JP2002366220A - Information processing system and supply chain evaluation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To allow a user planning a supply chain to speedily make his (her) decision. SOLUTION: This information processing system has a plan making part 112 for performing a process considered MRP(material requirements planning), a distribution simulation part 113 for simulating a distribution process with a distribution process model, an MRP master data inputting part 14 for receiving an input of MRP master data 150, etc., needed to perform the process considered MRP, and a distribution process data converting part 18 for generating distribution process data used by the distribution simulation parrot 113 from the MRP master data 150.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an information processing technique for quantitatively evaluating a supply chain from material procurement to customers by simulation.

[0002]

2. Description of the Related Art As one of tools used to evaluate a business connection from a material procurement to a customer, that is, a supply chain, a material requirement plan (Manufacturi) is used.
ng Resource Planning (MRP) is known. FIG.
As shown in (A), this MRP 210
(For example, materials such as parts, intermediate products, products)
The material requirement information 210 indicating how much quantity needs to be supplied is stored in the product production plan (Master Production Plan).
Schedule: MPS), inventory and backlog data 153, order data 151, product bill of material data 152, and other input data. For example, as reference documents relating to this MRP, for example, 500 illustrated MRP terms are selected.
(Nikkan Kogyo Shimbun, published in 1983).

When the same item is handled at a plurality of bases (for example, procurement, manufacturing bases, etc.) in the supply chain, even if the same item is used, attributes such as a lead time and a distribution ratio differ for each base. There is. For this reason, in the planning engine of the actual supply chain simulation system, the planning unit 212 considers the attribute data 154 and 155 of each base, and
The item procurement information 213 for each site is determined on the basis of the calculation result 211. For example, if the part B procurement base is 2
MR if one vendor (Vendorend1, Vendor♯2)
P210 “100 parts B required on February 20” 211
A is determined, the planning engine 212 sends the determination result 211A and two vendors (Vendor # 1, Vendor # 1).
2) Attribute data (for example, procurement lead time, distribution rate, etc.)
"We arrange 40 parts B to one vendor (Vendor # 1) on February 10 and the other vendor (Vendor # 2)
Item procurement information 213A such as "60 parts B will be arranged on February 15".

[0004]

By the way, the response performance of the conventional supply chain simulation system described above is based on the attribute data 154, 155 of each base by the planning engine.
It is reduced by considering. This delays the user's decision.

[0005] Further, the above-mentioned conventional supply chain simulation system further has a physical distribution simulator for simulating physical distribution by using a physical distribution process model. This logistics simulator and planning engine
Although the same type of attribute data and the same type of process data are used as input data, the data format of the input data is not common between the physical distribution simulator and the planning engine. For this reason, it is necessary that attribute data and the like to be input data of both the physical distribution simulator and the planning engine be prepared in two data formats. For this reason, time is required for data preparation, and the user's decision is delayed accordingly.

SUMMARY OF THE INVENTION It is an object of the present invention to provide an information processing system capable of speeding up the decision making of a user who plans a supply chain.

[0007]

According to an embodiment of the present invention, there is provided an information processing system having a logistics simulation unit and a planning unit, wherein the planning and planning unit uses data and logistics used for simulation. When any one of the data used by the simulation means for the simulation is input, the data is converted to the other data not input.

[0008]

Embodiments of the present invention will be described below with reference to the accompanying drawings.

First, the configuration of the information processing system according to the present embodiment will be described with reference to FIG. In the following, general materials used in the production of products will be referred to as parts.

[0010] The information processing system according to the present embodiment comprises:
An information processing device in which a program for realizing a supply chain evaluation process described later and an operation system program are installed from a storage medium (such as a CD-ROM) to a hard disk, and an input device (a keyboard, a mouse, and the like) connected to the information processing device ) And an output device (such as a display device).

