and A list of some or all of the attribute values for the attributes of the order. For example, if there is a color (red, blue) and skylight (yes / no) attributes about model 1 @ 1, model 1 @ 2, and type 1 —2 ^ .2's SKU exists, then someone can define (red) (sku: (M ^ 1 or model 1 @ 2) and color (red)) the concept of red throughout all Model 1 vehicles. SAD group. The SAD group can be used to control how the ABP system places orders in the schedule and plans the use of resources. For example, '玎 Order Group' can be used to determine the earliest and latest time about order group, schedule control about order group, define the order of "best" configuration about order, and Goals, and similar things, how to order. Each SAD group can be processed in order of priority, so that orders belonging to a SAD group can be listed in the plan table before orders belonging to a lower priority SAD group. Scheduling Controls: Schedule books used to influence the way ’barrel-like intervals are searched to find out the feasible position of the order. There are many types of schedule controls available, including advance, postponed, just in time, frozen, and not included in schedules. -20- 200305088

(16) Scheduling Opportunity: Defines a position / resource / barrel interval or resource / barrel interval for the opportunity to place an order in the schedule. It satisfies the order and barrel interval, resources, and And / or all available restrictions for the location. SKU: Each SKU is related to the project and location. SKUs have predetermined attributes and user-defined attributes. SKUs can be raw materials, products in process (" WIP "), finished products, or WIP and finished products. SKUs can be hard or soft restrictions, and if the raw materials will have a supplementary model, it will tell if supplementary materials are possible, and If so, how to do it. Smoothing constraint (smoothing constraint): a type of constraint that will allow the system to calculate the average amount of capacity per unit of time regarding the limit based on the load and the total amount of time available within the range. The maximum value of a bucket interval will multiply the amount of available time by the average amount per unit time. Subordinate Item:-A B0M record related to the parent and secondary items. See the definition of bom. Use User Defined Attribute (UDA): — An attribute of an implementation characteristic. For example, customers of a car implementation have color attributes for each type of car. Customers in a computer implementation may not have color, but may There will be hard disk size. General Concept The present invention relates to a property-based system for planning orders and resources. To facilitate understanding of various aspects of the present invention The following examples will introduce concepts that can be used to understand the innovative aspects of the present invention. -21-(17) 200305088 According to one of the embodiments of the present invention, The ABP system is a robust planning system. It can operate in a highly complex and highly dynamic environment. Referring to Figure 1, it depicts a block diagram of the Ab p system 100 in an example environment. The ab p system 1 〇 〇 Can be transmitted and implemented with the combination of software and disaster. The ABP system 100T includes a data base 1010 $ thick 4 and a single unit such as a personal computer, workstation, servo X and the like One or more databases on one or more computers are used as the interface. Figure 1 shows the manufacturing network of an automobile manufacturer, which includes two basic car models, SUVs, and Minivan because of a selectable number. (For example, power drive windows, sunroofs, and similar objects) are provided by car manufacturers, so the network must be able to make many changes to the three native model types. The network includes three manufacturing plants in Atlanta, Denver, and RokkVlUei. 102 to 106. Each site 102 to 106 includes multiple resources in sequence i! 〇, 12 〇, and i 3 〇. Resources ii 1 2 0 and 1 3 〇 can be assembly lines, warehouses, machinery and equipment, inventory lists or any Other entities are the source of any finished product that can be requested by the customer. In a sense 'each resource 110, 120 and 130 can be unique and each can have a different capacity, operating time, product line, and Other restrictions. Restrictions may be specific for resources, resource groups, locations, or resource groups. Furthermore, automobile manufacturers can implement certain rules, which will place more restrictions on resources and locations. Each resource 110, 120, and 130 may be associated with one or more materials 140. Material 140 is any component part or component material, or even a finished product that may be required by resources to produce a finished product. One way to look at resources 110, 120, and 130 is to treat them as a well that can be supplemented by, for example, making, buying, or replacing. Although not shown in -22 · (18) (18) 200305088, other materials can also be used as material 14. That is, the material 140 as the resources 110 to 130 may be composed of other materials. The automaker has many customers 150 and will deliver orders 160 to the automaker. Orders will be grammatically conformed by the ABP system 100, and a plan will be generated that makes the best use of resources to fulfill multiple orders. Each order contains relevant information, which can be used to generate certain parameters when placing the order in the planning table. These include the date and location of the requested transmission, the identification of the requested product, the number of requested products, the identification of the customer, the mode of transmission, and the like. The finished product requested in the order can be considered as a "FG SKU". There will usually be multiple configurations and component materials to meet the requirements set by each FG SKU. For example, suppose a customer orders a car. Into one

Steps assume that all three components required to build a car are components A, and C or D. In this example, there are at least two possible configurations.

The sedan has elements A, ..., and the sedan built has element Am. These different configurations and component materials can be listed in the bill of materials (here BOM). In addition to the above restrictions and order parameters, 'manufacturing resource planning system + planning network resource utilization must be able to adapt — some other important factors such as' if the finished product is to be transmitted at or near the desired date: order And / or materials to make the component parts and the right time are needed. If the material is not ordered at the appropriate time, then the material fulfilling the order will be one of the keys to effective and timely manufacturing capabilities for ordering the component parts before the time of the required part. Planning and inclusion in the schedule is a continuous process. Therefore, any effective regulations • 23- (19) 2003050S8 planning system must be able to adapt to the list before the list ... Table new use of available manufacturing resources is better, believable II Γ: already listed in the plan table Assignment or order. Ϋλ ^, and planning system will be able to adapt to habits, business rules ^, and more than 4 types of manufacturing business rules network. For example, Me and M include complicated manufacturing, and the user can follow the request within the time just before the transmission date. Therefore, the manufacturer may prefer to be the earliest and the earliest. Date, pass. These goals are unique to each manufacturer, and possible, different types of orders are unique (via models, customers, priorities, etc.): and; help manufacturers understand their long-term goals. ^ And ^ Therefore, a system that will eliminate and adapt to the special needs of the manufacturer will be very satisfactory. Companies (such as large manufacturers) typically receive orders from multiple customers and / or make predictions for customers who have not yet given their orders. Kelu may be a third party, a division within the same company, a supply chain partner, or any other seller. Each order received by the company can be defined by its attributes such as customer name, order identity, requested SKU, demand date, quantity, and the like. SKUs are usually defined by at least two attributes, called items and locations. SKU can have values for user-defined attributes. s K U can also be grouped into a mouthful (FG) SKU, a product in process (WIP) SKU, or a raw material SKU. Raw materials and WIP SKU items may be secondary in the BOM. A minor item is a component part or material that needs to be used to produce another item. It should be noted that the value of the user-defined attribute on the order can invalidate the value of the user-defined attribute on the SKU. For example, SKUs can have incorrect preset values for sunroof user-defined attributes (meaning no sunroof). Certain orders can invalidate this value -24- 200305088 (20) and set the sunroof user-defined attribute to true. These concepts can be best understood with the following examples. Assume that the FG SKU can be defined by the following attributes [item == car, location = Atlanta, select = power steering wheel]. It is further assumed that parts A, B, and c for building the F G S KU assembly for the basic car model and additional components for steering wheel selection ("steering wheel assembly") are needed. In this example, there are four secondary item SKUs: component A in Atlanta, component B in Atlanta, component C in Atlanta, and steering wheel component in Atlanta. The A B P system 1 〇 〇 can organize SK U ′ and user-defined attribute values into S KU attribute description (here, “S A D”) group. The s A D group of orders will be related to any order that has the same attribute that "at least" defines the SAD group. Therefore, as long as it has attributes that at least define the SAD group, orders with more attributes than those that define the SAD group will belong to the sad group. For example, suppose the SAD group is defined by the following two attributes [item = car and location == Atlanta], regardless of whether the order is related to other attributes, all orders with these two attributes will belong to the SAD group. For example, orders with attributes [item = car, location = Atlanta, and power window = Yes] will belong to the SAD group. Orders that meet the conditions defined by the SAD group are considered part of this group. The ABP system 100 uses a sad group to provide some functions. For example, among other functions, the sad group can be used to: define a list of materials (b0m) that are vulnerable to attributes for an order; Restrictions apply to orders; define earliest / late date for orders; define dedicated resource groups for orders; apply rules to orders; define for orders-25- (21) 200305088

Included in the plan, the order will reach the response time, or the user will not usually be shown to the planning process, taking the example of the SAD group as the color = color, genus, $ 丁 单 will be every The species, for example, the attribute index and the attribute name confirm that the index of the custom name-value pair is ^ -1 ". With "or" to group: attribute value from the order. Belong to seven behaviors. For example, "color", "blue table control; define the sorting criteria to execute the pre-order in the planning process; apply the rate model to the order about the location; and to the order. The order fulfillment means that the order reaches the anti-soft limit and can be planned At the time, because it has reached the anti-hard limit. The share and some related values can be displayed in an internationalized, partial format. Grouping various items into SAD groups can simplify the rules and provide the best planning solution. The shell material can be stored in the SAD group table. Simple SAD group list—the group defined by the attribute name and value group: attribute name f value = red. For all groups with red value in the color attribute— Part. A certain field in the table will form a definition for the SAD group name / attribute value pair. These include, type, attribute name, attribute value, indicator, attribute matching flag on flag, and similar things. Attribute Type and attribute name order attributes for comparison. The attribute value is used to compare the data of the order. The indicator can be used to specify how many of the groups in the group are related (for example, "and" Or "OR" connection relationship) means that name / value pairs are evaluated with the rest of the group "or name / value pairs with the same index are edited together with" and "and the rest are edited. The attribute matching flag specifies whether the attribute value should match or not match the existence from the name / value pair. The flag specifies whether the attribute does not exist on the order. If the attribute value is a color, the allowed value may be "red ", Or no value stored. This flag indicates whether there is currently no -26- 200305088

(22) There is a value match. Some attributes can be used to define SAD groups. These attributes include, for example, item identifier, planning location, request location, start date start, start date end, demand date start, demand date end, preferred date start, preferred date end, minimum number, maximum number, minimum priority Rights, maximum priority, customer name, customer location, SKU, and any other user-defined attributes that can be used to implement the ABP system 100. The planned location attribute can be used to group orders by its planned location. The requested location attribute can be used to group orders by the requested location of each order. Start Date The start and end date attributes are used to group orders by a range of start dates. The start date start and end date end attributes can be used individually or combined with the start date that defines a range. The start date identifies the fastest (ie, earliest) barrel interval in which the order can be planned. This is an optional field, which can use the latest of the following dates [range start, order start date, order demand date-earliest]. The start date is used to identify the fastest barrel interval in which the order is allowed to be planned. Note that capacity or material feasibility may delay the actual start date, but not earlier than the earliest start date. The demand date start and demand date end attributes are used to group orders by a range of demand dates. The start of the demand date and the end of the demand date can be used individually or combined with a range of demand dates. The preferred date start and preferred date end attributes can be used to group orders together by a range of preferred dates. It can be used individually or in combination with a requirement date that defines a range. The minimum and maximum quantity attributes can be used to group orders together based on the acceptable, minimum, and / or maximum -27- (23) 200305088 quantity requested for each order. The minimum priority and maximum priority attributes can be used to group orders by priority. The A B P system 100 supports property-based bills of materials (here, BOM). However, unlike the BOM in traditional planning systems, the BOM related to the system 100 allows the modeling of selection-based and rule-based material requirements. For example, in the automotive industry, automotive wedges often have some characteristics and options. Each feature or option (such as a power window) drives the type of component that will need to provide such a feature or option. For a car with a power window, materials such as a power window assembly and a 4 w horse stable, m ^ 1 Wu (to drive the power window) will be required (ie, component parts). The presence of a particular combination of properties or choices also affects the materials to be used in the combination. For example, suppose that in the above example, in addition to the power window selection, a second selection (auto sunroof) is needed. This will result in a 4% motor requirement (when the power window is present, which was only required) in addition to the sunroof assembly, and a 10W motor requirement. The BOM is basically a method for SKUs or finished products, and shows the required component parts or materials for all possible configurations of the finished product to meet the attribute requirements of the SKU. For the auto industry example above, the BOM for a SKU (for example, a car model) can show components of various acceptable configurations for building a SKU (for example, 'power window assembly, 4 w motor, engine, brake, etc. ). So there are more components, more configurations are possible, and more component parts or materials will be needed. The presence or absence of this feature has driven the demand for materials. Use alternatives when you need to try to make the configuration feasible. Replacement models can produce helpful replacements. The substitution model is used to identify substitutable s κ u for known S K U, with a priority of -28. 200305088

And the pull amount of the substitute. If the basic configuration is not feasible, an attempt is made to replace the SKU. The chain allowed in this one allows SKU2 to be substituted for SKU1. If SKU2 is not feasible and has a replacement SKU3, SKU3 will be tried. Cyclic substitution will be detected and not allowed. Substitutions can be restricted by the current SAD group. SAD groups can be used to group other items. For example, SAD groups can be used to generate dedicated resource groups. Dedicated resource groups are generated and used to limit the orders that can be planned for specific resources. Dedicated resource groups can be implemented using SAD groups. Any resource referring to a dedicated resource group will only be able to make orders belonging to the SAD group related to the dedicated resource group ^ The SAD group can be used to group other items, some of which will be explained in the following paragraphs. In a preferred embodiment, the ABP system 100 is a barrel-shaped interval planning system. This means that the ABP system 100 attempts to plan the order into a bucket interval. The bucket interval can be defined by many parameters such as time, limits, resources, and the like. For example, the order shown in FIG. 1 that requires one of the resources to be listed in the schedule may be assigned a barrel interval defined by a time interval, and is specific to the resource at this location. For example, suppose the order has been assigned the resource "A" 11 located in Atlanta position 102. Then, the order can be assigned time such as r September U to September 12 "," resource A ", and" Atlanta, gA " Bucket intervals defined by intervals, resources, and locations. To support the various features provided by the present invention, some database tables are generated. A table consists of columns and rows. The values of the columns and rows will depend on the table itself, and the native table produces BOM, bucket interval, group, SAD group, inventory list table, items (all finished products that should be included in the list and sub-29- (25 ) 200305088

Resource groups, and some similar materials), locations, resource entities. All procedures In order to meet the needs, all procedures used to generate a plan for the utilization of resources can be divided into two sub-procedures. Referring to FIGS. 2A and 2B, there are two high-level processes 200 and 220 for generating a plan for planning or modifying the use of the existence of network resources to achieve the requirements according to a specific embodiment of the present invention. For illustrative purposes, process 200 will be referred to as the initial process and process 22o will be referred to as the order planning process. For each process 200 and 22, a brief introduction to the various steps that define each process 200 and 220 is provided below, followed by a more detailed discussion of specific steps and concepts introduced in the two procedures . Jane I 'When the static model is loaded and / or generated, the procedure 2000 will be opened in step 202. Static models can be defined or loaded by, for example, data about available resources, locations, calendars, rules, restrictions, business rules, SKU SAD groups, bills of materials (BOM), dedicated resource groups, and the like Modeling. This includes SKUs that can be labeled "keep in memory" and the BOM relationships involved by these SKUs. At step 20 *, the bucket interval is initialized. To initialize bucket intervals, each bucket is related and / or defined by a restriction. These restrictions can include, for example, 'capacity restrictions'. In step 206, the initial allocation and configuration of the deer and material will be placed. In step 208, one or more unplanned booking, early '^ temporary tables are generated. A more detailed description of some of these steps is provided below. y. After completing the initialization program 200, the second program used to process the order is 222. -30- 200305088

(26) Begin.

In order to achieve a demand as defined by, for example, an unplanned order (ie, an unplanned order), the second full procedure 220 is used to plan the utilization of network resources. Between T ' When a portion of one or more orders is selected at step 222 ', the procedure 220 may begin. A part of the order is a group of orders, each of which will be related to a specific 8-8 13 group based on the attribute value of the SAD group. At step 224, the next window is loaded with one or more selected parts of the order and its related items. Items that will be relevant to one or more orders include, for example, configuration, BOM, minor item SKU, finished SKU (FG SKU), and the like. At step 226, each order in the window is processed in order of priority. Those with higher priority will usually be listed on the plan before those with lower priority. In step 228, the highest priority order that has not been planned is selected, and this is planned. If there are any more unscheduled orders in the window, the next one will be listed. * ^ Γ Call the network priority The order will be listed in the plan table, as indicated in step 230, otherwise in step M], the allocation will be written, so that the merchant needed to complete the order will be saved

Source and / or material. Once the allocation has been written, the temporary data will be unloaded at step 234. In step 236, it is judged whether other ‘eighth orders need to be processed’ and if so, it returns to step 222, :: program 2 2 0. Then, enter the specific steps, outlines, and detailed descriptions of the procedures 200 and 220 described above. When in step 002: <More static compilation, eight-going, see-through model, spoon static J Shao Dao, the initial procedure 200 usually starts. For example, η — out of resources, dedicated resource groups and their locations (:: Definition of table 4 or warehouse location -31 · (27) 200305088 The general order of the general needs or the schedule is set after delineation It is related to the calculation of the supply, the spoon. The information about the capacity and items available for a specific resource, etc. 4 can also be defined. During the initial modeling, often static restrictions can be defined. Transmission will occur Matrix to define the use of; i includes the various routes that need to be used to transfer to the specific customer's supply chain

Special, ^ between. Such as calendar, bucket interval, business rules, SKU, BOM pages can be defined. Those skilled in the art will understand that during the soilization phase of the planning process, some other general static entities can also be defined. Generally, it would be better to enter some data until the last moment. Females will enter dynamic data that often changes direction, or will not be available until the last moment, just before planning an order. This ’, after the static part has been defined, the moving knife of the model will be entered at some point. Just at the beginning of the planning process, it will generally be entered as new order modification order data. Just at the beginning of order planning, it is even necessary to update the general static data (such as information on restrictions, resources, and business rules) on a weekly basis and input information about those. New restrictions that are just in the scope of planning or order specifications regarding specific conditions such as previous customers will also increase. New or revised business rules are also added at the very least to reflect frequent changes in business needs. Finally, the latest order will usually be entered at the last moment before the single plan is implemented. Preferably, the procedures 2000 and 220 will generate a resource utilization plan to meet the demand (for example, independent and dependent orders). ^ Special bucket intervals will retain special orders. Bucket intervals are time intervals that are related, for example, to resources and presentation opportunities. In step 204, the bucket interval is

(28)

Set the limit to initialize it. These limits may include limits on quantity and limits on quality. During the initialization step 204, all restricted states (barrels) will be generated and the capacity will be set in these states. In barrel-like zones, restrictions are increased and enforced. These restricted bucket intervals are parallel to the resource bucket intervals. So, for example, specific limits (such as resource capacity limits) are defined for specific barrel ranges. For example, when it is limited to another level at different time periods, the total capacity for a particular resource is limited to a certain level during one period. Restrictions are modeled using three database tables (restriction tables, restriction rule tables, and bucket interval tables).