With the above hardware configuration and software, the information processing system realizes the following functional configuration for realizing the supply chain evaluation processing. The functional configuration of this information processing system includes a simulation execution unit that simulates production activities at each site and logistics activities between each site using a supply chain model that simulates the connection of operations from material procurement to customers. 11. Evaluation unit 1 for evaluating the simulation execution result
2. A simulation data input unit 13 for receiving inputs of supply chain model proposals 160, 161 and the like, and a process-considered type M described later by the simulation execution unit 11.
MRP master data input unit 14, MRP master data input unit 14 for receiving input of data necessary for execution of RP (MRP master data 150 and planning data 156, which will be described later regarding the current supply chain production plan)
Storage unit 15 for storing input data 150, 156, etc., from the MRP master data 150, an evaluation value output unit 17 for outputting an evaluation result of the evaluation unit 12, and logistics process data relating to a logistics plan of the supply chain. A process data conversion unit 18;

The simulation execution unit 11 includes a planning unit 112 for executing a process-oriented MRP, a logistics simulation unit 113 for simulating a logistics activity (logistics process) between each site in the supply chain by a logistics process model, and a planning. A simulation overall control unit 111 for controlling the unit 112 and the physical distribution simulation unit 113 is included. Here, the process consideration type M
The RP differs from the ordinary MRP described in the section of the prior art in that the material requirement and the item procurement amount for each site are simultaneously calculated. More specifically, as shown in FIG. 2B, the process-considered MRP 230 includes planning data 156, stock / unscheduled data 153, order receiving data 151, product parts list data 152, and the Attribute data 15
4,155 also takes as input data, executes material requirement development based on the input data, and calculates distribution between bases. As a result, immediately from the input data, for example, “100 parts B are required in the in-house warehouse on February 20; one vendor Vendor # 1 arranges 40 parts B on February 10 and the other vendor The required material amount / item procurement information 231 that can be used as it is in the part arranging work for each base, such as “arrange 60 parts B to vendor Vendor # 2 on February 15” 231A, is obtained.

Next, information stored in the storage unit 15 will be described.

The storage unit 15 stores MPR master data 150 and planning data 156 input from the MRP master data input unit 14.

As shown in FIG. 9, business cycle data 900 for each site is stored in the planning data 156. Each business cycle data includes a base name 904,
Material requirement development timing 901, manufacturing instruction timing 902, manufacturing period 903, order arrangement timing 905,
An order target period 902 and an order target item name 907 are included.

On the other hand, the MPR master data 150 includes order data 151, parts table data 152, stock / unscheduled data 153, supply process attribute data 154, and manufacturing / order attribute data 155. These data 15
1, 152, 153, 154, and 155 store the following data.

As shown in FIG. 4, in the order data 151, order information 400 created based on a customer request is stored for each order item on a period basis or year basis. Each order information includes, for example, an order ID 401, an order item name 402, an order manufacturing site name 403, an order shipment date 404, an order item quantity 405, a request order date 40
6, etc. are included. Here, only the order information 400 created according to the actual order is stored in the order data 151, but the order forecast information created based on the demand forecast or the like is also stored as the order information 400 in the order data 151. It may be.

As shown in FIG. 5, the parts table data 152 includes an item name 501, an item name 502 of a component item (child item), and an item name 502 of each child item for each item (product, intermediate product, part). The number 503 and the like are stored. For items having unique information, the information may be further stored in the parts table data 152.

As shown in FIG. 6, the stock / unscheduled data 153 includes inventory items in the warehouse or delivery schedules (purchase arranged).
For each item, an item name 601, a storage base name (warehouse name or the like) 602, and a stock quantity or purchase quantity 603 are stored, respectively. For the items to be delivered, the date of expected entry to the warehouse 604 and the name of the purchaser base (eg, vendor name) 605 are further stored.

As shown in FIG. 7, in the manufacturing / order attribute data 154, attribute data 700 determined according to the relationship between the item and the base that handles the item is stored for each combination of the item and its handling base. I have. Each attribute data 700 includes, for example, an item name 701, a handling base name 702 for handling (manufacturing, procurement, etc.) of the item, an item handling type (manufacturing, procurement, etc.) 703, a lead time 704 for the handling base name 702, Etc. are stored.