Before the AB P system 1 0 0 makes a plan to reach any unplanned orders, during the initial step of step 2 06, the orders with a predetermined allocation are planned. Initial allocation is used to "freeze" orders. That is, it can be used to save locations / resources / barrels to fulfill specific orders before the planning process is performed. It can be done with an initial allocation that will usually be placed in a barrel section before any other order is planned to determine that it will always be in the same position on the plan. Prior to order planning, orders with pre-assigned allocations will preferably be included in the planning table. This can be done by resorting to an initial allocation configuration routine. In some cases, a pre-allocation table is generated to define a predetermined allocation. Such a table would contain allocation information such as: the identity of the order to be allocated, the resources in the allocated order, the bucket interval used for the order to be included in the planning table, and the number of orders related to the allocation (which may not belong to this) . The BOM configuration information about the initial allocation will be stored in the BOM table. Once the hope is reached, the initial allocation is processed in the pre-allocation table. Referring to Figure 3 A, it is -33- 200305088

(29) Process 3 for configuration of initial allocation. In step 3 02, the order quantity BOM in the initial allocation is placed in the design resource in the design ^ ten barrel-shaped interval configured using the design BOM. At step 04, the material availability of the unapproved material is updated. The material in this article can be any component material or finished product used to supplement resources. In step 306, a determination is made of the limits available for the bucket interval / resource. Restrictions are usually barrel-like intervals / references, ΛM / position-dependent. Two factors can be used to determine whether restrictions are available. Sheng Φ 1 &gt; Only design resources that are applied to the initial allocation will be considered ~ ..., π In other words, the resource name used to configure the restriction must really match the &lt; or the resource group used to configure the restriction The group must include initial assignments and design resources. Second, limiting the response should not prevent the initial allocation of,, and A directly in the design barrel-shaped interval on the design resources. In step 308, the capacity of the design used by the researcher in all available limits will be even greater. In step 3, the information about the allocation of the order is recorded. In step 208 of the process 200, one or more temporary database tables are generated for one or more M & M planning orders. These unplanned orders are already targeted orders that will be precisely planned by procedures 200 and 220. This table can be divided into gp ^ and & Tian Yuan to identify all orders that have not been completed. This table can be passed through the 升, 丨 surplus rules &quot; ordering 20〇, and the loaded orders are limited to only those orders identified in this table + ^ out 4 ^, ya. When processing orders by part or group of orders, the memory requirements of the ABP system 100 will decrease. Early middle In step 226 of Figure 2B, the order will be buried and eliminated in order of priority. When multiple orders are available, the order will be one after another. i worry. Priority orders usually have priority access to materials and capacity. -34- 200305088

(30) Because it is better for some orders to be processed before the others, it is better that the system will use the mechanism of ordering in priority. The mechanism used to prioritize orders is called sorting.

The ordering mechanism allows modelling of groups of orders and standard ordering in such a way that high priority orders are prioritized. If the two orders have the same priority, they will be processed sequentially by the database. Referring to Fig. 3B ', it is a flow 3 2 0 for prioritizing orders. At step 3 2 2 ’the orders are organized into order groups. At step 324, each group is defined by a SAD group. At step 3 26, each SAD group is sorted by, for example, a serial number. The serial number is used to model the relative priority of these order SAD groups. Lower numbers are associated with higher priorities. Within each order group, orders can be sorted (up or down) based on one or more attributes. At step 328, orders within each group are sorted by user-defined criteria. The criteria will be different for each order. For example, orders in one group can be sorted by demand date, while orders in another group can be sorted by a predetermined priority number

To illustrate some of the concepts already described, the following examples are provided. Suppose the automaker produces Model X cars and accepts orders for fleet, retail, and cargo sales. Manufacturers have three distinct order groups: fleet orders, retail orders, and inventory orders. Therefore, this = the relative preference of the k-group

Can be modeled. It is further assumed that the fleet order is important to take early, followed by the retail order ’and finally the inventory order. For each group, the priority criteria for sorting various orders in the group can also be defined. For example, orders in a retail group can be sorted by requiring w * not date (top ^ -35- 200305088

, And orders in the fleet group can be sorted (decreased) by revenue (user-defined attributes). The acquisition of order groups and ordering within groups can be achieved using the extended interface. The ABP system 100 can support the basic implementation of this interface operating below. SAD groups can be used to define order groups. The serial number can be used to model the relative priority groups of these order groups. Lower numbers are associated with higher priorities. Within each order group, orders are sorted (rising or falling) by a single attribute. For example, the sequence order group description symbol (SAD group) Sorting attributes Sort orders 1 Order type = Fleet revenue decline 2 Order type = Retailer decline 3 Order type = Inventory demand date e Rise The above table shows that fleet orders are more than retail orders Important, it is more important in order than inventory orders. Within the fleet order group, higher revenue orders are more important than lower revenue orders. Within each group, orders can be sorted on a different basis. For example, for a group of retail orders, an order from a vendor with a higher number of categories is more important than an order from a vendor with a lower number of categories. Therefore, manufacturers can define three levels of operators: the number of categories "3" is the highest level, "2" is the intermediate level, and "1" is the lowest level. Therefore, the orders of those operators that belong to the highest level will be given priority. In another example, suppose the manufacturer is concerned about shipping on time. In such a situation, orders within the SAD group can be sorted by demand date. In that case, the demand date attribute can be defined in the order and used to set the relative priority of each order in the SAD group. -36- (32) (32) 200305088 In addition to the sorting mechanism, the ABP system 100 will use two other mechanisms to help ensure that the most important orders are located next to each other. # 里里丁丁 早 扪 疋 成 疋 is satisfactory. These two mechanisms are capacity allocation and material allocation. The capacity allocation mechanism helps to reconcile the strong behavior of the system in the event that you do not want the order to be processed first (although the order is ordered). Based on this mechanism, a system limit model is generated that can be used to configure capacity based on meaningful attributes. For example, the capacity of a particular resource can be designed for a certain customer. The third mechanism used to confirm the highest priority order as a priority for satisfactory processing is called material allocation. This system allows tagging inventory lists and including income from usage attributes in planning tables to force allocation of materials to desired bills. For example, suppose that the inventory of 100 units used for the project has been assigned the attribute "customer = Jay-Mart". Basically, this property will give ιι single flags, and will basically be the opposite of the 100 units used for Jay Mart. This confirms that these 100 units can only be obtained by independent / dependent requirements of Jay_Mart. In a preferred embodiment of the present invention, the AB p system J 〇 〇 uses a single window, which can display a list of orders not included in the plan table. The list of TI orders that are not included in the schedule determines that the same order will not be included in the schedule twice because it will match multiple criteria of the SAD group. For example, suppose that the SA D group with priority 1 (e.g., '咼 priority) are all red cars, and the SAD group with priority 2 are all cars with ABS brakes. Red cars with AB S brakes will be planned in the first group. Although it will also be encountered in the second group, it will be slightly suitable because it is not in the order that is not listed in the schedule. In order to effectively manage memory and reduce database calls as much as possible -37- (33) (33) 200305088 'to improve performance, when entities are loaded into and unloaded from memory' according to the present invention The ABP system 100 of a preferred embodiment will follow certain rules. The order window will provide a way to view and process the order. The size of the single window depends on the hardware configuration and the size of the model, and is set by the user. Only orders that are not on the schedule will be processed ’These will remain on the temporary list in the schedules that are not on the schedule. When information is loaded into memory, the following rules will be used ... Orders in the order window to request an order for a specific SKU, the SKU will be loaded into memory; as defined by a unique item (not a SKU) Order, this item and all SKUs related to this item will be loaded; the BOM relationship for the SAD group 'it applies to the loaded SKU and item; the replacement sku information for the SAD group, it applies to the load Incoming SKUs and projects; only SKUs subject to hard restrictions (from a material perspective) will be loaded; and information on the availability of materials for the loaded and project-related inventory. For unloading 1, the SKU, item, and BOM of memory will be loaded at the beginning of the order window. After processing the order window, it will be unloaded from the memory, with the following exceptions ... Once it has been loaded, each SKU There will be a flag to determine whether it will be unloaded from memory. SKUs with this flag group will not be unloaded; parameters can be set on the algorithm to provide window memory. This parameter will be given to some order windows, which will remember the use of SKUs, that is, if in the last window, it has been modified or considered 'it will not be uninstalled; B0M configuration will not be uninstalled unless The unloading of the SKUs as intended; and the SKUs unloaded from memory will have an available status that will be updated in continuous storage. 200305088 (34) To illustrate these concepts, the following examples are provided. Assume that the ordering list of the orders (the output of the order sorting program) is as follows: Group Order Identity Fleet 01 Fleet 03 Retail 02 Retail 06 Stock 05 Stock 04 In the table above, there are six orders, 01 is the highest priority order, and 04 is Lowest priority order. Assume that the user has configured window sizes for three orders. When the first item requests the order window loader program, the routine loads the orders with the identity 0 1, 03, and 02 into memory. When the order window loader is requested again, the routine will load orders with the following statuses: 06, 05, and 04 into memory. The order window loader is usually requested only after all orders in the current order window have been processed. The way an order is processed will depend on whether the order is frozen. If the order belongs to the SAD group in the frozen group table, the order is frozen. This table contains a collection of SAD group names. Orders described by one of the SAD groups are preferably included in the schedule based on their demand dates. It is important to know that the frozen order is different from the initial allocation. The initial allocation is a basic order, which will be "frozen" after the previous execution of the planning process 200. After making the necessary adjustments to the ABP output, the system user freezes orders that the user does not want to move during subsequent ABP executions. The initial allocation will have an allocation date, location, and resources. -39- (35) (35) 200305088 However, a "frozen order" is usually used to force a "some" order of a specific date and / or location. For example, a car manufacturer may have business rules that say "Fleet orders must get their demand dates." In order to model this business rule, it is better to generate a frozen SAD group "Order Penalty-Fleet". / Dong Jie Ding Dan will be listed in the schedule based on its demand barrel range. The demand bucket interval is a bucket interval that contains the demand date (in this example, the demand date for rolling SAD groups). If no location is specified, a feasible location is used. Referring to FIG. 3C, it is a block diagram 3 50 showing the relationship among SAD group 3 52, orders 3 54 to 358, and freeze group table 3 6 0. Each of the orders 3 5 4 to 3 5 8 has the property of an order type, "fleet". Based on this attribute, orders 3 54 to 3 5 8 are related to SAD group 3 52. The frozen group table 360 is related to the three SAD groups 3 52, 3 62, and 3 64. Because SAD group 352 is related to the frozen group table 3 60, each order related to SAD group 3 5 2 will be frozen, so orders 3 5 4 to 3 5 8 will be assigned to a specified time (for example , 5 weeks). Order Planning In steps 2 2 8 of Figure 2B, the use of resources to fulfill one or more orders is planned. AB P system 100 implements strong algorithms that are processed in order of priority. This algorithm processes one order at a time and evaluates the potential allocation (barrels, resources, and locations) for the order. This algorithm uses the user-defined multi-level objective function to evaluate allocations and determine that allocations related to material and capacity constraints are feasible, and chooses the most appropriate allocation for the order. Figure 4 shows the process of resource planning 4 0 0 to achieve the needs as defined by the order -40-200305088

(36), and step 22 8 of FIG. 2B is usually displayed. In particular, this is an attribute-based planner. Process 4 will process orders processed in priority order, and will use the best use of resources to generate a plan to achieve the order. A brief description of each step shown in Figure 4 is provided below, followed by a more detailed description of the steps. In step 402, an order is selected for processing. Program steps 4 0 2 may also include steps for defining parameters of a planned order. In step 404, the configuration is selected and the acceptable locations are prioritized. Each order will have an item and a preferred position. If both of them are ’then the finished SKU has been identified. If there is only an item, the system will relatively easily generate a prioritized processing order that can be used to identify the SKU (item with feasible location) related to the finished product of the selected order, and a finished product SKU (herein "FG SKU "). Step 404 results in a decision on the acceptable location for each FG SKU in the set, as SKUs typically define locations. One or more configurations are associated with each SKU. Therefore at step 404 (permissible configuration previously loaded-see flow 2 2 0, Figure 2 B, step 2 2 4). In step 406, the SKUs from the collection of FG SKUs are selected for planning. The FG SKU selected will usually be the SKU with the highest priority in the unplanned collection. At step 408, the fg SKU is initialized so that the FG SKU will have all attributes corresponding to the order and / or item. Based on the selected SKU ', it is determined which resource is an acceptable resource for planning SKu, and the resources are ranked according to the priority of step 4 10. It should be noted that when part of the order accompanying the relevant date is loaded into the window of step 224 of FIG. 2B, a list of acceptable resources may have been loaded and / or determined. At step 4 1 1 • 41-(37) (37) 200305088 msmaam, Qiqishan-on the list will be selected, and the resource with south priority will be selected. At the step, the material feasibility judgment will be made, and 2 ^ Du 'Step 412' A. ^. It is determined whether the location / resource has sufficient materials to satisfy if the order has sufficient ^ ^ .. No, is the material available? In step 4 1 4, the combination of 嵙, 欠, and κ 疋 疋 + 1 4 1 6 ^ 做出 to make a feasibility assessment of the limitation of Beiyuan. At step 416, a material compatibility check is made in the order. In step 418,

The pick B 摘 muKr ^ ^ r estimated for FGSKU, and the best opportunity will be selected as the "most powerful ^ —, $, best one" for the position. At step 418, after assessing the use of the surname position <barrel interval / resource opportunity, whether there are resources to check. If there is a resource 420 'for the same bit, it is judged to be a resource, and then it returns to step 411 and sets other acceptable sources. If there is no more access at the same position; Choose: The other-used for evaluation will choose and remember the best bucket interval / resource machine * 'Original', then step 422 determines if there is still an acceptable position. If so ... At step 424, another-position is determined and selected. #If there are no more acceptable bits, then go back to step 406 and choose the best location / resource / barrel interval. In-place 'is allocated in step 426 to the best location / resource / barrel section. At step 428, there will be no more orders that need planning. If it has +43, it will be judged as

The process 400 will restart from step 402, otherwise, the program will end. The following simplified examples accompanying Figures 5A through 5 (b) illustrate how the process 400 used to plan the use of resources can meet the demand. At this point, you have been selected as a white 0 1 son, and have been selected to order 0 ^ 5 02 for planning, as shown in Figure 5A. The order 1 1 5 2 is selected from a list (not shown) processed in order of priority. Based on the relevant Λ, &amp; can be 0 502 information, a list of F G S KU can be determined (hence the location of &amp; and Loc 2 and Loc 2 and Loc 3). In this example, the acceptable location *, decision is Loci 504, • 42- 200305088 (38)

Loc2506 and Loc3508. Acceptable positions can also be sorted by preference. Therefore, in this example, 'Loci 504 is above Loc2 506' because Loci 504 is more desirable than Loc2 506, and Loc2 506 is above Loc3 508, because Loc2 506 is more desirable than Loc3 508. This first step generally corresponds to step 404 of FIG. Next, the order position pair (0 1, L 0 c 1) is checked again and a decision is made as to the list of acceptable resources for manufacturing the order 0 1 located at L 0 c 1. Once the list of acceptable resources is determined, the list is sorted by preference 'as shown in Figure 5B. In this figure, the resource R S 11 5 1 0 is above R S 12 5 1 2 'because 113115 10 is more desirable than RS12 5 12. This step generally corresponds to step 410 of FIG. In the next step (which usually corresponds to 412) 'will attempt to include the order in the first resource, RS η 5 10, which is a potential manufacturing order at location Loci 5 04, in the plan sheet. The combination (〇1-Locl-RSli) will then be included in the plan table, evaluated and scored (this step usually corresponds to 414), as shown in Figure 5C. Next, the last two steps (ie, steps 412 and 4 14 of FIG. 4) are reused for the resource RS i 2 5 1 4 as shown in FIG. 5D. In this example, the level of opportunity for inclusion in the schedule for (Oi-Locl-RS ^) will be found to be better than calculated for (Oi-Locl-RSn), so (〇1-L〇cl- RS12) is the best listing opportunity found to date and will be remembered as the best for Loci 504. Once all acceptable resources in Loci 5 04 have been evaluated, 'the next position in the list of acceptable positions (position L0c2516)' is checked as shown in Figure 5E. There is only one acceptable resource for 1 Ding 〇 502 located at -43-200305088 (39) [〇. 2 215 11321518. An attempt will be made to include resource 1 ^ 21516 in the schedule, as shown in Figure 5F, and / or evaluate the results. If successful, the schedule opportunity for (Oi-Loc]-! ^^) will be compared with the schedule opportunity for (O!-L 〇c 1-RS 12) to determine Best order / location / resource combination. A comparison will be made to compare the calculated fitness with the "best by far" and if the fitness exceeds the best fitness found so far, the current inclusion will be included in the plan The table opportunity is stored as "the best opportunity to be included in the plan table found so far." In this example, the schedule opportunity for (〇1-! ^ 〇 (: 2-11312) was found to be "best by far." Because all resources are being used for LO 2 of the 0! List of acceptable resources, so the next position in the list of 0i positions will be rechecked. However, as shown in FIG. 5G, there is no acceptable resource for 10c3 5 18 . Then the listing schedule information (Oi-LochRS! 2) found so far for the best day listing opportunity, (Oi-LochRS! 2), will remember to update the availability on all limits, and pick up the next order And handle it in a similar way as shown in Figure 5H. A more detailed description of the specific steps and concepts introduced in the process 400 of Figure 4 will be provided below. In step 402, the next or A priority full order (that is, from a sorted order list) for processing. During this step, restrictions and / or rules are defined to provide parameters for planning the order. Limits and / or rules will usually be based on Information about the selected order. Note that this step and All the next steps will be repeated in the loop until all orders in the current priority group have been processed -44- 200305088 (40). Also note that the feasibility of all configurations and all resources No check is required. The program will stop as soon as good and sufficient results have been obtained. In order to show how the parameters defined in processing step 402 affect the way the order is included in the planning table, the following simplified order processing example will be provided. Assume a car Manufacturers accept orders with three attributes: item name, location, and demand date. The project name can be the style name of a car built by the manufacturer. The location is the factory location, or any delivery location, such as the customer's location. The demand date is Represents the date of completion of the car. Reference is now made to Figure 51, which is a block diagram 540 showing various combinations of attribute values that may be used for orders of the car style "sedan". Quadrant 1 542 represents the date and location of the demand that a specified order must complete Orders in quadrant 1 542 will specify SKU = "sedan" (ie, item name), "Atlant Large ”(i.e., location), and“ 5 weeks ”(i.e., demand date). In this example, the ABP system 100 can resolve a suitable bucket interval / resource opportunity for an order, subject to some sort of Domination by conditions. For example, preferably, the bucket interval will fall within the acceptable schedule interval for orders. For example, the acceptable schedule interval is between "demand date- "Earliest allowed" and "demand date + latest allowed". Preferably, the resource is located at the position specified on the order (meaning the SKU specified on the order). Preferably, the related Allocation of materials and other hard constraints is feasible. Preferably, the bucket interval / resource opportunity should be the best of all potential opportunities, or the level corresponding to each goal in the objective function One is below the specified threshold. A multi-stage objective function is used to evaluate the optimal bucket interval / resource opportunity. ABP system 100 can allow some laws, -45- 200305088