FIG. 8 shows the supply process attribute data 155.
As shown in the figure, attribute data 800 determined according to the relationship between the item to be distributed and the location at which it is carried in / out is stored for each combination of the item and its carrying-in / out location.
Each attribute data 800 includes an item name 801, a destination base name 802, a source base name 803, a distribution ratio of a request from the destination base to the source base (the total amount of the items 801 arranged by the destination base 802 for supply). Of the number of items 801 that the supply destination base 802 supplies to the supply source base 803
804, a transport lead time (not shown) from the source site to the destination site, and the like. For example, supply destination Sh
op01 has Item It in two supplier bases Vender001 and Vender002
If the supply of m201 is arranged in a 7: 3 quantity ratio, 2
Attribute data {item name “Item201” 801, supplier base name “Shop01” 802, supplier base name “Vender001” 803, distribution ratio “70%” 804}, {item name “Item201” 801, supplier base name “Shop01” 802, supplier base name “Vender002” 80
3, the distribution ratio “30%” 804} is stored in the supply process attribute data 155.

Since the data structure of each data shown here is merely an example, appropriate changes such as addition / deletion of data items may be made in accordance with the mounting function of the information processing system.

Further, the storage unit 15 stores supply chain plans 160 and 161 prepared in advance.
The supply chain plans 160 and 161 store basic models and basic modules used to configure the supply chain. Using such a basic model and a basic module, for example, a supply chain model as shown in FIG. 10 is configured. This supply chain model is a model that simulates the processing at each site constituting the supply chain, that is, a logistics process model 1200 that simulates a logistics process from material procurement to product shipment, and a plan that gives ordering instructions and manufacturing instructions to the logistics process. The planning model 1000 includes an order receiving model 1100 that simulates a process of allocating an inventory item present at a manufacturing base to an order from a customer. here,
The logistics process model 1200 includes a procurement base model simulating a material procurement operation, a manufacturing base model simulating a product manufacturing process, a parts transportation model simulating a material transportation operation from a procurement base to a manufacturing base, and a manufacturing base. And a product transport model that simulates a product transport operation from the customer to the customer.
Determined based on the P master data. Further, the manufacturing base model is composed of a combination of an input instruction module, a parts inventory module, a manufacturing process module, and a product inventory module.
Determined based on master data.

Next, the supply chain evaluation processing executed in this information processing system will be described with reference to FIG. Here, it is assumed that the process for realizing each functional component shown in FIG. 1 is in an executable state by starting a program related to the execution of the supply chain evaluation process.

[0025] The user first inputs the data used for the operation of the current supply chain to the MRP master data.
(Order data, parts table data, stock / unscheduled data, supply process attribute data, manufacturing / order attribute data) 150 and planning data. Upon receiving the input of the MRP master data and the planning data, the MRP master data input unit 14 temporarily stores them in the storage unit 15 (S301).

Then, the planning task data of the MRP master data 150 stored in the storage unit 15 is set as a basic model constituting a planning model. Specifically, the planning unit 112 sets the required amount development timing 901 as the MRP execution attribute, sets the production instruction timing 902, the target period 903, the target place 904 as the production instruction attribute, and sets the order arrangement attribute as Order arrangement timing 90
5. The target period 906 and the target item 907 are set.

A logistics process model simulating the logistics process of the supply chain is created from the MRP master data 150 stored in the storage unit 15 (S30).
2). Specifically, the logistics process data conversion unit 18
As described below, based on the MRP master data 150, a combination of a basic model and a basic module constituting a logistics process model is determined, and data is set in the combination to thereby simulate the logistics process of the current supply chain. Generate a process model.

As shown in FIG. 11, the distribution process model includes a procurement base model 1100 and a manufacturing base model 110.
1. Parts transport model 110 connecting between procurement base and manufacturing base
2. It is composed of a product transport model 1102 connecting the manufacturing base and the customer.