Each has a level. The user can choose from a regular, extensible list and assign SAD groups (to identify which order is available) and regular levels. The user can also specify tolerance values to identify how close the two rules need to be before they are considered equal. For example, if the difference is 0 · 1 ', a rule having the values 2 · 0 1 and 2 · G 2 is regarded as having the same value. When-two opportunities are compared with a known order, the level in the rule is checked from the highest priority to the lowest priority. The first tier that differs within the tolerance value tells that this opportunity is better. Quadrant 2 544 indicates the date of the specified demand, but the order of the unspecified position is _ early. For example, 'order soap will specify items such as cars and demand dates such as 5 weeks. In this example, the ABP system 100 can resolve the appropriate bucket interval / resource opportunity for the order, f is subject to certain conditions. Preferably, the bucket interval will fall within the acceptable schedule interval for orders. Resources can be located anywhere. The assignments related to materials and all available constraints must be shouldering. Preferably, in the bucket interval, the resource opportunity should be the best among all potential opportunities, or the level corresponding to each target in the objective function-the system is below the specified threshold. · Quadrant 3 546 represents orders without a specified date or location. For example, orders, and staff, cars. And such as the demand date of 5 weeks. In 'this example', the ABP system 100 can resolve a suitable bucket of time for orders: time / resource opportunities, subject to certain conditions. For example, relatively speaking, the time bucket interval can be anywhere in the planning range. Resources 玎 are located anywhere. Preferably, knife materials related to the material and all available puddings will be acceptable. Preferably, the bucket interval / resource opportunity should be -46- (42) (42) 200305088, which is the best of all potential opportunities, or a low corresponding to the level of each goal in the objective function. At the specified threshold. The quadrants 4 5 4 8 represent orders without a specified date but at a specified location. For example, an order can specify an item, a car, and a location, Atlanta. In this example, the ABP system 100 can resolve a suitable bucket interval / resource opportunity for an order based on certain conditions. For example, a bucket interval can be anywhere in the planning range. Preferably, the resource can be located at the position specified on the order. Preferably, assignments related to materials and all available restrictions are feasible. Preferably, the bucket interval / resource opportunity is the best of all potential opportunities, or one of the levels corresponding to each objective in the objective function is below a specified threshold. At step 404 (of FIG. 4), the selected configuration for the order selected at the acceptable location in step 492 is determined and processed in priority order based on the order attributes. The set of finished SKUs for the order will be determined. The FG SKU will be loaded into the order window in step 224 of FIG. 2B. Sets can be determined based on some criteria. For example, if the SKU has been specified on the order, then this SKU is the only finished SKL in the set. For illustration, assuming that the order is for an Atlanta car, only this FG SKU can be included in the set. On the other hand, if an order specifies an item, all SKUs related to this item are feasible finished SKUs regardless of their location. For example, if the order has only designated cars, any SKU with a car as an item regardless of location (that is, Atlanta or any other city) is a viable finished SKU (assuming these SKUs exist). If there are multiple FGSKUs in the collection, these FGSKUs can be sorted using the extended interface. Prior to planning -47- 200305088 (43) a SKU with a lower preference is sorted to direct the ABp system 100 to use the most preferred SKU (hence the most preferred location) to plan the order. The A B P system 100 will support the basic implementation of the interface, which will sort the SKU collection according to the transportation cost from the SKU location to the destination location on the order. These costs can be modeled using the location-by-location transport matrix. For example, a table would be generated that allows the user to specify a cost of $ 1.0 per unit of Atlanta L Denver, and a cost of $ 0.75 per unit of Atlanta &gt; Denver. If no entrance exists' then the finished product will not move between known locations. Basically, deciding on the set of FG SKUs will lead to deciding on a list of acceptable locations. S KU is location dependent. Therefore, once all acceptable SKUs are identified, acceptable locations will also be identified. The collection of FG SKUs can be sorted by preference. That is, certain FG SKUs have higher priority than other FG SKUs based on, for example, location preferences. This location preference can be derived from customer preferences or manufacturer preferences or some second party preferences. In step 406 (of FIG. 4), an acceptable location is selected for planning with the highest priority. In general, this will be a location-based preference. Therefore, the FG SKU with the most preferred location will be preferred for planning. In step 406 (of FIG. 4), the unique FG SKU of the single finished SKU order combination is initialized, whereby the attributes are copied to the order and not to the SKU. The attributes related to various entities in the ABP system 100 (for example, orders, SKUs, items, and the like) are modeled at three levels (item, SKU, and order level). Project-specific (and associated with planning) production, design, or sales-related attributes are modeled at the project level. Israel -48-200305088

The attributes of the target mode change are usually applied to all SKUs of a known project (regardless of location). Preferably, the items specific to a known location and the attributes of all orders planned for this location are modeled at the SKU level. Order-specific attributes that tend to change orders based on customer preferences are modeled at the order level. If the order has a value for an attribute, it is used. If the order does not have a value for the attribute, but its associated SKU is, then the SKU value is used. If neither the order nor the SKU has a value for the attribute, and the item does, the item value is used. If none of the order, SKU, and item have values for the attribute, no value will be used for this order. During the initialization step, a decision is made on all available SD groups. All SAD groups describing FG SKU objects are determined. This can be achieved by matching the attributes (name-value pairs of the Bollinger combination) on the S A D group to the attributes (name-value pairs) on the ρ g $ K U object. In achieving this, it will be determined which SAD groups are location (and resource) dependent. This step is performed so that multiple checks of SAD group availability will not be done twice for the same order, or for the same order / resource combination (for sad groupings that are location-dependent). The initialization step will also include the step of calculating the effective demand date for the order. When considering the transit time for delivering items to the requested location, the effective demand date is the real date when the finished product is required. If the order is made using a known finished SKU, the effective order will be calculated and the + and% I dates will be calculated. This calculation can be achieved, for example, by some of the steps% below. For example, if there is a date of arrival on the order, "effective demand, time 1 = arrival date-from the customer location in the morning to the location of the known finished SKU, I &lt; transport time" -49 · 200305088 (45) . If there is no arrival date on the order and there is a demand date on the order, [effective demand date = demand date on the order]. If neither the date nor the demand date arrives on the order, [valid demand date = invalid]. The initialization step may include the step of calculating the correct inclusion in the schedule interval for the FG SKU object. If there is a valid demand date, it is better to use the earliest and latest parameters to calculate the correct inclusion in the schedule table. If there is no effective demand date, it is correctly included in the planning interval as the planning interval. The morning / night table will be generated, and the SAD group defines how late or early the order can be listed in the plan table relative to the effective demand date. If there is no demand date, this table will be useless. The priority number is assigned to the SAD group of this table. If multiple SAD groups in this table are for FG SKU objects, the serial number can be used to determine the SAD group with the highest priority (and the earliest and latest parameters). In step 410, the ABP system 100 will decide which resources to use for the FG SKU are acceptable or allowable, and will generate a list of potential resources. These permissible resources are then sorted so that those with higher priority or preference than those with lower priority will be checked before the lower priority resources are checked to determine their inclusion. Schedule opportunities. The decision on allowable resources usually depends on many factors. For example, only those resources that are available will generally be considered viable resources. Other factors prevent specific resources from being considered. For example, conceptually, there are at least two factors that limit this set of resources, resource locations, and dedicated resource groups. The resource location factor is when the resource is not at the location defined by the finished SKU object. Such resources will not be considered as potential resources. Dedicated funds -50- (46) (46) 200305088 The source group factor is when the resource is related to a dedicated resource group. Deletion of a dedicated resource group can be defined by generating a dedicated resource SAD group. For example, the Fake Dedicated Resource Group includes assembly lines in Atlanta and Assembly Green1 in Denver. The removal of this dedicated resource group can be done by the SAD group "item

Project-Car or Project = Pickup ". The FG SKU object considered could be "Atlanta's SUV 'Color' Red, Power Window = Yes, Inner Shaw = Leather". In this example, the line in Atlanta is part of a dedicated resource group that only manufactures cars and trucks. Although the position of the sKU object = Atlanta, assembly line 1 is not an allowable resource, because the item corresponding to our FG SKU object is SlJv. When the allowable resources are identified, they will be sorted so that the most preferred resource will be in Priority inspections for non-favorite resources are given priority inspection opportunities. In step 411, if the resources are sorted ', the resource with the highest priority is selected. "If the set of allowable resources is not sorted by priority, the system will choose randomly, or by any other method defined by the system user. In step 412, the material feasibility of the FGSKU object is evaluated. This step will determine whether the previously selected resources will have sufficient "material" supply to provide the required amount of FG SKu objects within an acceptable period of time. “Materials” can be component parts or materials, or the finished product itself with respect to the request. Based on the previously determined Fg SKU objects, the ABP system searches for each level in the Bill of Materials (BOM) (multiple configurations in the preferred order. The search allows replacements to find out about the finished sku -51- (47) (47) 200305088 In order to understand the material feasibility of the ABP system and system 100, the concept of "barrel section" will be described as follows. Preferably, the ABP system 100 is Bucket interval planning system. This means that the system attempts to plan an order into a bucket interval. It will generate a bucket interval for each restriction. The bucket interval for restrictions can be a combination of calendar, style range, and restricted characteristics Define it. The calendar will be generated and used to define some barrel intervals and the duration of each barrel interval available. The style start is used to determine the true start and end dates of each barrel interval. Planning scope + Limit the starting small change (deita) to determine where the beginning of the first barrel interval will be located. This is because ABp system 100 needs to rotate from cycle to cycle. For example, suppose the user is on Monday (the first) do The plan for every Monday (8th) ^ The horizontal start will be Monday (8th), and the limit will usually have a zero offset, so that the first bucket interval for all limits will be Monday (8th) ). When the next week arrives, the user will plan for Monday (15th) on Monday (8th), and the user's planning range will be set to Monday (15th). Because the offset is zero , So the beginning of the bucket interval will be Monday (15th). It should be noted that changing the starting range of the planning range will cause the entire system to adjust. Obviously, if there is a week start after the horizontal start Restrictions, when planning Monday (8th), the first bucket interval will be Monday (15th). When the next week arrives and planning the beginning of the next Monday (5th), the first bucket interval It will be the next 7 days or Monday (22nd). Each bucket section can include one or more elements, which include time (width or duration of the bucket section), maximum capacity (should be placed in the bucket section) Maximum number of orders expected in the interval), maximum capacity to relax ( Placed in the barrel range in the maximum number of orders does -52-200305088

Project), and the minimum capacity (the minimum number of orders that should be placed in the barrel section). The capacity of each barrel section is controlled by limits. The restriction rule basically limits the capacity of each bucket interval or a group of bucket intervals. According to a specific embodiment of the present invention, at least three types of restriction rules are feasible, such as value, percentage, and smoothing part. The value limit rule will provide a mechanism to define the increase and change in capacity from one bucket interval to the next. Percent limits are similar to value rules, except that values defined on limits are interpreted as percentages and not as a set amount. The increase from one barrel interval to the next changes to a percentage of limited capacity. The smooth partial limit rule interprets the value defined on the limit as a percentage of the total potential load on the limit. This load percentage is distributed in the planned bucket interval defined by the bucket interval range line, and is proportionally distributed in the bucket interval based on the total available time in the bucket interval. The number of orders with a usage limit is distinguished by the number of bucket intervals to obtain the maximum capacity of each bucket interval. The remainder can be unrolled in bucket-like intervals according to some satisfactorily ending rules (randomly, from the first bucket-like interval forward or backward from the last bucket-like interval, or by adding all bucket-like intervals). It should be noted that the smoothing rule processes overlapping bucket intervals by calculating the load per unit of available time and multiplying this ratio by the amount of time available for each bucket interval. Material Feasibility Referring to FIG. 6, it is a process 600 for judging material feasibility. The output of Procedure 6 0 0 is information about the feasibility of the required material and can be very useful for the entire planning process. Such information may include, for example, materials -53- (49) (49) 200305088

Use dates, material availability, feasibility flags, and the like. The output can be in the form of a graph, text or quantitative report. The feasibility flag indicates whether the process 600 was successful in finding the material supply needed to select the resource. If the feasibility flag indicates that Cheng has succeeded, the available M will usually be equal to the demand, and this amount will be available on the last date that is acceptable (date of demand + latest) or on the last date. If one or more or conditions are not met at the same time, the feasibility flag will indicate that the procedure was unsuccessful. More preferably, it will try to find the earliest available supply before the earliest date when the demand is met or before the earliest date when the demand is met. At step 602, the order data is retrieved. In step 604, the inventory of the selected resource is checked to determine the material inventory level. After making sufficient judgments on the inventory, the p system i 〇 〇 will produce an output about the availability date of the inventory and the amount of inventory that will be available. The availability date of the inventory will be when the inventory is available for use. Available stock: For example, the amount of inventory available on the available date and the amount of income included in the schedule. In step 606, it is determined whether the available amount will meet the demand amount. In order to check the inventory and make a decision as to whether the inventory will meet the demand date and quantity: related to, for example, order attributes, effective demand dates, demand quantities, earliest, latest, and the like dates. If the inventory is judged to be sufficient, an output is generated at step 608. If, on the other hand, there is not enough quantity in the inventory to meet the demand, then at step 6 10, the inventory must be replenished by manufacturing and / or purchasing new inventory. Replenishment of inventories can be achieved by manufacturing and / or replacing inventory. The system's manufacturing, purchasing, and / or dedicated supplementary functions are discussed in more detail below. In step 12, it is judged whether supplementary step 6 1 0 is sufficient to meet the demand. If so, -54- 200305088 (50) will produce output at step 608. If supplementary step 6 1 0 is insufficient, then step 614 will attempt to fill the gap of another option. The replacement step 614 is discussed in more detail below. In step 6 16, it will be determined whether replacing step 6 1 4 can successfully make up for the shortage in step 6 1 0. If supplement step 6 1 4 is successful, an output is produced. If the supplemental step 614 is unsuccessful ', an output is generated in step 618. Note that the output produced by steps 608 and 618 will be different. The output produced at step 608 will preferably include the available amount (which should be the same as the demand amount), the available date, and a representation, such as before or before the last acceptable date (demand date + latest). Accept the feasibility flag indicating "yes" if the date can meet the demand. The output produced at step 6 1 8 will preferably include the available amount (which will be lower than the demand amount), the available date, and a representation, such as before the last acceptable date (demand date + latest) or A table that fails to meet demand on the last acceptable date is a "no" feasibility flag. The checking inventory step 604 usually requires an exact match between the attributes of the FG SKU object and the inventory attributes. However, in another specific embodiment, exact matching of these attributes is not required for certain attributes called preservation attributes. For example, suppose if the attributes of the order are as follows, item = sedan, color $ red, and power window = yes. Generally, for the inventory used to match this SKu, this &gt; must be exactly matched in each case. However, it is assumed that the additional attribute of "for customers" is the preservation attribute. The attributes used for the order can now be Project = Car, Color = Red, Power Window = Yes, and Customer Two Cambodian Operator. If the inventory has the same first attribute (item = car, color = red, power window = yes), but there is no customer attribute, then the inventory • 55 · 200305088

The attributes match the attributes of the F G S K U object. However, on the other hand, if the inventory has customer attributes like a Northwest operator, it will not match. The net logic of the inventory check step (606 in Figure 6) can be best understood with reference to Figures 7A to 70, which is a timeline that describes an example of inventory levels and demand over time. Figure 7A shows that during the early period of timeline 700, the inventory level 702 will rise. Demand dates are shown as vertical lines 704. The earliest acceptable date is indicated by the vertical line 906, which is equal to the required date minus the earliest. The latest acceptable date is indicated by the vertical line 708, which is equal to the demand date plus the latest. Therefore, the time interval between the vertical lines 7 06 and 70 8 is an acceptable time period. Demand is indicated by the horizontal line 7 1 0. Because the inventory level 702 rises early in the timeline 700 in this timeline 700, the inventory availability date D1 710 is before the earliest acceptable date 706. Inventory availability date 712 is the date when the inventory is at its maximum, or the first date when the inventory level exceeds or equals the demand. Therefore, in this timeline 700, the required inventory from the earliest acceptable date of 70.6 is available. In the time line 7 2 0 of FIG. 7B, the rise of the inventory level 722 will be slower than the inventory level 702 of FIG. 7A. Therefore, the inventory availability date is 724 after the earliest acceptable date of 72 6 but before the demand date of 7 2 8. Referring to FIG. 7C, it is another example timeline 740. In this timeline 74, the inventory level 742 rises very late in the timeline (after the demand date 744), and never reaches Demand 746. The available inventory date 74 8 in this example will be the earliest date that the inventory is at its maximum (as represented by 750) before the latest acceptable date 752. In order to make up the difference between the maximum inventory level 750 and the demand 746, the inventory will be replenished and -56- (52) (52) 200305088

99BHB / or some or all of them will be suppressed by another (as shown in steps 610 to 614 of Fig. 6). Figure 7D shows the time period 764, when the inventory level 7 62 is maintained at zero during the entire period of time, and the straight line] will rise to the demand 766 after the last acceptable date of 770, As indicated by available field J with inventory date D4 772. Supplement In order to better understand the multi-million methods that can be used to supplement, the following paragraphs will explain many concepts and projects ’which are packed with materials, materials, materials, wares (BOM here) and configuration. In order to fully understand the concept of innovation of the present invention, it would be helpful to briefly discuss the entire high-level relationship between order, BOM, SAD group, configuration, and the like. The ABP system 100-year-old plan is based on the use of resources for receiving orders. An order can represent a customer's need for electricity, travel, forecasted customer demand, and / or secure inventory (to provide protection against unmet demand, ^ y,] precautions). Each order will have attributes. For the same SKU, there may be more than ^ ^ bites. For example, suppose there is a SKU with the attribute sedan @ 亚特. -录 —-1 1 — A kind of 玎 can be related to this SKU, one is for cars with select characteristics (power windows) request @ 亚 and the second order is for cars with unrequested power windows @ 亚 SAD 群Departments are separate from orders and can be used to group orders. One way to look at SAD groups is to treat them as filters. The SAD group is used in many places. For example, it is used to define the processing order, and to determine which orders can be completed with which resources. Configuration can be viewed as a way or an indication of building a project. It usually lists the materials needed to fully build the item it was searching for. For example, in the example above, the configuration used for the above car @ &amp;# I large will list the required materials (ie, components) to build a car. Each project may have more than one configuration, as some materials will be replaced -57- 200305088

(53) expected. The BOM will define or identify all configurations for the searched items. : BOM also defines parent-child relationships. The SAD group is used by the B OM in two ways. Each parent-child relationship has a parent and child. If one line replaces a parent with a SAD group, the other will have additional control levels. For example, one might indicate a relationship that applies to all orders for a project car, but only if it has the property of a power window. If desired, one might indicate a relationship that applies to all orders that have power window attributes, regardless of the item. Another way to configure the use of SAD groups is when deciding on allowable replacements. Each substitute has a parent and child. Users can replace the SAD group used for any project, and have a better replacement control level. Orders that are not related to the SAD group will have all the necessary attributes to identify the materials (and configuration) that will be used for the searched item. The BOM used by the ABP system 100 according to a specific embodiment of the present invention is based on attributes. Unlike the BOM in traditional planning systems, the BOM used in accordance with the present invention allows the modeling of material requirements based on selection and rules. The examples provided below will introduce the concept of B OM. In today's automotive industry, for example, it is very common to find the following rule: All cars must have (regardless of other options present) the basic sub-components A, B, and C of the basic group. Car style with sunroof (but no power window) Each car requires a sunroof assembly and 10W motor; car style with power window (but no sunroof) requires a power window assembly and 10W motor; The car style requires a power window assembly, a sunroof assembly, and a 15 W motor. Because of the extra load, higher wattage motors are needed. Note that in this example

-58- (54) (54) 200305088

The presence or absence of choices drives the demand for materials. Furthermore, material requirements will depend on the combination of choices that exist. To better model these requirements. The SAD group will be included in the Bom. The SAD group can be a 林 κυ of the Bollinger combination that accompanies the attribute. In determining the material configuration for each order used for planning, bmm plays an important role &amp;. In order to use the finished BOM, the car is delivered well, and a BOM table will be generated. The ABP system 100 will try to find a feasible configuration for each order by looking at the inventory of the finished product of the order and by expanding the BOM as necessary and checking each definition. The necessary minor items for the material determined as follows (for each Sad group describing the order, and for the items requested for the order, at least one of the methods defined in the BOM table) are usually used to make the mark. The same is true for the secondary materials, for example, the project and the available SAD groups may decide to use the secondary materials, and at least one method for each of these must be used to make the secondary items. The SAD ping group referred to here is the sAD group about materials, not orders. "Offset" can be defined for any item in the BOM. This offset defines the amount of time required for this item after the manufacturing of the finished SKU begins. The ABP system 100 can determine that the lead time for the manufacture of the starting finished SKU will always be at least as long as the maximum offset of any item in the BOM for this finished SKU. A configuration is essentially a list of secondary items needed to make a parent item, which could be, for example, an order item, or an intermediate item used to make other items. As long as at least one configurational supplement is feasible, the parent item can be supplemented. When there are multiple configurations, strong feasibility and most suitable, AB P system 1 0 0 • 59- 200305088

(55) Two mechanisms for search and optimization will be provided. In strong feasibility, once the system finds a working configuration, it stops searching for acceptable configurations. The acceptable configuration can be defined as completing the SAD within the planning interval [if there is no earliest, (demand date-earliest) or the beginning of the planning range, if there is no latest, (demand date + latest) or end of the planning range] A configuration of group demand. In the best fit, the system searches all configurations for the SAD group and selects the best configuration for the targets listed in the plan. More specifically, the ABP system 100 will use the SAD group in the BOM to model attribute-based material requirements. 8A to 8C, which are actual displays of exemplary relationships between SAD groups and SKUs in a BOM. Figure 8A is a block diagram showing a "basic" bill of materials for a Denver wheeler. Therefore, in this example, the BOM includes a relationship (which can use SAD groups) that defines basic materials (for example, parent items) and related secondary item SKUs. In this example, SAD group 802 is defined by two SKU attributes, sedan and Denver. Every car manufactured in Denver requires certain materials, regardless of the choices or characteristics that exist. In this example, these required materials include minor items sku 804 to 808, such as component A in Denver 804, component B in Denver 806, and component C in Denver 808. The relationship shown between the SAD group 8 0 2 and its secondary items KU 804 to 80 8 can be regarded as a kind of β 0 M of the same degree as used for Denver's sedan. Figure 8B shows a block diagram of another BOM. The BOM described here shows the components required for "extra" (the same three types of components required for a BOM of the same degree shown in Figure 8A). If the sunroof is configured as a selection, but the motor The window is not. In Figure 8B, the SAD group 8 10 is controlled by Xu -60- 200305088.

(56) Multiple attributes to define, including "SKU = Sedan @ 丹佛", "Skylight = Yes" and "Power Window = No". The SAD group 8 1 0 is related to the sunroof components for Denver and the secondary items SKU 812 and 814 of Denver's 10W motor. Minor items SKU 812 and 814 are additional materials needed when sunroof selection is requested.

Referring to FIG. 8C, a block diagram of another type of bomb is shown. BOM is a component required to display "extra", if both sunroof and power window are selected as options. SAD group 82 is defined by a number of attributes, including "sku = sedan @ 丹佛", "Sky®", and "power window = yes". The choice of sunroof and power window options drives the need for additional materials. In this example, SAD group 820 is related to three minor items SKU 822 to 826, Denver's power window assembly, Denver's sunroof assembly, and Denver's 5 W motor. It should be noted that this BOM will require a more powerful motor than the BOM (only 10W motor required) shown in Figure 8B. This is because the second scheme (ie, Fig. 8c) has a request for the power window and sunroof options, while in the first scheme (第一, Fig. 8B), there is only one request for the power consumption option (roof).

A key element of planning is a concept called "configuration." The configuration is essentially a list of secondary item SKUs that must be used for the order to make the parent sku. The concept of configuration can be understood from the following examples. For each SKU, there is a corresponding BOM with a method list, and the Shanghai Stock Exchange AI ^ ^ shows the various ways it can be manufactured. The whole method is very needed, such as ^^ 徐 for baking cakes. Furthermore, when baking, if there is a shortage of ingredients, you can substitute one ingredient with another. The SAD group in the BOM record will be legal when A ^ .m indicates when a secondary item is available. For example, suppose a car needs 10w horses' ^ ^ ^. Transport, but a car with sunroof -61 · 200305088

(57) Requires a 20 W motor. The mother SKU sedan will have two types of BOM records, each with a designated sunroof or unspecified sunroof, and a SAD group of 20 W or 10 W motors. Configuration tells us which materials are needed for those quantities. Someone will take the method + supplement + substitute to get something that can be built. As part of the work, a mesh system for materials on hand and future supply will be achieved. For example, suppose a 10 W motor is needed and one is on hand. Orders for a single car can be made and used. The next order placed will also require a 10W motor. To supply the required 10W motor, the motor must be replenished (purchased), replaced, or not planned at all, because not all the materials we need are available. If it is manufactured, it is usually a subassembly, and this subassembly has a set of materials that require various quantities. Order for cars 1 may have materials for the sedan 1 0 W motor Order for cars 2 may have materials for the sedan bridge 1 0 W motor motor housing This order may have different groups of materials to support its manufacture. If at least one configuration can be supplemented within the planning interval, the order is a viable material. Different configurations can have different materials because they will have different materials and / or quantities among them. When there are multiple configurations ("strongly feasible" and "most suitable"), at least two mechanisms can be used for searching and -62- 200305088

(58) Optimization. In the strong feasibility, ABP system 100 will choose the feasible first configuration without going through all the other configurations. And search for the best configuration. Conversely, in the "best fit", the system searches through all configurations to find the corresponding order, and selects the best configuration related to the target included in the schedule. In the strong feasibility, once the feasible configuration has been determined ("feasibility" is defined as follows: the demand for the order can be reached on the demand date or before the demand date), the ABP system 100 will not search for another group state. For example, suppose two configurations (Configuration 1 and Configuration 2) are available for order j. If configuration 1 is prioritized and the available quantity (order) is found = the demand of configuration 1 using the demand date (if it exists), then the AB P system 1 0 0 usually does not look at the order again. . In other words, configuration 2 is not even considered. The program leaves the loop and processes the next order. In the best fit, once the system finds a feasible configuration, it does not stop searching. Instead, it searches all configurations for order j, and selects the best configuration for inclusion in the schedule target. So configuration 1 and configuration 2 will be processed at the same time. A better configuration will be selected. The relationship between configuration, order, and SKU is described in the following example accompanying Figure 9. In this example, the configuration used for the order (Configuration 1, Configuration 2, and similar) is essentially a set of secondary relationships. In this example, the order "900" has two configurations, configuration A 902 and configuration B 904. Each configuration is a set of minor items SKUs 906 to 920. For example, configuration A 902 is a set of secondary items SKUs 906 to 9 12 and configuration B 904 is a set of secondary items SKUs 914 to 920. If at least one configuration is possible by planning the endpoints of the interval, the order "900" is feasible. In other words, if at least one configuration (configuration j of order j) can be found, so that the available quantity (configuration j) = demand, -63- 200305088 (59) then the order "· 900 is feasible, The available quantity (configuration) · is the quantity that can be supplemented by using the configuration "configuration ij" at the latest date (= demand date + latest) or before the latest date. Configuration "j" should be read as the "jth" configuration of the order. The available quantities for the two configuration orders will be the same. As long as all minor items in the configuration (for example, component materials) are feasible, configuring "configuration j" is feasible. In other words, the configuration "configuration j" indicates that it is feasible, as long as all "k" (where k is an indicator for the secondary items in configuration j) are available, the available amount (secondary items SKUjk) = demand (secondary item SKUjk), Hkm, with "η" as the number of intermediate materials. The available quantity and date for each configuration can be calculated as follows. Available amount (configuration) · ΜΙΝ [Available amount (secondary item SKUjk) / Pull amount (secondary item SKUjk), where the minimum value is used for all secondary items in the configuration. Available Date (Configuration) ·) = ΜΑχ [Available Date (SKUjk for minor items) + Delivery time (to supplement minor items)-Offset (SKUjk for minor items)], where for all times in configuration ij Major items will take the maximum. Delivery time is the time when the supplementary item is needed. For example, suppose it takes five days to build the component material, and in this example the shipping time will be five days. Therefore, it is important to note that in some cases there will be no shipping time (Shipping Time = 0). In short, for a viable configuration, in terms of the required secondary project SKUs, each secondary project SKU (that is, component material) must be feasible by the time a secondary project is needed, and There is sufficient quantity in inventory at this date, or if there is not enough quantity, the supply will be fully replenished to meet demand by manufacturing, buying, and / or replacing. Supplement by manufacturing -64- (60) (60) 200305088 Supplemented by the manufactured material will be explained with reference to the flow 1000 in FIGS. 10A and 10B. Process 1000 is a process that is supplemented by manufactured materials. In order to judge the replenishment through manufacturing, it is preferable to enter certain information, as shown in step 10 02. Such information may include information about s κ υ, order, supplementary demand date, ME (earliest), ML (latest) parameters, as well as the demand for supplements and the fastest start of supplements (the fastest start of supplements will occur during planning The date before the start of the range). For example, suppose that the planning for Monday (8th) is completed on Monday (8th). It is further assumed that the planner publishes the schedule sheet on Wednesday (3rd) and starts calculating the supplementary start on Thursday (4th) instead of Monday (8th). In this example, the supplementary start will be set to replace Thursday (4th) instead of Monday (8th). The program (shown in Figures 10A and 10B) produces an output that shows the last acceptable date (demand date + ML) or before the last acceptable date, the quantity can be replenished by manufacturing (replenishing the available amount) This date is available for replenishment availability, and the flag indicates whether 100% of replenishment demand is at the last acceptable date (demand date + ML) or can be met by manufacturing before the last acceptable date. In step 1 0 05, a list of available SAD groups based on the date of the planned order is generated. Therefore, in determining the available SAD groups, the ABP system 1 0 0 will check the B applied to the order. All SAD groups in OM, and only those SAD groups that are available. In order to generate a list of available SAD groups, the ABP system 100 will first decide on all SAD groups in the BOM of the SKU with attributes. For example, suppose a planned order can be defined by certain attributes as follows: sedan @ 亚特兰大, sunroof = yes, electric window = yes. Based on the order, the relevant BOM of the order can be identified. This -65- (61) (61) 200305088

The concepts can be best shown with reference to the following examples. Referring to Figs. 10C to 10F ', it is not possible to lose four different groups of bm. Figure 10 (: shows a kind of bom for the "basic" of the car @ Atlanta. This BOM group can be regarded as a kind of bom for the "basic" of the bridge, regardless of the choice How (must have components). Therefore, the SAD group in this B OM group is just "SKU = Sedan @ 亚特兰大". Figure 10E &gt; shows the first type of ΒOM group. This group shows additional requirements Components, if the sunroof is configured as a selection, but not a power window. Therefore, the SAD group in the second group is "SKU = sedan @ 亚特兰大, skylight = yes and power window = no". Of course, in order to really The sedan 'defined by the SAD group in FIG. 10D is shown in the first group B (in addition to the secondary item sku in the second group (ie, FIG. That is, all minor item SKUs in Fig. 10c) will be needed. Fig. 10E is the third bom group, which shows additional required components, if the power window system is configured as a selection, but not a sunroof. About this The SAD group in the group is "SKU = Sedan @Atlanta and Skylight = No and Power Window = Yes" The last BOM group (as shown in Figure 10F) shows the additional required components. If the sunroof and power window system are selected as options, the SAD group in the fourth group is "SKU = Sedan Fensi &amp";# 卞 ㊇ 威特兰 大 and skylight = yes and power window = yes ". Please note that the second, third, and fourth SAD groups shown in Figures iOD to if Each still requires a secondary item SKU of the basic BOM (of FIG. 10C). Therefore, among these four groups, 'only one and four of the Sad groups will describe input orders with attributes (ie, when the first SAD When the attributes of the group do not conflict with the attributes of the input order with attributes, the attributes of the fourth sad -66- (62) (62) 200305088 group, and the attributes will actually match the attributes of the input order with attributes) It should be noted that the order will cause the attributes existing on the SKU or item to overlap, so that the user always has to look at the order instead of looking at s κ u or the item. Therefore, at step 1005, the list of qualified SAD groups Will produce. In this example, the list produced in step 1005 will only include The first and fourth SAD groups. The total number of SAD groups in the SAD group list is p and. All SAD groups found in step 1 005 will be processed through the holding step, using the loop in sequence until The ABP system 100 finds the "SAD group i" that satisfies one of two conditions: o) the available amount (SAD group i) = 0, which means either at (demand date + ML) or at (demand Date + ML), one of the SAD groups has zero availability. Once the available quantity = 0, there is no need to process the SAD group in the list; or (2) i =: P, which means that the system loops through all the parent SAD groups in the list. In step 1010, the ABP system 100 retrieves the first (or next) sad group in the list for processing. Therefore, the index lj in the list of sad groups is increased by 1 (that is, i — i + 1). Then, the ABP system 100 will retrieve all BOM configurations for the selected SAD group based on the order planned in step 10i. This is because the SAD group will not contain all attributes of the order. Therefore, in order to get a suitable BOM, the ABP system 1000 will look at the original order. For the purpose of explanation, "Configuration U" is definition 4 for the j-th configuration in the configuration list of "SAD Group", and the total number of configurations in the / monthly bill is q, where l £ j £ _Q. The configuration total is specific to the order -67- 200305088 (63) because the order has attributes that would not exist in the SKU / project, or the order attributes would cause attributes that exist in the SKU / project to overlap. In step 1 020, the system will retrieve the next configuration from the configuration list for "parent SAD group i" for further processing. Similarly, the index "j" in the configuration list is increased by 1 (that is, j — j + 1). As mentioned above, each configuration is essentially a list of secondary items needed to make the parent item. As long as at least one configuration complement is feasible, the parent supplement is feasible. Therefore, in step 1025, the AB P system 1 0 0 will generate a set of secondary items for configuring ij, and in step 1 030, it will retrieve the The next minor item in the list of minor items for further processing. In the preferred embodiment, it represents "k" on the configuration list. That is, the "secondary item SKUijk" means the k-th secondary item in the list of secondary items used for "configuration ...". The total number of secondary items in the list is R and 1. In a similar manner, in step 1030, the index "k" on the configuration list is increased by 1 (that is, kek + 1). Then in step 1 305, the ABP system 100 will copy the attributes of the order [preferably, the secondary items will be copied to the order. Secondary item SKUs (if included in the configuration) can temporarily add attributes to the order. When the next configuration is performed, the group must be stored on the order. ] And calculate the demand date and demand for the secondary item, and prepare the secondary item SKU. This step will require the ABP system 100 to preferentially select the pull amount, offset, and copy instructions related to the BOM relationship between the "Order" and the "Minor Item SKUjk". Pull Amount The amount of component material (for example, secondary item SKU) required to search (for example, the parent unit) per unit item. For example, for a car order, -68- (64) (64) 200305088 for headlights

Pull I for one. According to a specific embodiment of the invention, the demand date. The undesired item SKUjk) can be calculated by the following equations: · Demand date = Supplementary demand date · Delivery time (parent SAD group j) + offset (secondary item SKUijk) The required amount can be calculated as follows: Minor item SKUijk) = supplementary demand x pull amount (minor item SKUijk) is better and P, the selection attribute of the single list and / or input with attribute and / or the item corresponding to the input SKU with attribute will be copied to Use the secondary item SKUijk of the copy instruction on the BOM. The copy instruction is used to propagate the related attributes of the order / parent SKU / parent item to the secondary item SKU. Copying The 々command distinguishes what attributes need to be copied. After the procedure of step 105, the ABp system 100 will output a secondary item SKUijk (represented by a secondary item sku with ATtribSijk) with related attributes. The quantity and demand date can also be known from the above calculation. Use copy instructions to spread the appropriate attributes to secondary items, such as a surge in bill of materials. Appropriate attributes need to be propagated to lower-level secondary items to find inventory and replenish the correct secondary material. An example of a copy instruction will now be described with reference to FIG. 10G, which shows BOM, where the project name is shown in parentheses. If shown, this list is a property-based list. = 疋 All the parent-child relationships shown can be used for every order on Router A. For example, only if the customer has selected "Interface Type = 4 Ports", the 8 (^) relationship represented by "A" (between router-A and 4P-IMOD) is correct. Similarly, only the customer has selected " Interface Type = 8 Ports "and" Note-69- 200305088

Memories = 128MB ", the BOM relationship represented by" E "is cross. As mentioned above, attribute dependence is modeled using the parent SAD group. Therefore, the copy instruction for each BOM relationship in FIG. 10E is shown in Table I below. Reference number in the figure: Primary SAD group secondary item copy instruction A "item = router A" and "interface = 4 ports" 4P-IMOD from attribute = memory, to attribute = memory, to value = "" B " Item = Router A "and" Interface = 8 Ports "8P-IMOD attribute, to attribute = memory, to value =" "C" item = 4P-IMOD "and" memory = 128MB "MEM-128 unreplicated attribute D "Item = 4P-IMOD" and "memory = 256MB" MEM-256 unreplicated attribute E "item = 8P-IMOD" and "memory = 128MB" MEM-128 unreplicated attribute F "item = 8P-IMOD" "Memory = 256MB" MEM-256 Unreplicated attribute G "Project = Router A" ASSY-Master unreplicated attribute Η "Project = ASSY · Main" Cl Unreplicated attribute I "Project = ASS ASS Primary" C2 Unreplicated attribute

Table I assumes that there is an order for 50 units of Router-A within a 10-week period, and this order has configuration options: 1) interface == 8-port; and 2) memory 1 2 8 MB. It is further assumed that the inventory locations of various parts in the system are as shown in Table 11 below. -70- 200305088 (66)

Item / SAD group__One inventory item = router-A and interface = 8 璋 and memory = 128 MB __. 25 items = router-A and 50 interface = 4-chun and memory = 128 MB one__. ASSY · Main 50 MEM-128 10 items = 8P-IMOD and 20 memory = 128 MB items = 8P-IMOD and 30 memory = 256 MB _

Table II assumes that all parts have the same shipping time = 1 week and that no replacement is configured for any part of the system. Assume that 0 weeks ago, you need a router-A of 50 units with interface = 8-port and memory Η 28MB, and a router of 25-unit with 8-port interface module and 128MB &memory; 'Available' means that only 25 units are needed. Therefore, this requires 25 units of Router_a with an interface + 槔 and a router called Memory 2A. It will be transferred to the intermediary demand for all intermediate replacements (25 units, 9 weeks). From the BOM table, you can see that J has two parent SAD groups B and G that will be applied to • 71-200305088

(67) Router with interface = 8-port and memory = 1 28MB-A ", where the secondary item sfCu of group B is 8P-IMOD, and the secondary item SKU of group g is ASSY-main. Therefore, ABP System 100 will try to find the source of supply for these two minor projects. Finding supply can be achieved through the available net inventory or by manufacturing these parts. It is explained by the following: (1) Find out the supply from group G: Group G is a standard component, which is located in a router-independent option placed on the router. Therefore, when looking for deposit # or supplementary A S S Y-primary, there is no need to know the specific attributes of the order for this group. From Table II, it can be seen that there is an ASSY-main female SAD group, and an inventory of 50 units' is sufficient to meet the demand for 25 units. So ’in 9 weeks, the secondary item ASSY- is mostly feasible. (2) Find out the supply from group B: From Table π, there are 20 units of inventory for "item = 8P-IM0D and memory = 128MB" and "item = 8p_IM0D and memory = 256MB". And 30 units of inventory. As mentioned above, the inventory in this group is distinguished by attributes. Although all 50-unit 8-port interface modules are available at hand, not all of them are available. Only 20 units are available at hand, and there is demand for the remaining 5 units. Using the copy instruction in the BOM table can achieve the remaining 5 units. The copy instruction will copy attributes along the BOM level, but it will not help us to solve the inventory shortage. In Table I, the parent SAD group shows that the copy command is "from attribute = memory, to attribute = memory, to value =" "". The interpretation of the copy instruction is: transfer the memory attributes to the secondary item SKU, and copy the value of the order record attribute to the memory attributes of the secondary item SKU ". "= -72 · 200305088