The part transport model 1102 is created based on the attribute data 800 of the supply process attribute data 155. Specifically, for each attribute data 800 of the supply process attribute data 155, the item name 801 and the destination / supplier base names 802 and 803 and the transport lead time included in the attribute data 800 are respectively the transport item name and the transport. Parts transport model 1 set as destination / source destination base name and lead time
102 is generated. However, if the attribute data 800 in which the same base name is stored in the supply destination base name 802 and the source base name 803 exists in the supply process attribute data 155, the part transport model corresponding to the attribute data 800 is Not generated. For example, as shown in FIG. 8, the destination base name 802 and the source base name 8
In the case where the same base name “shop01” is stored in “03”, the part transport model corresponding to the attribute data 800 is not generated.

The product transport model 1103 includes the order data 1
It is created based on 51 order information 400. Specifically, for each order information 400 of the order data 151, a product transport model 1103 is generated in which the order item name 401 and the manufacturing base 403 included in the order information 400 are set as the transport item name and the source base name, respectively. Is done. The final customer is set as the destination base name of the transport item of the product transport model 1103 generated here.

The production base model 1101 is generated based on the attribute data 700 of the production / order attribute data 154. Specifically, of the attribute data 700 of the manufacturing / ordering attribute data 154, for each piece of attribute data for which “manufacturing” is set in the handling type 703, the base name 702 included in the attribute data is set. Production base model 1
100 is generated. At this time, if a plurality of attribute data 700 including the same manufacturing base name 702 is stored in the manufacturing / order attribute data 154, a plurality of manufacturing base models 1100 corresponding to the same base are not created. One manufacturing base model 1101 is created for a plurality of attribute data 900. For example, as shown in FIG. 7, the same base name “Sho
If “p01” 702 is stored, the base name “Shop01”
Only one manufacturing base model is generated.

Then, among the storage modules of the manufacturing base model 1101 generated here, the parts inventory module 1101a, the manufacturing process module 1101b, and the product inventory module 110c are generated as follows. If there is a plurality of attribute data 700 including the base name of the manufacturing base model in the manufacturing / order attribute data, the parent-child relationship between a plurality of items included in the attribute data 700 is checked in the BOM data. A production process module 1101b in which the parent-child relationship and the production lead time of each item are set is generated. Also, if there is one or more parts transport models 1102 that use the base name of the manufacturing base model 1100 as the destination base name, the one or more parts transport models 1102
Is created as the inventory item name with the transportation item name included in the component inventory module 1101a. Similarly, if there is a product transport model 1103 that uses the base name of the manufacturing base model 1100 as the source base name, a product inventory module 1101c that uses the transport item names included in the product transport model 1103 as inventory item names Is created.
Then, the corresponding quantity 603 of the stock / unordered data is set as an initial value of the stock quantity of each stock item name included in the component stock module 1101a and the product stock module 1101c.

The procurement site model 1100 is generated based on the storage attribute data 700 of the manufacturing / order attribute data 154. More specifically, among the attribute data 700 of the manufacturing / order attribute data 154, for each attribute data 700 in which “procurement” is stored in the handling type 703, the site name 702 and the base name 702 included in the attribute data are respectively included. Procurement base model 110 in which item name 701 and lead time 704 are set
1 is generated. Here, the point that a plurality of procurement base models 1100 corresponding to the same base are not generated is similar to the case of generating the manufacturing base model 1101.

Using the supply chain model including the logistics process model and other models generated in this way, the simulation executing unit 11 executes a simulation of work at each site in the supply chain.
(S303). Specifically, under the control of the overall simulation control unit 111, the planning unit 112 and the physical distribution simulation unit 113 execute a simulation as described below.

The planning unit 112 calculates the order occurrence date 4 before the date specified by the simulation overall control unit 111.
The order-accepting information 400 including the 06 is taken out of the order-receiving data 151, and the order-accepting information is given to the planning model to execute the process-dependent MRP. As a result, a site-specific plan such as a procurement instruction, a production instruction, or a transportation instruction is calculated for each day or every week. Logistics simulation unit 113
Simulates activities (procurement, manufacturing, transportation) at each site by giving instructions based on this site-specific plan to the logistics process model. After that, Planning Dept. 1
Reference numeral 12 denotes order information 400 used for the process-oriented MRP.
Is given to the order receiving model, the allocation instruction for the ordered item is given from the order receiving model to the physical distribution process model. As a result, the stock of the ordered item is allocated.

When an event rises from the planning model at the timing determined by the required quantity development timing 901, the planning unit 112 executes the logistics simulation unit 1.
Data generated during the 13 simulations (stock quantity,
Acquisition of out-of-stock quantity, order receipt date, etc.), and newly create procurement instructions, manufacturing instructions, and transportation instructions. When a new instruction is created in this way, the physical distribution simulation unit 113
Simulates activities (procurement, manufacturing, transportation) at each base by giving these instructions to the logistics process model.

The simulation overall control unit 111 compares the history information of the number of incoming and outgoing items at each site obtained in such a simulation process with simulation results 1
58 is stored in the storage unit 15. The simulation result 158 further includes the number of items in and out at each site.
(Equivalent to the amount of production, procurement, etc.) and the amount of work in process per unit time (corresponding to the amount of work in process or stock at the base) calculated from the number of inputs and outputs.

Based on the simulation result 158, the evaluation processing unit 12 calculates the inventory turnover (required amount / inventory amount for a certain period), out-of-stock, and order fulfillment rate as the current supply chain evaluation index value. The calculation result is stored in the storage unit 15 as the evaluation result data 159. Further, each evaluation index value obtained at this time is compared with the target value of the evaluation index, and the evaluation value indicating the degree of achievement of the target is
It is calculated by an appropriate calculation method according to the type of the evaluation index. The evaluation value thus obtained is also stored in the storage unit 15 as the evaluation result data 159 (S304). Then, the evaluation value output unit 17 outputs the evaluation result data 159 of the storage unit 15 as a file or display data. The user
By referring to it, the current supply chain performance can be easily verified, so that it is possible to quickly examine whether the current supply chain needs to be improved (S305).

As a result, when it is determined that there is no need to improve the current supply chain, the supply chain simulation may be terminated.

On the other hand, if it is determined that the current supply chain needs to be improved, the user can obtain an optimal supply chain by repeating the following processing until a proper evaluation is obtained. First, determine whether the currently set target value needs to be changed.
(S306) Make appropriate changes to the target values as needed
(S307). Thereafter, the user improves the current supply chain plan (S308), and then re-executes the simulation (S302-).

As described above, according to the supply chain evaluation processing according to the present embodiment, the input data to the physical distribution simulation section is generated from the input data to the planning section, so that data having different data formats are prepared. It becomes unnecessary. As a result, the time required for data preparation is reduced, and the user can make a decision to improve the supply chain earlier.

Further, since the planning unit simultaneously calculates the material requirement and the item procurement amount for each site, the time required for the simulation is reduced, and the responsiveness of the system is improved. This also speeds up the decision of the user.

In the above description, the input data to the physical distribution simulation unit is generated from the input data to the planning unit. On the contrary, the input data to the physical distribution simulation unit is generated from the input data to the planning unit. It is also possible to generate input data. For example, when the supply chain improvement plan is defined in S308, the following S30
2, the reverse process to the above-mentioned case, that is, S30
The process of generating the supply process attribute data 154 and the manufacturing / order attribute data 155 from the physical distribution process model created in Step 8 may be executed.

[0044]

According to the present invention, decision making for improving the supply chain can be speeded up.

[Brief description of the drawings]

FIG. 1 is a functional configuration diagram of an information processing system according to an embodiment of the present invention.

FIG. 2 is a diagram for explaining a difference between an MRP and a process-oriented MRP.

FIG. 3 is a flowchart of a supply chain evaluation process according to an embodiment of the present invention.

FIG. 4 is a diagram showing an example of a data structure of order data.

FIG. 5 is a diagram showing an example of a data structure of parts table data.