(68) to order without copying to SKU. The output of this operation is a secondary object, that is, a "secondary item SKU with attributes". In this example, the secondary item SKU is 8P-IMOD, and the secondary item object is "80-IMOD with 128 MB of memory". Next, the inventory check of the secondary item object is achieved by matching the attributes of the inventory to the attributes of the secondary item object. Since there are already 20 units on hand, the ab P system 1 0 0 needs to add 5 units of minor items. The object is "8P-IMOD with 128 MB of memory". From Table I, it can be found that the parent S AD group e meets the demand, because this group has the secondary item sKU "8P-IMOD". In addition, the copy instruction of group E is "unreplicated attribute", which means that the attribute is not replicated. Therefore, after checking the table Π, it will be found that the ^ head / SAD group "MEM · 128" has 10 units on hand, which is enough to meet the remaining demand of s units. According to the supply method mentioned above, in step 1 040, the ABP system 100 will obtain the supply for the secondary item SKU, and will call the supply method for the secondary item SKU with AttribSijk. The output of step 104 is the available amount (with a minor item SKU with AttribsUk) and the available date (with a minor item SKU with AttribSijk). The ABP system 100 then updates the available date and the available quantity with the output determined by the above steps, as shown in step 1 045. According to the month of this issue, the update can be achieved in the following ways: available date (configuration ij) = maximum (Max) [available date (secondary item SKUijk) + shipping time (parent SAD group)-an offset (second To the item SKUijk), the available date (configuration U)] amount (configuration u) = minimum (Min) [available amount (secondary item SKUijk) / -73- 200305088 (69) pull amount (secondary item SKUijk ), Available quantity (configuration ij)] In addition, the determination of feasible flags is made by:

3: line flag (configuration ij) = yes (YES), if the following conditions F (a) available date (configuration {") &lt; supplementary demand date and (b) available quantity (configuration ij) = Supplementary demand. Or, the feasible flag (configuration ij) == no. In step 1 050, the ABP system 100 checks that the configuration available is equal to zero. If so, the system will no longer look at this configuration, and the program will return to step 1020 to get the next group sound. If no, then in step 1 0 55, the system will There are no more secondary items in China. If there are more secondary items k &lt; R) in the current configuration list, the program will go to step 1030 to retrieve the item (kek + 1) from the list, otherwise it will go to step ι〇6 〇, to determine the configuration search 4 According to a preferred embodiment of the present invention, when there are a variety of AB P system 100 will provide two types of mechanisms for searching and optimization is called "strongly feasible", and The other is called "the most suitable and feasible, (of Figs. 10A and 10B). The procedure will choose the feasible meaning of the requirement that the demand for the parent SAD group can be reached before the demand date (before). In the system, even if the system finds that the ABP system 100 will not stop searching. Instead, 100 will go through all configurations and search the parent sAD group and select the best configuration for drawing table targets. If you search The mechanism is strongly ^ In step 1 065, the program will determine whether the configuration of the feasible flag meeting table meets: the list of minor items that are equal to the amount of the list. If you continue to check the item (ie, the minor item spring mechanism. Configuration) Time, control. A "°" in a strong configuration (or in the demand line configuration, AB The P system is related to the model, and the configuration shown here is -74- 200305088 (70) is feasible. However, if the search mechanism is the most suitable type, the program will go to step 1 0 7 0, of which the AB P system 1 0 0 Will remember the best configuration found so far. In step 1 090, it will be determined whether there are more configurations for the current parent SAD group. If there are more configurations, the program will return Go to step 1 0 2 0 'to get the next configuration. In step 1 065, a judgment will be made as to whether the feasible configuration has been found [as indicated by the feasible flag (configuration i' ·) ]. If the feasible flag indicates that a feasible configuration has been found, in step 〇 075, the ABP system 100 will select the current configuration as the best configuration based on the strongly feasible type mechanism, and then Go to step 1 〇 8 If there is no feasible flag 'this means that no feasible configuration has been found so far (according to a strong mechanism)' then the AB P system 1 〇 〇 will go to step 1 〇 〇 and will remember Best configuration so far (however, because strong mechanisms are chosen, None of the configurations is feasible.) Then the program moves to step 1 090 to check if there is more configuration on the order. If there is more configuration on the order, the program returns to step 1 〇 2〇 To evaluate and process the next configuration on the order. Otherwise, if there is no more configuration on the order, the program will also move to step 1 080, where the system will calculate and update the available configuration for the purpose. Date and available amount. In this specific embodiment, the available date of the parent SAD group is the available date of the best configuration, and the available amount is the available amount of the optimal configuration. Then in step 1 08 5, ABp The system 100 will update the replenishment availability date. According to a preferred embodiment of the present invention, the supplementary use date is a larger beta supplementary available amount between the available date for the current parent SAD group and the current supplementary available date for the current parent- 75- 200305088 (71) The smaller of the available amount of the SAD group and the current supplementary available amount. Supplementary flag = Yes, only the following two conditions are met at the same time: 1) supplementary availability date S supplementary demand date + ML; and 2) supplementary availability = supplementary demand quantity. In step 1 092, it is judged whether the calculated supplementary available amount after step 1085 is equal to zero. If it is not zero, there is no need to process the SKU for the current configuration again, and the program moves to step 1096, where the ABP system 100 returns (ie, outputs) the replenishment availability date, replenishment availability, and replenishment Feasibility, and will be supplemented by the manufacturing process of step 1098. If at step 1 092, the supplementary available amount is judged to be zero, the ABP system 100 checks if there are more methods on BOM 1094. If there are more, the system of step 10 10 will fetch the next parent method (that is, the SAD group) for processing. Otherwise, in step 1096, the system will leave this B 0 μ method and return the supplementary availability date, supplementary availability, and supplementary feasible flag. Then at 10 9 8 the program 100 0 0 will end. Purchasing via purchase Refer to FIG. 11, which is a general process 1094 (as represented by step 610 in FIG. 6) which is supplemented by purchase. The program produces an output by attempting to plan the replenishment demand into available buckets of time along the timeline. This output can be in the form of a quantity and / or quality report. In step 1102, when the relevant data starts to be entered and / or retrieved and / or conforms to the grammar, the program will start. Relevant information may include, for example, the attributes of the order item, and information such as supplementary demand, date of supplementary demand, earliest (ME), latest (ml), length of time bucket interval, maximum period, and the like Timing Resources-76- 200305088

(72) information. Further, the time to purchase (PLT) depends on the order attribute of the "supplementary demand" for the purchase defined in step 1104. pLT is the delay time to be used for replenishment after the buy order (P0) has been placed. The time required to obtain the materials has been given and pLT will be used to determine when the order needs to be placed. In the AB system 100, this is limited by supplementary starting parameters. Recall that there is a planning range start / end, so no order will be planned at the beginning of the range or after the end of the range. It should also be noted that the "start of supplementation" will determine the earliest time for any supplementation. Any supplement that will happen fastest is "Supplement Start Time + PLT". In order to receive the "supplementary demand" on the "supplementary demand date", then the date that the PO must deliver (called the "purchase order date" or "POPD") is calculated:

POpD = Supplementary Demand Date-Purchase Shipment Time (RNQ), by which RNQ stands for Supplementary Demand. At step 1 108, a timeline of SKUs with attributes is generated. A timeline is a timeline that defines the sequence of related events. These time events are illustrated in FIGS. 12A to 12D and include, for example, purchase order placement dates (POPD), supplementary start date (RSD), purchase order placement dates plus latest date (POPD + ML) ), Supplementary demand date minus earliest (RND-ME), supplementary demand date (RND), supplementary start date plus PLT (RSD + PLT), supplementary demand date plus earliest (rnd + mE), and the like Thing. Based on the timeline generated in step 108, at least four general types of solutions are feasible. At step 111, the available options are decided. Based on the available scenarios, output is produced. The output produced will depend on the sequence of related time events (i.e., scenarios), and the time between -77 · 200305088

The barrel-like interval of time, the ability to include the replenishment of demand in the schedule. The various possible solutions and the output produced are described below. Figure 12 A is a timeline 1200 that depicts time events that can help define these scenarios. These events include purchase order placement date (POPD) 1 202, purchase order placement date plus latest (POPD + ML) 1204, supplementary start date (RSD) 1206, supplementary demand date minus earliest (RND-ME ) 1208, supplementary demand date (RND) 1 2 1 0, and supplementary demand date plus latest (rnd + ML) 1 2 1 2. It should be noted that these time events do not necessarily have to fall according to the timeline 1 2 0 0 of Figure 2A, but the order of these events will depend on the specified situation. For example, the choice of ML and ME is usually arbitrary. Therefore, the RSD date at 1206 can really lead the POPD + ML date at 1204. When a purchase order is delivered, the purchase process for replenishment usually begins. Generally, for any purchase order (P0), there will be a delay from the time when p0 is actually delivered to the date when P0 has been completed. As discussed earlier, this time difference is called the time of purchase or shipment, or "PLT" 1 2 丨 4. Purchase order Placement date (POPD) 1202 is the date when PO must be placed for PO, so that it can really be completed on the date of supplementary demand 1 2 1 0. Many companies will accept replenishment purchases before and / or after 1210 on the demand date. Therefore, the earliest available double date at 1208 (supplementary demand date minus earliest or RND-ME), and the latest acceptable date at 1212 (supplementary demand date plus latest or RND + ML) will also Define it. The supplemental start date or RSD at 1 206 is the actual or expected purchase order date. The timeline can be divided into bucket intervals 12 16. The displayed timeline 1200 is divided into time intervals, which indicate that the barrel-shaped intervals 12 16 are time-dependent. In addition to being time dependent, these bucket-like intervals of -78- 200305088 (74) can be defined by other factors such as quantity or quality factors. It should also be noted that the term "date" is so widely used here that it can be read as an exact point in time, including, for example, down to the second of the day. Many companies have many restrictions to prevent them from having unlimited capacity. To more accurately reflect the true limits, the capacity limits are preferably represented in the supplement by purchasing models. One approach is to model this by defining a time-based “maximum capacity”. These maximums are called "period maximums". These cycle maximums can be used to limit the number of materials or items whose resources (such as suppliers) can be produced or sold in any known time interval. Other rules can also be included (such as the concept of “continuing existence”), which allows the supplier's model to continue to exist in any excess product produced during the earlier time period for use in later time periods. The following is a brief summary of the three basic scenarios, followed by a more detailed description of the various scenarios. The three basic situations are when the full number of supplements is on time, when the full number of supplements is delayed, and when the full number of supplements is not feasible. Case 1: The supplement is marked as feasible and the fastest available date has been recorded. No further processing is required. Case 2: Supplements are marked as feasible, the amount available on the recorded demand date, and the fastest available date recorded. Users can set flags that allow the system to search for one or more alternatives to improve the timeline. Case 3: Supplements are marked as infeasible, and the amount available on the demand date and the demand date + latest date have been recorded. In this example, the AB P system 100 replaces the trial with Case 2 in an attempt to make up for the difference between the demand date + the latest date. -79- 200305088

(75) The user can set a flag that allows the AB system to search for an additional quantity of one or more alternatives to improve the timeline. If the replacement cannot be found to make the configuration feasible, the configuration is marked as infeasible and ignored. The maximum period is used when the user cannot get all the material the user wants within a known time frame. This can happen in daily necessities such as iron ore, or components in high demand such as computer CPUs. For example, the user can get a configuration of no more than 10 tons in a week, or 50 CPUs in a month. In this example, the user needs to decide how to use these parts to get the most money. If the expanded output capacity of the distribution output is lacking, the ABP system 100 can determine the minimum amount of replacement to use. This can happen in case 2 or case 3. The following is a detailed description of each scheme. The first case is when POPD + ML &lt; RSD. The replenishment start date (RSD) is the date when the actual replenishment purchase order is delivered. Referring to FIG. 2B, it is a timeline 1 220 showing the first scheme. In this scenario, pPCC at 1 222 + mL is leading the RSD at 1 224. Therefore, the completion date of the order at 1 226 is after the RND + ME date of 1 22 8 based on PLT 1 230. In this example, the purchased material or item is not available until after the latest acceptable date. So 'if in step 丨 丨 丨 〇 case 1 has been decided, an output will be generated (output 1.1). Output 1.1 replenishment available amount = 0 replenishment date = maximum date supplementary feasible flag == error -80- 200305088

(76) The second scenario is the case where the POPD date is earlier than or equal to the rsd date, and the RSD date is earlier than or equal to the sum of the POPD and ML dates: POPD £ _ RSDSPOPD + ML. Referring to Fig. 12C, it is a timeline 1240 illustrating the second scheme. The interval between the POPD date at 1242 and the RND date at 1244 is defined as the PLT at 1 246. Unlike the timeline shown in Figures 12A and 12B, the RSD at 1 248 leads the POPD + ML date at 1 250. The interval between the RSD date at 1248 and the POPD + ML date at 1250 is a potential interval for placing the PO. This interval is called the "potential PO resettlement interval" 1 252. The available date interval 1 254 corresponding to this potential PO placement interval 1 252 is between the RSD + PLT date at 1 256 and the RND + ML date at 1 25 8. This interval will run from left to right (starting at 1 256 RSD + PLT) to check to find the barrel interval that will not reach the maximum value of the anti-purchase cycle. If necessary, a division is made across the number of bucket intervals. If it is judged that this scheme is available, a judgement is made to know which secondary schemes under the second scheme are available. There are three sub-schemes below the second scheme which will result in three possible outputs, outputs 2.1, 2.2 and 2.3.

The first plan for the second plan is when the 100% supplementary demand can be placed at the end of the interval (RSD + PLT at 1 156, 1? ^ 0 + 1 ^ 10 in 1 25 8) The following output will be generated during the interval: Output 2.1 Supplemental Available Date (RAD) = End date of the last barrel interval, so that the supplementary amount can be completely placed. There are two exceptions: If this barrel interval contains RSD + PLT , Bay 1J RSD + PLT will be the RAD date, or if this barrel interval contains RND + ML ', then RND + ML will be the RAD date ° -81-200305088 (77) Supplementary available quantity = Supplementary demand quantity Supplementary feasible flag = The second scheme that is feasible about the second scheme is when the quantity X is greater than zero, but less than 100% of the supplementary demand, it can be placed at the end of the interval (supplementary start date + PLT, supplementary demand date + ML) For a bucket interval, the following output is produced: Output 2.2 Supplemental Available Date (RAD) = the end date of the last bucket interval, whereby the quantity X can be completely placed. There are two exceptions: if this bucket interval contains a supplementary start Date + PLT, then RAD and supplement start date + PLT is equal, or if this barrel interval contains the supplementary demand date + ML, RAD is equal to the supplementary demand date + ML. Supplementary available quantity = X Supplementary feasible flag = feasible. The third option for the second option is due to When the period is reached, nothing can be placed in the barrel-shaped interval that extends to the end of the interval (supplement start date + PLT, supplementary demand date + ML). If the third solution is used, the following output will be generated : Output 2.3 Supplement available date = Maximum date Supplement available amount = 〇Supplement feasible flag = Not feasible. The third solution is when the POPD-ME date is earlier than or equal to the RSD date, which is earlier than or equal to the POPD date, and it is earlier Date equal to or equal to POPD + ML: -82-200305088 (78) POPD-ME £ _ Supplementary start date £ jP〇PD £ jP〇PD + ML. This scheme is essentially the same as the third time of the second scheme above. The scheme is the same. Therefore, the interval (supplement start date + PLT, supplementary demand date + PLT) will be checked to determine whether the bucket interval in the interval will be sufficient. The output of the third scheme will be the same as the third of the second scheme. The sub-scheme is the same.

The fourth scenario occurs when the supplementary start date is less than or equal to the purchase order configuration date minus the earliest, which is less than or equal to the purchase order configuration date, which is less than or equal to the purchase order configuration date plus the latest: RSDSPOPD-ME1 POPD £ _POPD + ML. Referring to FIG. 12D, a marginal line 1260 of the fourth scenario is shown. Timeline 1 260 is divided into barrel-shaped intervals 1261. The barrel interval 1 2 6 1 is limited by the increased time and capacity. In this timeline 1 2 60, the fourth scheme requires that the RSD date at 1262 is earlier than or equal to the POPD-ME date at 1264, which is earlier than or the same as the POPD date at 1266, which is earlier than or equal to POPD + ML Date at 1 268: RSD £ jPPD-MES POPD £ _POPD + ML. Furthermore, the RSD + PLT dates shown at 1270 on the timeline of 1 260 are given priority over the RND-ME and RND dates at 1 272 and 1274. Referring to FIG. 13, it is a process for generating the output of the fourth scheme. When a decision is made as to whether the supplementary demand can be fully provided by the bucket interval contained in the [RND-M E] date of step 1304, the procedure 13 00 will begin. If successful, the following output will be produced in step 1 3 0 6: Supplementary available quantity = Supplementary demand quantity Supplementary availability date = Supplementary demand date-ME Supplementary feasible flag = feasible -83- (79) (79) 200305088

In step 1308, it is determined whether at least a part of the amount can be placed in a barrel-shaped interval 1 275 (RND-ME) (see FIG. 12D). If not, then at step 13 10 an output is displayed that is not feasible [correct? ]Output. If part (for example, greater than zero, but lower than the supplementary demand) quantity can be placed in the barrel section containing [RND-ME], it will back out to conceal multiple consecutive barrel sections, one barrel at a time And it will be placed in every bucket interval that does not violate the cycle as much as possible [please explain this sentence? ]. It is better, and it will not move backward until one of the three cases is met: Case 4 · 1. The supplementary demand is only partially located in the bucket-shaped interval containing (supplementation start date + PLT). Case 4.2: The replenishment demand is fully settled, but it is not located in the bucket interval containing (replenishment start date + PLT). Case 4 · 3: The replenishment demand has been completely placed in the bucket interval containing (replenishment start date + PLT). At step 1311 ', the process is started by returning to the time bucket region 1 274 containing (RND-me). At step 1312, a barrel section 'is moved backward and the barrel section is filled as much as possible. In step 丨 3 丨 4, it is judged whether it is the case of case 4.1. If so, an output based on certain factors is generated in step 1316. Fig. 14 is the output flow of the case 4 · ι (as shown in step 1 3 1 6 in Fig. 13). Multiple consecutive barrel sections in the forward direction will be checked, starting with the barrel section ι276 (in FIG. 12D) after the barrel section 1274 that occurred (rnd-me), and will be placed as much as possible In each bucket interval that does not reach the maximum value of the counter-period. It will not move backward until one of the following three conditions is met (e.g. -84-200305088

(80), towards the earlier time interval), one barrel interval at a time: Case 4.11: The supplementary demand is not completely located in the barrel interval containing (supplementary demand date + ML). Case 4.12: The replenishment demand has been completely placed in one or more bucket sections, but not in the bucket section containing (supplementary demand date + ML). Case 4.13: The replenishment demand is fully settled and is located in a barrel section containing (replenishment demand date + ML). Program 1 400 will return to barrel interval 1 276 (before barrel interval 1 274 (Supplementary Demand Date-ML) occurred) and place it as close as possible to each In a bucket interval, and it starts at step 1 402. This means that an attempt will be made to fill each bucket interval before the time when (supplementary demand date-ML) bucket interval 1 474 occurs, and will include (supplementary demand date + ML) date The barrel interval reaches the barrel interval before the end of the barrel interval 1 278 (the barrel interval 1 3 78 in FIG. 12D) on the (supplementary demand date + ML) date. At step 1404, one barrel interval is moved backward to the next earlier time barrel interval. At step 1406, the timeline is checked again, and it is judged whether it is the case of 4.11. If so, the following output will be produced at step 1 0 0 8: Supplemental availability date = end date of the last barrel interval where non-zero quantities will be placed Supplementary availability = total amount that can be placed Supplementary feasible flag = not feasible If it is not 4 · 1 1, in step 1 4 1 0, it will be determined whether it is -85-200305088.

(81) Case of 4.1 2. If it is the case of 4 · 1 2, then the output will be produced in step 1 4 1 2 as follows: supplementary availability date = the end of the last barrel interval where non-zero quantities will be placed. Supplementary availability = supplementary demand. Flag = feasible If it is not the case of 4 · 1 2, then in step 1 4 1 4 it will be judged whether it is

4.1 Case 3. If it is the case of 4.13, the output will be as follows: supplementary availability date = supplementary demand date + ML supplementary available amount = supplementary demand supplementary feasible flag = feasible If it is not 4 · 1 3, it will return to step骡 1 4 0 4 and will move back to a bucket interval again to start the program. Referring to FIG. 13, if it is not the case of the 4.1 case, it is determined whether the case is the 4.2 case at step 1 3 1 6. If it is the case of 4.2, then the following output will be produced in step 1 3 1 8: supplementary availability date = end date of the last barrel interval where non-zero quantities will be placed supplementary availability = supplementary demand supplementary feasible flag Mark = feasible If it is not the case of the 4.2 case, then in step 1 320, it will be determined whether it is the case of the 4 · 3 case. If it is the case of the case of 4 · 3, then in step 1 3 22, the output will be as follows:

Supplement Available Date = Supplement Start Date + PLT -86- 200305088

(82) Supplementary available quantity = supplementary demand supplementary feasible flag = feasible. If it is not the case of 4 · 3, it will return to step 1 3 1 2 and will not move back a barrel interval until the output has been generated, again Restart the procedure ° _ Supplemental replacement by replacement If the supplementary attempt made by manufacturing and / or purchasing does not fully meet the material feasibility procedure 6 supplementary step 6 1 0 (Figure 6), the ABP system 1 00 will attempt Make up the difference between the quantity replenished by manufacturing and / or purchasing and by replacement and the total available quantity. Replaces any type of SKU that can be used, including FG SKUs with attributes, SKUs, minor item SKUs, and the like. Replacement models are generated to help replace SKUs with attributes. Whenever a replacement needs to be used for an SKU with attributes, after the ABP system 100 attempts to manufacture using one of the defined BOM configurations, it attempts to replace the missing SKU. The substitutes will be processed in priority order, and all the substitutes will test the existing inventory before trying any manufacturing configuration on the substitutes; otherwise the manufacturing configuration of the high priority substitutes will be tried first. Substitutions can be modeled by generating substitution tables. Substitutes can define all children [secondary items whose children are parent's, such as 'cars are parents' and car seats are children's], but are usually not used for finished products. Multi-stage substitutes are also permissible, such as substitutes for substitutes. At steps 614 and 616 (Fig. 6), an attempt is made to attempt to meet any supplementary demand that has not been achieved by using a supplementary step of 6 1 0. Referring to Figure 14B, it will be used in the process of supplementing with the substitute product 1450. The process will start when some -87- 200305088 (83) data / parameters have been retrieved and defined. The retrieved data can include the parent SKU with attributes (the parent SKU with attributes, which will be optional), the minor item SKU, the original demand (the minor item demand), and the minor J page demand Volume and date, earliest (ME), latest (ML), and similar information. The abp system 100 will use this information along with any substitution preferences to achieve what is called the "replacement demand" or "SNQ" &lt; required number of substitutes. SNQ is for substitutes with attributes SKU 'which is available on or before the last acceptable date (replacement demand date + ML). The output of the replacement function (as shown in step 6 1 4 of Fig. 6) includes the amount of the substitute available, the date when the substitute is available, and the flag of the substitute feasibility. Based on the information provided, acceptable alternatives can be determined in steps 1 4 5 4. If more than one acceptable substitute exists', the priority of each substitute is judged at step 4 5 6. In general, some substitutions of w will be preferred over other substitutions. Therefore, it is better to prioritize acceptable products. At step 4 5 8 one of the acceptable products will be selected to judge the feasibility. In order to determine whether the selected substitute is available for replenishment, an inventory check is performed first in step 1460. In step 1462, it is determined whether the inventory can fully meet the demand before the demand date. If not, then in step 1464 an attempt is made to achieve any inventory shortage by manufacturing or purchasing. Procedures for supplements by manufacturing and / or purchasing replacements can be accomplished using the procedures described above for supplements by manufacturing or purchasing. If there are more acceptable substitutes, then return to step 1 45 8 to determine the feasibility of the next acceptable substitute at step 1466 '. In step 1 468, select Override Priority. This can be accomplished through the use of flags, which are explained below. -88- 200305088 (84) At step 1 470, one or more substitutes will be selected based on the priority, feasibility, and preference of the substitutes. Supplements by substitution can be modeled by generating substitution tables. This table has one or more rows that govern how the ABP system 100 can implement the replacement. This table can be used to define some items. If a parent SAD group is specified, when the order matches this SAD group, only relevant substitutions will be allowed. If this is not specified, the substitution rule defined by the column for all substitutes S KU with attributes is correct 'is explained by the substitute SAD group. In other words, substitution can be applied to SKUs in general, regardless of the parent (when the parent's behavior is empty) 'or it can only be applied to certain parent-child relationships. In doing so, users can use SAD groups to further restrict when substitutes are allowed. Substituting rows in the table defines a secondary item SAD group. The secondary item SAD group indicates the secondary item SKU that will be replaced. The other can define secondary item SKUs. This line (which can be implemented as two separate lines • Substitute Item and Substitute SKU) indicates that the SKU is an acceptable substitute for the 'entry item SKU' with attributes. Copy instructions can be defined. This line contains the reference number of the copy instruction specifying the attributes that must be copied to the secondary item SKU. For example, the record in the substitution table can be as follows:

Feng SAD Group: Item = Router A &amp; Required Item SAD Group: Item 2 Interface Module and Interface Type = 4 itch I Substitute SKU: Item = Interface Module and Location II Atlanta Jl System Instructions: Attribute = "Interface type", go to property one "Interface type-89- 200305088 (85) style", (or the user can leave this space), and the value == "8 -port". The above modeled substitution relationship can be transformed into the following business rules: For the parent router A, the 4-port interface module can always be replaced by the 8-port interface module. Although not shown in this example, users can specify additional attributes and use the copy command to copy to the secondary item SKU. Priority can be defined by one of the lines. A known minor item SKU with attributes (assuming this is just a SKU) may have many attributes. This trip models the relative priority of each of these substitutes. For example, the secondary item SKU "Y" can have three different attributes (each attribute is a different record in the table), SKU "A", SKU "B", and SKU "C". Using priority lines, users can model relative preferences among these different alternatives. For example, the user can specify that SKU A is the most preferred (priority = 1), SKU B is the second most preferred (priority = 2), and SKU C is the least preferred (priority = 3) ° Other rows Will be produced as well as designed for other purposes. For example, rows can be designed for valid dates. The effective date is the earliest point in time when the substitution relationship is correct. Rows can be designed to stop dates. The stop date is the latest point in time when the replacement relationship is correct. Lines can be generated for pulling amounts. When using substitutes, the substitution feature allows the user to plow different draw volumes. By specifying the pull amount in this row, when using a substitute, the user can overlap the B 0 Μ pull amount between the parent item and the secondary item (which will be replaced). For example, the parent item may be SKU "X", the secondary item may be S K U "Υ", and the pull amount on the B 0 M relationship may be 4. If the secondary item SKU is not replaced by the secondary item SKU ζ, the user can specify not -90- 200305088

(86) Use the same amount of draw (specify 5). This property is essentially useful in chemical industry applications. Guilds are generated and designed for serial numbers. Multiple parent SAD groups in the substitution table · Secondary items SAD group combinations (modeling different replacement choices / rules) can be applied to the female SKUs with attributes in the memory_secondary items with attribute combinations SKU. In this example, preferably, the replacement selector / rule with the lowest number is used. There are also factors specific to the parent SAD group-secondary item s AD group combination (relative to the parent SAD group · secondary item s AD group-secondary item s KU combination) can be modeled in the substitution table (require Note that the columns in the replacement table will be specific to the parent SAD group-secondary item s AD group-secondary item s KU combination, which is usually different from the style factor in the replacement table. The BOM table is used to combine These factors are modeled better). For example, the AB P system 100 allows for many types of "flags", which allows users to easily enforce predetermined business rules. These flags include, for example, the "Partially Complete" flag, the "Complete Mode" flag, the "Not Used Until Used" flag, and the "Multi-Level Replacement" flag. If the partial completion flag indicates that only partial completion has been reached, this means that only the original demand (before net output / manufacturing / purchase of the original replacement product) can be fully satisfied from the stock / replenishment of the replacement product separately. can use. If the original demand does not fully meet the net / supplement of using a substitute, the substitute will not be used. If a replacement for a minor project SKU is not found, and it can fully meet the demand (secondary project demand) even after trying multi-level substitution, the substitution is not feasible. The completion mode flag will provide completion functions and manage net / supplementary behavior -91- 200305088

(87) Search for a replacement function that spans multiple replacements. For this flag, there are two permissible settings: “net value across all substitutes before any replacement” and “net value and supplementation based on the priority of the substitute”. The manner in which the completion mode flag affects the behavior of the planning process can be explained by the following example. Assume that SKUs A, B, and C are configured as replacements for the secondary item SKU "Y". A prefers B, and B prefers C. It is further assumed that the replacement demand is 50 and the original demand is 80 (indicating that 30 units are completed using the inventory / replenishment of the secondary item SKU "X"). Assume that the inventory locations for SKU A, B, and C are as follows: SKU A: 20 units SKU B ·· 10 units SKU C: 10 units In addition, anywhere in the range of SKUA, B, and C, no longer Receipts included in the schedule and some completion flags will be set to Yes. Based on the above example, if the completion mode flag is set to "net value across all substitutes before any replacement", the method of completing the substitution function of the demand for substitutes can be as follows: 1. 20 units of A net inventory (After this point, 5 0-2 0 = 30 more units will be required). 2. 10 units of B net inventory (after this point, 3 0-1 0 = 20 more units will be required). 3. Net inventory of 10 units C (after this point, 20-10 = 10 more units will be required). -92- (88) 200305088 4. Now return to A and try to replenish A unit. Fake and. ‘A can be moderately supplemented. At this point, I sighed that there are 5 units 5 · Then, we can know whether 5 units of B are available for more units. Fruit supplement. Due to the upward trend, the replacement rule will use the following as the required quantities: 、 &quot; Should be reached to achieve the replacement • 20 units of inventory a • 10 units of inventory b • 10 units of inventory c • used Planning order for A of 5 units • Planning order for B of 5 units such as Wo sculpting • Work penalties cross the non-net value of all substitutes ”, then the method of completing the substitution function of the demand for substitutes is completed. It can be as follows: · I 2 0 units of A net inventory (after this point we need 50_20 = 30 more units) 2. Try to replenish 30 units of A. We assume that we can only moderately fill A without 5 units. After this point, we need 25 more units. Net inventory of unit B (after this point, we need 2 5 -1 0 = 15 more units) 4. Replenish 15 units of B. We assume this is feasible. At this point, we do not need any further inspection. So the replacement C will not even come across. The "Use Only Until Depleted" flag can be used to determine the source from which the replenishment can be derived. If this flag is set to "Yes", it will be used for the primary (secondary) period until -93- 200305088 (89) is exhausted of all alternatives. To the project) new planning orders will not be generated. This flag is set to Yes if you want to minimize any new supplements used for minor items. In other words, if this flag would be set to yes, then the rule would behave as follows: 1 • Receipt of any net inventory / minor items included in the schedule. 2. Attempts will be made to achieve the remaining amount (if there is any remaining amount) through substitution by resorting to the substitution procedure. The replacement process will attempt to fulfill this need by exhausting all possible alternatives for minor items (including multi-level replacements, if configured). 3. If the replacement process does not fully meet the remaining requirements, an attempt will be made to supplement the secondary items by generating a planning order for the number of secondary items remaining after replacement. The "multi-level replacement" flag will direct the replacement process to the use of recursive technology. If the multi-level substitution flag is set to "Yes", the ABP system will attempt to achieve the substitution requirement through the substitution procedure in the call recursive form. If this flag is configured (that is, set), the replacement program will look for substitutes in the substitute, or substitutes in the substitute, which are substitutes in other substitutes, and so on. The AB P system 1 00 will identify potential listing opportunities for each resource on the list of allowable resources generated in step 4 1 0 in FIG. 4. As discussed above, the system 100 repeats the list of locations via known orders. At each location, the system 100 will iterate through the list of allowable resources, and when it repeats, it will evaluate potential listing opportunities. At the end of the order, the system 100 repeats the best listing opportunity across all resource-location combinations and is included in the planning table. -94200305088

In order to evaluate potential listing opportunities on known resources, it is better that the system 100 first identifies potential listing opportunities on resources. A potential listing opportunity can be defined as a bucket interval within the time when all available limits of the order are met. In other words, orders can be included in the schedule within barrel-shaped intervals that do not reach any limit. The potential listing opportunity on any resource is a function of three different entities (material availability, resource capacity limits, and dependency limits). · There are essentially two types of resources, primary and secondary. The main resource determines whether there is sufficient capacity to meet or fail to meet the demand. This can be modeled in the finest particles (e.g. in the order of days). Subordinate resources are also needed. Granularity below the level of the main resource cannot be modeled. All resources and materials related to the order must be available at the same time. Resource capacity limits are usually the most basic limits related to resources. In general, each resource will explicitly have a capacity limit associated with it. Orders placed on a resource will be checked for resource capacity constraints. In addition, it is assumed that the bucket-like time interval on the capacity limit has the finest particle shape. To model the capacity limit of a resource, a capacity calendar is generated and related to one resource and many resources via, for example, a resource group. Unlike resource capacity limits, ancillary limits are "abstract" limits that may or may not be available for known orders. Ancillary restrictions can be implemented by Bollinger triggers, which define the availability of restrictions on orders. In addition to resource capacity restrictions, the order will check the feasibility of other restrictions. These subsidiary restrictions are triggered by the presence or absence of a property (or a combination of properties). An example of an ancillary restriction is: -95- 200305088 (91) Number of red cars with windows &lt; 1 ο ο This is an ancillary restriction for orders that have both of the following attributes: color = red and sunroof = yes. To create affiliation restrictions, designated entities can be "bonded" together. The three entities are SAD groups, resources or resource groups and calendar maximums. To illustrate this concept, the following examples are provided. Assume that no more than 50 cars are made in a day, and that each week is defined by the seven working days at the Atlanta plant. If we decide to model the main capacity limit in days, there will be a maximum of 50 cars per day. If we decide to model the main capacity limit in terms of weeks, there will be a maximum of 5 0 X 7 = 350 cars per week. It is assumed that the number of red cars with a sunroof manufactured in Atlanta does not exceed 50 cars per week. Next, the user will generate an affiliated restriction, the designated SAD group (color = red and sunroof = yes), and the maximum value of the designated restriction is 50 cars per week. Ancillary restrictions can be specific to a resource, specific to a resource group, or overall. If a restriction is specific to a resource, the restriction can only be used when an attempt is made to include an order on the resource in the schedule. If the limit is overall, the limit will be used regardless of which resource the order is listed in the plan. In the example above, restrictions are specific to all Atlanta-based resources. In implementing subsidiary restrictions, calendars related to restrictions are generated. Each limit will have a mechanism to specify how much of its status (barrel interval) will be used by the order if this order is listed in the plan table with this status (barrel interval). There are many ways in which the order can reduce the limited capacity: Case 1: (Quantity) Reduce the capacity of the bucket interval by the amount of demand on the order

In this example, the order quantity is always reduced. For example, if five cars are needed, it will be reduced by a difference of five. Used to limit the number of allowable units. Μ / brother 2 · (1) Reduce the capacity of the bucket interval by one unit per order τ ^ In this example, for orders, always decrease by 1. Used to limit, which limits the total number of allowable orders relative to the quantity produced. Case 3: (UDA) Query the configured values of the attributes of the order / item / SKU. Important attributes, and reduce the capacity of the bucket interval by the value of the order / item / SKU. In this example, the value in the User Defined Attribute (UDA) is used to determine how much to reduce. It is usually used when the user wants to limit the total amount of the order and another attribute that is externally modeled at the same time. For example, suppose that a shipping company would limit how many units a car can transport, and would like to limit the total weight of the shipment. In this example, one person can replay the total of the order into UD A. Case 4: (UDA * Quantity) Query the value of the order / item / SKlj attribute, and if this value is different from the value of the attribute of the order that was previously listed in this state, the capacity will be reduced to zero, and otherwise it will Decrease by 1. In this example, the value in UD A is used and multiplied by the order quantity to determine how much to reduce. Assume that the factory limits how many cars can be made in a day, and limits the number of hours it takes to make a car. In this example, one can put the number of hours it takes to make a car into UD A and multiply it by the number of cars in the order ', the total number of component hours. Case 5: (setting) query the attribute value of the order and determine whether this value exists in the order of the prior (or next) status; if the attribute value does not exist before -97 · 200305088 (93) (or the next ), It will decrease by one unit, otherwise it will decrease by zero. If the SKU / attribute value is not in the existing bucket interval, it will decrease i, otherwise it will decrease 0. The number of types that are usually used for things that can be achieved in buckets. Case 6: (On) If the SKU / attribute value is not in the previous bucket interval, but in the current bucket interval, it will decrease by 1, otherwise it will decrease by 0. When moving from barrel to barrel, it is often used to limit how many new things can be achieved. Case 7: (Off) If S K U / attribute value is in the previous bucket interval, but not in the current bucket interval, it will decrease by 1, otherwise it will decrease by 0. When moving from bucket to bucket, it is usually used to limit how many types of things can be removed. Referring to FIG. 15A ′, it is a flow 150 (usually represented by step 414 in FIG. 4) for judging the feasibility of the restriction. The restriction feasibility process 1500 will try to find the barrel-like interval on the grain limit, in which the order is feasible for all the restrictions (capacity and subsidiary) applied to it. Limiting the feasibility procedure 丨 5 00 will involve many steps. Procedure 1 500 is based on many parameters that were well known before the procedure was implemented. For example, from the previous steps, the order demand to be manufactured and the material availability date for the order are assumed to be available. Furthermore, due to the previous steps, the schedule interval used for the order is known. Also based on the previous steps, the target resource (for example, allowable resource) is known. Below is a brief description of the k supply stream private 5 00, followed by a more detailed description of some steps 4 in Figure 15a. When a set of restrictions for an order for planning has been determined, the procedure 1 500 will begin at step 1 502. This set of limits used for orders -98- (94) --- (94) --- 200305088 system includes capacity and subsidiary limits for resources. In step 1 504, it is judged that it is effectively included in the schedule interval. In other words exaggerate ^ Narrow down the correct listing of the earliest materials available using the configuration plan — clothing. At step 506, it will be judged whether the SAD group is frozen or not. The order level will be described. If the frozen SAD group describes this order, then this order will be placed in a barrel-shaped range with a capacity limit, where the effective demand date will decrease by H at step 1508. The item "Relocation" will use ‘because the order has not yet been listed in the plan. The resource that will try to place the order is just one of the resources in this group of allowable resources ^ σ ′. It should also be noted that, the order resettlement assessment% sequence described below will be used to evaluate the current resource listing opportunity (relocation). 〇 / 、 Orders will not be listed in the schedule until the best opportunity for inclusion in the schedule is found. At step 1510, the program jumps to the step called Limit Feasibility Program 15 and proceeds to the order placement evaluation step of step 421. If there is no SAD group describing the order, then at step 1512, it will decide It is used for order schedule control. At steps 15 and 14, feasible bucket intervals will be searched. At step 1 504 of FIG. 15, a judgment will be made to determine the effective schedule interval. Column The schedule interval can be defined by the intersection of one or more time intervals. The time interval will depend on various factors related to the order. At least four types of effective inclusion in the schedule interval are feasible. Refer to Figure 1 5 B, which is a procedure used to determine the effective inclusion in the schedule interval based on certain parameters. In step 1 522, it is determined whether there is a valid demand date. For example, (Figure 4) step 4 0 2 will produce Is invalid valid demand date? If so, the valid demand date will exist and the program will move to step 1 524. At step 1 5 24, it will be determined whether the earliest (ME) and latest (ML) are invalid. None-99- 200305088 (95 )