FIG. 6 is a diagram showing an example of a data structure of stock / unscheduled data.

FIG. 7 is a diagram showing an example of a data structure of manufacturing / order attribute data.

FIG. 8 is a diagram illustrating an example of a data structure of supply process attribute data.

FIG. 9 is a diagram showing an example of a data structure of planning data.

FIG. 10 is a diagram conceptually showing a configuration of a supply chain model.

FIG. 11 is a diagram conceptually showing a configuration of a physical distribution process model.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 11 ... Simulation execution part 12 ... Evaluation part 13 ... Simulation data input / output part 14 ... MRP master data input part 15 ... Storage part 17 ... Evaluation value output part 18 ... Data conversion part 111 ... Simulation whole control part 112 ... Plan planning part 113 ... Distribution simulation part 131 ... Evaluation method setting interface 132 ... Supply chain plan definition interface 133 ... Result display interface

Continuation of the front page (72) Inventor Manabu Naganuma 292 Yoshida-cho, Totsuka-ku, Yokohama-shi, Kanagawa Prefecture F-term in Hitachi, Ltd. Production Technology Research Laboratory F-term (reference) 3C100 AA05 AA65 BB01 BB36 BB38 BB39

Claims (4)

[Claims] 1. An information processing system for simulating activities at a series of bases constituting a supply chain from material procurement to product sales, wherein the data is associated with the production plan of the supply chain and the data is produced in accordance with the production plan. Planning means for simulating production activities at each of the bases; and logistics simulation means for simulating logistics activities between the bases according to the logistics plan from data related to the logistics plan of the supply chain. An input receiving unit that receives any one of data used for the simulation by the planning and planning unit and a data used for the simulation by the distribution simulation unit; and the input unit receives the data received by the input receiving unit. The other who did not accept An information processing system comprising: a data conversion unit that converts data into the data; and an output unit that outputs simulation results of the planning unit and the physical distribution simulation unit. 2. A supply chain evaluation method for causing an information processing system to execute a supply chain evaluation process from material procurement to product sales, wherein the evaluation process includes a production plan of the supply chain and a logistics of the supply chain. An input receiving process for receiving an input of data related to any one of the plans; and a data conversion process for converting data input in the input receiving process to the other data not input in the input receiving process; Among the data received in the input receiving process and the data generated by the conversion of the data conversion process, the data related to the production plan of the supply chain is used to calculate the production activity at each of the bases according to the production plan. Of the supply chain logistics The data related to the image includes a simulation process of simulating a logistics activity between the bases according to the logistics plan, and an output process of outputting a result of the simulation in the simulation process. And supply chain evaluation method. 3. A program for causing an information processing system to execute an evaluation process of a supply chain from material procurement to product sales, the program being executed by the information processing system to relate to a supply chain production plan. From data, planning means for simulating production activities at each of the bases in accordance with the production plan; and logistics activities between the bases in accordance with the logistics plan from data related to the logistics plan of the supply chain. Logistics simulation means for simulating data, input receiving means for receiving any one of data used for simulation by the planning and planning means and data used for simulation by the physical distribution simulation means, and input receiving means for receiving the data. The data , The program characterized a data conversion means for converting the other data which the input unit is not accepted, an output means for outputting a simulation result of the planning unit and the distribution simulation means, that function as. 4. A machine-readable storage medium storing a program for causing an information processing system to execute a supply chain evaluation process from material procurement to product sales, wherein the evaluation process includes the production of the supply chain. An input receiving process for receiving an input of data relating to one of a logistics plan and a logistics plan of the supply chain; and converting the data input in the input receiving process to the other data not input in the input receiving process. Data conversion processing, and among the data received by the input reception processing and the data generated by the conversion of the data conversion processing, the data related to the production plan of the supply chain is in accordance with the production plan. Simulate production activities at each of the bases, From the data related to the logistics plan of the supply chain, a simulation process for simulating the logistics activity between the bases according to the logistics plan, and an output process for outputting a result of the simulation in the simulation process are included. A storage medium characterized by being stored.