Effect, the effective inclusion in the schedule interval is intersection A. Intersection A is defined as the intersection of the following intervals: • The interval between the material availability date and the planned end date. • The interval between the planned start date and the planned end date. • The interval between (effective demand date-earliest) and (effective demand date + latest). • The interval between the start date of the first bucket interval on the capacity limit and the end date of the last bucket interval on the capacity limit. If neither ME nor ML is valid, then in step 15 28, the effective inclusion in the plan table area is intersection B. Intersection B is defined as the intersection of the following intervals: • The interval between the material availability date and the planned end date. • The interval between the planned start date and the planned end date. • The interval between the start date of the first bucket interval on the capacity limit and the end date of the last bucket interval on the capacity limit. If the order has no expiration date, at step 1530, it will be judged whether the ME and ML are invalid. If none of them are valid, then in step 1 5 3 2 the valid schedule will be the intersection C. Intersection C is defined as the intersection of the following intervals: • The interval between the material availability date and the planned end date. • The interval between the planned start date and the planned end date. • The interval between the start date of the first bucket interval on the capacity limit and the end date of the last bucket interval on the capacity limit. If the booking does not have a valid demand date, and the ME and ML are not invalid, then in step 1 5 3 4 the valid listing schedule interval will be intersection D. Intersection D is defined as the intersection of the following intervals:

-100- 200305088

(96) • The interval between the material availability date and the planned end date. • The interval between the planned start date and the planned end date. • The interval between the start date of the first bucket interval on the capacity limit and the end date of the last bucket interval on the capacity limit. In step 1 5 1 2 the schedule control for the order is determined. The inclusion of a schedule control affects the way the search for feasible bucket intervals is handled by the program. The four types of daily schedule control or goals can be supported by procedures, forward, backward, just in time (JIT), and "not included in the schedule". Referring to FIG. 15C, it shows a timeline 1550 that was previously included in the control concept of the schedule. In this timeline 1 550, the relevant points of time are the start date (SDESI) 1552, the effective demand date 1 5 5 4 and the end of the effective schedule interval. Period (EDESI). The timeline will move from the left (earlier time period) to the right (later time period) ^ If the listing schedule used for the order is controlled to "forward", it will be used for the feasible bucket interval (which meet The capacity limit and all available ancillary limits) are searched starting from bucket intervals on the capacity limit, where the effective date for inclusion in the schedule interval 1 50 2 will decrease and move forward from there. Orders placed in the first bucket interval satisfy all restrictions. If we can't find a single feasible barrel interval in the interval between SDEDI 1 52 and ED EDI 1 56, the order cannot be included in the plan. Fig. 15D is a timeline 1560 showing the concept of future control. If the inclusion schedule for an order is controlled to be "backward", the search for a feasible bucket interval (which satisfies the capacity limit and all available ancillary restrictions) will begin at the bucket interval above the capacity limit, where The end of the effective schedule period 200305088 (97) date will decrease and move backward (for example, to the left of the timeline 1 5 6 0). Orders placed in the first bucket area meet all restrictions. If the feasible interval between SDESI 1562 and EDESI 1566 cannot be found, the order cannot be included in the day meter. Figures 15E and 15F show timelines 1570 and 1580 for two different cases where JIT is included in the control concept of the schedule. In the first case (Figure 15E), the order has a valid demand date of 1 5 74. If the order has an effective demand date of 1 5 74, the system will first try to place the order in a bucket interval on the capacity limit, where the effective demand date will decrease. If this bucket interval is not feasible, the system will proceed in the backward direction (early in the schedule) until it reaches the SDESI 1 572 date. If it is determined that in the interval between SDESI 1 5 72 and the effective demand date 1 574, no barrel-shaped interval is feasible, the system will proceed in the previous direction, starting from the effective demand date 1 5 74. If it is determined that in the interval between effective demand date 1 574 and EDESI 1 5 76, no barrel interval is feasible, the order cannot be included in the plan. Figure 15F shows the timeline of the second JIT situation 1580, where the order has no effective demand date. If the order does not have a valid demand date and if it is included in the schedule control type as ΠT, the action is very similar to "list in the schedule forward". In this example, the system will look for feasible bucket intervals by first looking at the bucket intervals on the capacity limit, where SDESI 1 5 82 will be reduced and will search for feasible bucket intervals in the previous direction (which meets the capacity Restrictions and all available ancillary restrictions). Orders placed in the first bucket area meet all restrictions. If a feasible interval cannot be found between SDESI 1 5 82 and EDESI 1 5 84, the order cannot be included in the schedule. 200305088

(98) Decisions for inclusion in the schedule control of orders are usually based on user preference. For example, to reduce storage costs, many manufacturers prefer the UIT method. Another is that some users will use more than one type of control depending on the situation. At step 1 5 1 6 (Figure 1 5 A), a search for a feasible bucket interval is made. Once the schedule control for the order has been determined, the feasible barrel interval for placing orders can be determined based on the schedule control and other factors such as resource constraints mentioned above. Only after determining the feasibility of all restrictions (capacity and available ancillary), the ABP system 100 will place the order in the barrel section. The search action can be guided by a schedule control for the order. When there are many mechanisms that can be used to search for all barrel-like intervals included in the schedule interval, the mechanism used should mainly emphasize speed. The basic principles behind this method are as follows. Resource capacity limits are used as "fixed limits" in the search mechanism. It can be assumed that the capacity is limited to all limits with the smallest graininess. The procedure starts by checking the capacity in the desired bucket interval on the capacity limit. Many rules can determine which bucket intervals will be the desired bucket intervals. If sufficient capacity is available in the desired bucket interval, the first ancillary limit is checked again for feasibility (eg, movement across the limit may be referred to as "vertical movement"). If sufficient capacity is available for the first auxiliary limit, "vertical movement" can be used for the second auxiliary limit. Similarly, if sufficient capacity is available for the second subsidiary restriction, vertical movement can be used for the third subsidiary restriction. These vertical movement steps will then of course continue to repeat other ancillary restrictions. If, at any point in time, the limit found is our best -103- 200305088

In the bucket section viewed first, if there is not enough capacity ’, a search will be made to go backward or forward across the bucket section on the limit (depending on the schedule table control and the bucket section viewed). This will not be completed until the barrel interval on the limit of the demand on the order is met. Such a movement across multiple barrel-shaped intervals on a single limit is called a "pepper direction movement". There are various rules that can be used for horizontal / vertical and vertical movement. 2. Whenever there is a lateral movement on the subsidiary limit, in order to find a feasible barrel-shaped interval, the capacity limit must be checked again. For example, whenever there is a "lateral movement" on the auxiliary limit, in order to find a feasible bucket interval, it is better that _, the capacity limit will be checked again. Therefore, the system will "vertically move" to the capacity limit, "transversely move" at capacity limit 1 (if necessary), move vertically to the first "affiliate limit", move laterally at the first subsidiary limit} (if necessary), "Abandon straight movement" to the valley limit, if there is "horizontal movement" on the first subsidiary and so on. Banknotes, assuming three restrictions, A, B, and C, 10 bucket intervals, A is always available, B can use bucket intervals 3, 4, 7, 8, 9, 10, and C can use bucket intervals丨, 2, 5, 6, 7, 8, 9, 10, and the material can start with a barrel-shaped interval U. Lu further assumes that he wants to be included in the plan table forward, and that there is no start date of the order. Period. Then, preferably, the system will start checking the limit in the bucket interval 1. In this example, A1 will be checked first, if it is good, it will be vertical, move, and check B 1 and find the problem. Next, check the limits A2 or B2. The ΛBP system 100 will find the next available bucket interval before returning to A and checking A. In this example, it will find that the barrel interval 3 series is available for B, and then it will restart checking A3. In general, if B is more than C -104- 200305088

(100) Restricted, the user's best interest may place restriction B before C. This reduces the number of checks. In essence, search usually includes "vertical movement" across the limit and "horizontal movement" across the barrel-like interval on the limit. The search will continue until one of the two cases is met: 1 · A feasible bucket interval on the capacity limit that satisfies all subsidiary limits will be found. In this example, the order can be placed in the identified feasible bucket interval, and the order placement evaluation step continues. 2. In the search through the entire schedule interval, no single feasible bucket interval was found. In this example, orders cannot be placed on current resources. So the system will try to place the order on the next resource in the list of allowed resources. This would involve the duplication of the feasibility assessment on the next resource. If the current resource is the last resource in the list of allowable resources, the system will leave the resource loop, extract the next SKU from the list of allowable SKUs, and reuse the next SKU from step 408 (FG SKU initial) forward The examples provided below show the above concepts. In this example, an attempt is made to include the order in the plan table on resource R1. This order has the following characteristics: • Effective demand date: 3 days in 6 weeks 200305088 (101)

Included in the schedule control = JIT restrictions used are as follows: • Resource capacity restrictions for resource R 1 • Two subsidiary restrictions (restrictions A and B) Refer to Figure 16 for the purpose of finding out based on the above list A block diagram 1600 of the true representation in the search procedure for an example of the bucketing interval of the satisfactory time and the characteristics and limitations. Figure 1600 contains the day of the week divided by the dividing line

One of the three columns (1 6 2 to 1 6 0 6) between periods ------ ~ Erli P. Good shoulder capacity limit 1 602, and ancillary limit, limit a 16〇4 and limit β 16〇 . Here, the week time period 16 0 7 indicates a barrel-shaped area and eight rooms. The top column 1 60 represents the available quantity (ie, the capacity y,.) In the middle of the weekly capacity limit (as represented by the repertoire within each division line in U). The middle column 1 604 is I does not comply with the limits of each week. A, available, take I (3F, that is, the capacity Θ consideration column 1 606 means that according to the limits of each week B, summer) (that is, capacity). In order to satisfactorily place the order in the available quantity (in this case, the bucket interval is the time of the week, the bucket interval is 1 JW Ιηε), it is necessary to know the sufficient capacity of each limit of the bucket interval . ♦,: ,, 啕 are used in the middle of C: 6 weeks, as indicated by i 6 0 8. There is a long date that falls on 舅 β. 8 weeks to drill w! Watch interval 1 6 1, J,, 々 bundle. Because the column fighting + main ρ system is set to JIT, the system will try to order the date of the dagger watch. Therefore, the search will open To be close, I #, _ ,,. 〇 is in the time bucket interval 162, in which the demand date 1608 will fall among them. "Dagger AS * 5- ^ r 1 \ ^ The mouth is represented by ^ one. ^ Is 玎Earlier miles (= 1) are the same as the available numbers from the field of >> rm (if it is less than 1 620 Φ) according to the capacity limit ^, so it is used for the 6th star during the growing period &lt; grain limit Rongwu is satisfactory. Next, the factory will be made to move J to divider 162

-106-200305088 (102)

. The dividing line 1 6 2 2 indicates the capacity of the limit A in the 6th week. Vertical movement is implemented to determine whether the capacity of limit A is sufficient. In this example, the capacity of the dividing line 1 6 2 2 is zero. Therefore, limiting the capacity of A is not satisfactory, and the system “moves horizontally” to an earlier barrel section to locate a barrel section with sufficient capacity. The time bucket interval used for week 5 is also not satisfactory because the capacity of limit A in week 5 (as shown in divider 1 623) is zero. In this example, the system will find the capacity in the divider line 1624, which means that the capacity of limit A in the 4th week is sufficient. However, because the system must leave the previous bucket interval (also

That is, week 6), so it is a limit), and recheck the capacity of week 4 for capacity limitation. g. From divide line 1 624, the system will move vertically to divide line 1 626, y: Determine whether the capacity limit capacity in the 4th week is sufficient. In this case, there is enough capacity in divider line 1 626 (as indicated by divider line 1 626 the number "1"). Therefore, the system will pass the dividing line 1624 to newly check and judge whether the capacity of the limit A in the 4th week is enough to be generated earlier). The other is that the step of rechecking the capacity of the divider 1624 will be ignored because the capacity of the divider 1624 has been judged to be satisfactory. Then, the system will move vertically to the divider 1 62 8 to determine the Restrict whether the capacity of B is sufficient. Because the capacity in period # 4 of #Limit B is zero ', the system must move to another 4 :: interval in the bottom column. However, the system will not move to the earlier bucket interval because the effective inclusion in the daily meter interval i6i〇 will end at:. So ‘, the item moves to the right or a later time bucket’ and then the system knows

-107- 200305088 (103)

Weeks 5 and 6 (divided lines 1630 and 1632), as it has been found that the capacity to limit A is insufficient in those weeks (as shown by the divided lines 1 622 and 1 62 3). However, it is sufficient to limit the capacity of Week 7 of B, as indicated by the dividing line 1 6 3 4. The system then moves back to the capacity limit to determine if the capacity for capacity limit during the seventh week is sufficient. Divider line 1 636 (which is the capacity used for capacity limitation during Week 7) indicates that the capacity limitation used for this barrel section has zero capacity. As a result, the system moves to the next (later) bucket interval. At divide line 1 63 0, the system will decide that the capacity limit in the eighth week is satisfactory. Therefore, the system moves to the divider line 1640, which indicates the capacity of the capacity limit A in the eighth week, and determines the capacity that has also been satisfied. The system will then move to the divider line 1650, which indicates the capacity limit B in the 8th week and will also find a satisfactory capacity. Therefore, in week 8, all three limits (1 602 to 16 0 6) are satisfactory and the search will end. The rules used to find "want" bucket intervals will also be implemented. The desired barrel interval is the most desired barrel interval. Therefore, in most cases, the first bucket interval will be checked for feasibility (in the above example, it is the bucket interval of the 6th week) ^ The identification of the desired bucket interval will depend on the Many factors of drawing table control. For example, if the inclusion schedule control is ΠT, and if the order has a non-invalid valid demand date as shown above, the desired bucket interval will contain the bucket interval of the effective demand date of the order. If the inclusion schedule control is set to "forward" or the inclusion schedule control is ΠΤ, and the order has no valid demand date, the desired bucket interval will contain the start date of the effective schedule date Bucket interval. most

-108- 200305088

(104) Later, if the listing schedule is controlled backwards, the desired bucket interval will contain a bucket interval that is effectively included in the end date of the schedule interval. In step 416 of FIG. 4, the ABP system ιOO checks the material volume compatibility. This means that the system 100 will recheck the feasibility of configuration / resource bucket opportunities by recursively generating any necessary schedule receipts for the finished product sκυ and its minor items. Receipts are used to order materials for additional steps in the planning process. Preferably, the receipt for the finished SKU should be generated at the beginning of the barrel section where the amount of manufacturing grain has been found. For minor item SKUs, the receipt of T ′ in the schedule should be pushed back based on the delivery time of the parent SKU. For any SKU, if the number of requests in the bucket interval is greater than the maximum period value used for SKU, the receipt listed in the schedule table will be generated for the previous bucket interval. These should be at least one period or a set of periods for the available materials, because the cycle maximum check is done during the material feasibility step. If the min / increase / max rule makes the material infeasible here, then the configuration / resource / barrel interval combination will also be infeasible. In such a case, the system 100 will continue to the next configuration. For any secondary item, if the BOM relationship for the SKU is used, and the secondary item is incorrect during the manufacturing or supplementary sKU 'The configuration is not feasible. The program continues with the next configuration. In step 418, the ABP system 100 will evaluate each bucket interval / resource opportunity for the FG SKU and will select the best bucket interval / resource combination (shown in step 422). This is usually achieved by grading each opportunity and choosing the opportunity with the best rating. Better yet, before starting a true assessment of the bucket interval / resource opportunity -109- 200305088

(105) Multi, ′, and objective functions will be defined. The objective function calculates a vector (or rank) 'whose entry is the rank for the goal of each rank. At each level, the level is the sum of the weights of the levels given by law. A rule table is generated and used to define each of the rules. This table can further define the t 1 value and tolerance for the goals of each level to determine whether two different levels at a given level should be considered equal. Once this table has been established, the resource / bucket interval opportunities can be ranked using a multilevel objective function.

Preferably, the ABP system 100 will incorporate a multi-stage objective function to determine the best placement of Ding Dan. If the ABP system 100 finds multiple opportunities for planning orders, the objective function will be used to measure each opportunity and select the best order. Each opportunity is classified based on each object of the multi-level objective function. The objective function is composed of a set of laws. At least three rules are available late (measurement of planned order to the effective demand date for the order), total month (measurement of how full the barrel-shaped interval on the planned order capacity limit), and shipping by side (in The location of the manufacturing order's resources and the customer's location on the order's shipping costs). The laws that make up a goal can be grouped into levels, or levels. Each law within a level can be weighted. The goal can use one ^ multiple rules. For example, in order to model the commercial implementation of the number of delayed orders, the target rule composed of the rules that are just too late will be one level with a weight of 1-a rule that minimizes the number of delayed orders, and If the order can be composed of a variety of resources, and the late rule for each resource exceeds θ 7-the resource that minimizes the transportation cost will be selected and sent to the customer's location = the same implementation of this commercial implementation has two rules And two grades of 1 and 3 are known to produce -110- (106) 200305088. The regularity is-grade-a rule. Li. This means that when there is a two-tier improvement order that makes the transportation law a level (as specified by the customer, the opportunity is set, if a location can cost what, it will be used. $ Each tolerance) timeline, Regardless of the transportation order requirements, the one with the most other-ten thousand faces will be used, if the two positions can meet the goals defined for each level. The location of the second shipping cost. Tolerance can be used with certainty. If compared: Tolerances for levels are considered equal when comparing goals. For example, the difference between the number of items is lower than the tolerance. If the number is a manufacturing order at one location? The main rule is the transportation cost ', but the late rule will be used to select the best bit cost for the other one. 'The standard is used to calculate each element in the unitary vector. The rank (which is a vector) is the sum of the weights by the rank. The two kinds of direction = are calculated by the uni-level rule. The first-pair of primes will be compared with the element and then the elements will be compared within the tolerance defined by the layer), and next-if they are equal (in this order class. If they are not equal, lower: pair of elements Will compare. Such as this will check the subsequent hierarchy .. ^ prime will be considered better, and not

Once all ^ p ^ _ greedy / original in the acceptable position has been evaluated, and the best resources have been selected for this position, such as .Λ. If there is any in step 424 'Procedure 4 〇〇〇 repeated in other accessible Steps to evaluate each bucket interval / resource opportunity for each of the incense,,, and set. If there is no longer an acceptable position, then the best position / resource / barrel interval opportunity will be selected in step 426, and the order will be assigned to this opportunity in step u. Then at step 43, the program 400 judges whether there are no more orders not listed in the schedule. If there are more unscheduled orders, the next highest unscheduled order will be selected • 111 (107) 200305088

# ， It will repeatedly evaluate and select the best location / resource / barrel interval opportunity for this order Μ # + ^ spoon "order. However, if there are no more orders to plan, the process 400 will end. Now refer to the figure 17 is a block diagram showing an AB system according to a specific embodiment of the present invention. The system} 7 00 may include a computer device, such as a personal electronic workstation, a word server, or any other microprocessor with a microprocessor. Device. The system 1700 may include a database 1701, which may include tables containing temporary tables for unplanned orders: BOM, configuration, orders, and the like, and may include a transportation matrix. System 丨 7 〇〇 will receive input from the user 17 〇2, and will produce planning output. The system 丨 〇〇〇 can include some modules (1 704 to 1 722) 'to provide some functions. For example, the system 1700 can Includes a window management module i 7 〇4 to manage the single window. Module 1 704 can be used to organize and manage the order window. For example, the window management module 1704 will select the order to be placed to Window, and will Those orders in the window are processed in priority order. Then, for planning purposes, they can be used to select the highest priority order. SKU module 1 706 will be used to organize, maintain, process, and manage skus. Similarly, B0M, Configuration and SAD Group Modules 0708 to 17 12) is used to generate, process, and manage BOM, configuration, and sAD groups. Style module 1714 is used to generate and manage styles, which can be accessed through the web Sequence resources, restrictions and business rules, time bucket intervals, and the like. The timing / sequence module 1716 can be used to generate timelines and decision procedures' and to manage shore-time events and time items. The evaluation module 1718 is used To evaluate and select various options' which will rise during the procedure according to the invention to evaluate another configuration

. For example, module 1 7 1 8 evaluates another opportunity, -112- 200305088

(108), and the like. The order module 1720 is used to recheck and make the data in the order comply with the syntax. Based on the above description, those skilled in the art will understand that some other modules 17 2 2 will also be included in the system 1 700. For example, these may include modules for managing and enforcing business rules, search objectives, multi-level objective functions, and the like. Therefore, the program and system according to a specific embodiment of the present invention can be implemented using a combination of software and hardware.

It will be apparent to those skilled in the art that the procedures and systems used to plan the utilization of the network resources of the present invention can make various modifications and changes within the spirit or scope of the present invention. Therefore, it is intended that the present invention cover the modifications and variations of this invention provided within the scope of the appended patent applications and their equivalents. The attached drawings are used to provide a further understanding of the present invention, and are added to and constitute a part of this application. They illustrate specific embodiments of the present invention, and explain the present invention in conjunction with the description. The principle of the invention. The drawing briefly illustrates that FIG. 1 is a block diagram of an example environment in which a system according to a specific embodiment of the present invention can operate; FIG. 2 A is a flowchart of an initialization procedure according to a specific embodiment of the present invention; FIG. 2B is based on A flowchart of a procedure for planning the use of resources to meet demand in a specific embodiment of the present invention; Figure 3 A is a flowchart of the procedure for initial allocation of resettlement; -113- 200305088

(109) Figure 3B is a flowchart of the procedure for processing orders in priority order; Figure 3C is a block diagram showing the relationship between the SAD group, the order and the frozen group table, Figure 4 is about resource planning In order to achieve the requirements as defined in the order flow chart. Figures 5 A to 5 are block diagrams showing an example of a procedure for resource planning to complete an order.

Fig. 51 is a block diagram showing various combinations of order attribute values used for the example order, Fig. 6 is a flowchart for determining the feasibility of the materials; And the time line of demand; Figures 8A to 8C are block diagrams showing a true representation of an exemplary relationship between SAD groups and SKUs in the BOM; Block diagram of example relationships between

Figures 10A and 10B are flowcharts of procedures supplemented by manufacturing; Figures 10C to 10F are block diagrams of BOM groups; Figure 10G is a block diagram of exemplary BOMs; Figure 11 is about purchase by purchase The flow chart of the supplementary process; Figures 1 A to 12 D are timelines of time events of the example; Figure 13 is a flowchart showing the procedure for generating output based on a specific scheme; Figure 1 4 A -114- 200305088 (110) flowchart showing the procedure for generating output based on a specific scheme; Figure 14B is a flowchart about the procedure supplemented by substitution; Figure 1 5A shows that it is feasible to determine restrictions Figure 15B is a flowchart showing the procedure for determining effective inclusion in the schedule table; Figures 15C to 15F are timelines showing various control concepts included in the schedule; Figure 16 is a block diagram showing a true representation of a search procedure for an example of finding a satisfactory time interval; and

FIG. 17 shows the attribute basis of a specific embodiment of the present invention.

Block diagram of the planning system. Schematic representation of symbols 100 ABP system 101 Database 102 Manufacturer 104 Manufacturer 106 Manufacturer 110 Resource 120 Resource 130 Resource 140 Material 350 Block Diagram 352 SAD Group 354 Order 356 Order -115- (111) Order Block Group Table SAD Group SAD Group Order Loc 1 Loc 2 Loc 3 Resources RSh RS 1 2 Quadrant 1 Quadrant 2 Quadrant 3 Quadrant 4 Timeline Inventory Level Demand Date Vertical Line Vertical Line Stock Availability Date D 1 Stock Availability Date Timeline Inventory Level Inventory Availability Date-116- (112) Earliest Acceptable Date Demand Date Timeline Inventory Level Demand Date Demand Quantity Available Inventory Available Date Inventory is Maximum Maximum Latest Acceptable Date Timeline Inventory Level Acceptable Demand over time

Latest acceptable inventory date D4 SAD group secondary item SKU secondary item SKU secondary item SKU SAD group secondary item SKU secondary item SKU SAD group secondary item SKU -117- (113) ( 113)

Minor Item SKU Minor Item SKU Order j Configuration A Configuration B Minor Item SKU Minor Item SKU Minor Item SKU Minor Item SKU Minor Item SKU Minor Item SKU Minor Item SKU Minor Item SKU Timeline Purchase Order Placement Date (POPD) Purchase Order Placement Date plus Latest (POPD + ML) Supplementary Start Date (RSD) Supplementary Demand Date minus Earliest (RND-ME) Supplementary Demand Date (RND) Supplementary Demand Date plus Latest (RND + ML) purchase shipping time or "PLT" barrel interval timeline purchase order placement date (POPD) -118- (114) (114)

Purchase order placement date plus latest (POPD + ML) completion date supplementary demand date plus latest (RND + ML) purchase shipping time or "PLT" timeline timeline replenishment start date (RSD) supplementary demand date minus Go to earliest (RND-ME) purchase order placement date (POPD) purchase order placement date plus latest (POPD + ML) RSD + PLT date RND-ME date RND date bucket interval bucket interval bucket interval timeline is valid Start date (SDESI) for effective schedule date

EDESI timeline

SDESI

EDESI Timeline -119- (115)

SDESI

EDESI timeline

SDESI

The EDESI chart lists the time period during the week. The date will fall in the middle of the 6th week. It is effectively included in the schedule. Barrel interval divider divider divider divider divider divider divider divider divider system database. -120- (116) Window Management Module SKU Module BOM Module Configuration Module SAD Group Module Style Module Timing / Sequence Module Module Evaluation Module Order Module Other Modules • 121-

Claims (1)

200305088 Patent application scope 1. A method of planning the use of supply chain resources to meet the needs as defined by the order, including the following steps: Generate SAD groups, which are defined by attributes and related Based on the orders based on the attributes; Based on the SAD groups, the orders are processed in priority order; Based on the priority of the orders loaded in a window, one or more of the orders are selected Selecting an order from the window; determining a configuration for the selected order; and selecting a resource to complete the selected order selected from the window based on the configurations. 2. The method of claim 1 in the scope of patent application, wherein the step of selecting a resource includes a step of determining whether the resource can be supplemented by purchase. 3. The method according to item 2 of the patent application scope, wherein the step of judging whether the resource can be supplemented by the purchase includes the following steps: determining time items which are related to the order and at least one of which The item is based on a purchase and shipment time of the inventory holding unit with attributes; based on the time events of the time items; generating a timeline that includes the time events and the time items; based on a group of predetermined plans The timeline while choosing an available plan; and 200305088 Based on this available scheme, an output is generated. 4. The method of item 3 of the scope of patent application, wherein the time items further include a purchase order resettlement date, a supplementary start date, a supplementary demand date, one latest, and one earliest, and among which The shipping time is defined as the time required to obtain one of the requested supplementary materials, where the purchase order placement date is defined as the difference between the supplementary demand date and the purchase shipping time. 5. The method of claim 4 in the scope of patent application, wherein the time events further include a date as defined by the purchase order resettlement date and the latest sum. 6. The method of claim 4 in the scope of patent application, wherein the time events further include a date as defined by the date of the supplementary demand minus the difference between the earliest. 7. The method according to item 4 of the patent application, wherein the time events further include a date as defined by the supplementary demand date and the latest sum. 8. The method of claim 4 in the scope of patent application, wherein the time events further include a date as defined by the sum of the supplementary start date and the purchase delay time. 9. The method of claim 4 in the scope of patent application, wherein the time events further include a date as defined by the purchase order placement date minus the difference between the earliest. 10. If the method of claim 4 is applied, the time events further include, for example, the sum of the resettlement date of the purchase order and the latest, the date of the supplementary demand minus the difference between the earliest, the supplement Demand date and 200305088 The date defined by the sum of the latest, the sum of the supplementary start date and the purchase delay time, and the difference between the date of the purchase order placement minus the earliest, where the schemes are based on the time items And the sequence of these time events, and each such scenario is related to a particular output. 1 1. The method according to item 3 of the scope of patent application, in which the output generated is at least one of filling and supplementing is feasible and on time, filling and supplementing is not on time, and supplementation is not feasible. 12. The method according to item 3 of the scope of patent application, further comprising the step of generating a purchase model, wherein the purchase model is modeled by defining a cycle maximum to limit the amount of material that can be generated by a resource during a time period. 1 3. The method according to item 1 of the patent application scope further includes the step of generating a temporary list of unplanned orders to store the unplanned orders in the window. 14. The method of item 1 of the scope of patent application further includes the steps of generating a static model of the resources and using the static model for planning. 1 5. The method according to item 1 of the scope of patent application, further comprising the step of initializing a barrel section. 16 · The method according to item 15 of the scope of patent application, wherein the barrel interval is related to a specific resource and time interval. 1 7 · The method according to item 15 of the scope of patent application, in which the barrel interval is initialized 200305088 18 · The method according to item 15 of the scope of patent application, wherein the step of initializing the barrel section further includes the step of placing subsidiary restrictions. 19. The method according to item 1 of the patent application scope further comprises the step of generating a predetermined configuration table. 2 0. The method of claim 19 in the scope of patent application further includes the step of storing information about the order to be allocated in advance. 2 1. The method according to item 20 of the scope of patent application, further comprising the step of placing a pre-allocation into these bucket-shaped intervals. 22. The method according to item 21 of the scope of patent application, further comprising the step of allocating materials based on the pre-allocation. 2 3. If the method of the first scope of patent application, it also includes loading the configuration and BOM information about the orders placed in the window into the window. 0 24. If the first scope of patent application A method in which the planning and use of resources to complete the selection order from the window is based on the attributes of the selection order from the window. 2 5. A system for planning the use of manufacturing resources in the supply chain to fulfill the requirements as defined by the order, including: a computer device; a database that communicates with the computer device; used to define the order by attributes One module; a module for generating inventory holding units defined by attributes and related to one or more orders through the attributes, a module of attribute definition groups (SAD groups); 200305088 A module for processing the orders based on one or more of the SAD groups in priority order; for selecting one or more of the orders based on the priority of the orders loaded in a window Modules for waiting for orders; a module for selecting an order in the window; a module for determining a configuration for the selected order; and a module for selecting and completing based on the configurations A module from a resource of the selected order in the window. 2 6 · If the system of claim 25 of the patent scope, the module for selecting a resource further includes: used to determine time items, the time items are related to the order, and at least one of these time An item is a module based on a purchase and shipping time of the inventory holding unit (SKU) with attributes; a module used to time events based on the time items; used to generate a timeline that includes the A module for waiting for time events and one of these time items; for selecting a module for an available solution based on the timeline from a group of predetermined scenarios; and for generating one of an output based on the available scenario Module. 27. If the system of claim 26 is applied for, the time items further include a purchase order resettlement date, a supplementary start date, a supplementary demand date, a latest date, and an earliest time, among which the purchase shipment time Is defined as the time required to obtain one of the requested supplementary materials 0 200305088 28. The system according to item 27 of the scope of patent application, wherein the purchase order placement date is defined as the difference between the date of the supplementary demand and the time of purchase and shipment. 29. The system of claim 27, wherein the time events include a date as defined by the purchase order placement date and the latest sum. 30. The system of claim 27, wherein the time events include a date as defined by the date of the supplementary demand minus the difference between the earliest. 3K The system as claimed in item 27 of the patent application, wherein the time events include a date as defined by the supplementary demand date and the latest sum. 3 2. The system of claim 27, wherein the time events include a date as defined by the sum of the supplementary start date and the purchase delay time. 3 3. The system of claim 27, wherein the time events include a date as defined by the purchase order placement date minus the difference between the earliest. 3 4. The system according to item 27 of the scope of patent application, wherein the time events further include, for example, the sum of the resettlement date of the buy order and the latest, the date of the supplementary demand minus the difference between the earliest The date defined by the sum of the supplementary demand date and the latest, the sum of the supplementary start date and the purchase delay time, and the purchase order placement date minus the earliest. 3 5. If the system of the scope of patent application No. 34, where these schemes are based on 200305088 The time items and the order of the time events. 36. The system of claim 35, each of which is related to a specific output. 37. If the system of claim 26 is applied for, the output generated by the system is at least one of filling and supplementing is feasible and punctual, filling cannot be punctual, and supplementation is not feasible. 38. If the system of item 26 of the patent application scope further includes a module for generating a purchase model, wherein the purchase model is modeled by defining a maximum value of a cycle to limit resources available during a time period The amount of material produced. 39. The system of claim 25, wherein the database includes a table of unplanned orders to store the orders in the window. 40. The system of item 25 of the scope of patent application, further comprising a module for generating a static model of these resources. 4 1. The system according to item 25 of the scope of patent application, further comprising a module for initializing bucket-shaped sections, which includes a device for placing a capacity limit on these bucket-shaped sections, and The condition interval is related to a specific resource and time interval. 4 2. The system of claim 25, wherein the database further comprises generating a predetermined configuration table. 43. The system for claim 25 of the Tellurium patent scope further includes a module for loading configuration and BOM data about the orders placed in the window into the window. 44. A machine-readable program storage device that can be explicitly identified by a 200305088 The instruction program executed by the machine is specifically implemented to perform the method steps of planning the use of network resources in the supply chain in order to process and plan the orders in accordance with the priority according to the assigned priority, and to complete it by one or The requirements defined by multiple orders, the method steps include: organizing the orders into groups, the orders have at least two attributes; processing each group in priority order; based on the attributes of each such order , And each order in each such group is processed in priority order; combining each such order with a configuration; and by prioritizing orders with lower priority, planning with higher priority Priority of these orders, each order's priority is based on the priority of each such order within the group itself of each such order and the group among other such groups Its own priority, the planning of each such order is based on the configuration of each such order, and the use of these resources is planned. 4 5. If the program storage device of the 44th scope of the patent application, the step of planning the use of these resources further includes the following steps: selecting one of these resources; judging whether the selection of the supplement of the resource is feasible, and To complete the order completely, the supplementary judgment step further includes the following steps: It is determined that there are time items related to the order, and at least one of these time items is based on a purchase shipment time of the inventory holding unit with attributes; 200305088 Generating a timeline based on the time events of the time items; generating a timeline including the time events and the time items; selecting an available scheme based on the timeline from a group of predetermined schemes; and based on the available scheme, and Produces an output. 46. The program storage device according to item 45 of the patent application, wherein the time items further include a purchase order placement date, a supplementary start date, a supplementary demand date, a latest date, and an earliest date, in which the purchased Delivery time is defined as the time required to obtain one of the requested supplementary materials. 4 7. The program storage device according to item 46 of the patent application scope, wherein the purchase order placement date is defined as a difference between the supplementary demand date and the purchase shipment time. 4 8. The program storage device according to item 46 of the patent application, wherein the time events further include a date as defined by the purchase order resettlement date and the latest sum. 49. The program storage device of claim 46, wherein the time events further include a date as defined by the supplementary demand date minus the difference between the earliest. 50. The program storage device according to item 46 of the patent application, wherein the time events further include a date as defined by the supplementary demand date and the latest sum. 5 1. If the program storage device of the scope of patent application No. 46, in which time 200305088 The inter-event further includes a date as defined by the sum of the supplementary start date and the purchase delay time. 5 2 · The program storage device according to item 46 of the patent application scope, wherein the time events further include a date as defined by the purchase order placement date minus a difference between the earliest. 5 3. The program storage device according to item 46 of the patent application scope, wherein the time events further include a difference between the date of the purchase order and the latest sum, the date of the supplementary demand minus the earliest , The date defined by the sum of the supplementary demand date and the latest, the sum of the supplementary start date and the purchase delay time, and the purchase order placement date minus the earliest value. 54. The program storage device of claim 53, wherein the schemes are based on the time items and the sequence of the time events. 5 5. The program storage device of claim 54, each of which is related to a specific output. 5 6. The program storage device according to item 45 of the patent application, in which the output generated is at least one of filling and supplementing is feasible and on time, filling and supplementing is not timely, and supplementation is not feasible. 57. The program storage device according to item 45 of the scope of patent application, further comprising a module for generating a purchase model, wherein the purchase model is modeled by a defined period maximum to limit a period of time, The amount of material that a resource can produce. 5 8. The program storage device according to item 44 of the scope of patent application, wherein the orders have an attribute regarding the customer type, and the customer type belongs to 200305088 Sex is used to prioritize each order that belongs to one of these groups. 5 9. The program storage device according to item 44 of the scope of patent application, wherein the orders have an attribute regarding the date of demand, and the date of demand is used to place each order belonging to one of the groups according to Priority processing. 60. The program storage device according to item 44 of the scope of patent application, wherein the priority of each order belonging to one of the groups is based on capacity allocation, wherein the capacity allocation is based on one of the order attributes And reserve the resource capacity to one of these orders. 6 1. The program storage device according to item 60 of the patent application, wherein one of the order attributes is a customer identity attribute. 62. For example, the program storage device of the scope of application for patent 44, wherein the priority of each order belonging to one of the groups is based on the material configuration, wherein the material configuration is based on one of the order attributes, The inventory is reserved for one of these orders. 63. For example, the program storage device of the scope of patent application No. 62, wherein one of the order attributes is a customer identity attribute