CN111489048A - Method and system for matching requirements and productivity of shoe manufacturing enterprise - Google Patents
Method and system for matching requirements and productivity of shoe manufacturing enterprise Download PDFInfo
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Abstract
The invention discloses a method for matching the requirements and productivity of a shoe manufacturing enterprise, which comprises the following steps: s11, receiving data information related to the order in real time; s12, operating and screening the received order data information to obtain a list of orders to be processed; s13, ordering the orders in the obtained list of the orders to be processed based on a rule engine; s14, judging whether the money number production line of each ordered order is empty or not, and if not, executing a step S15; s15, judging whether the delivery period of each ordered order is reasonable or not, if so, executing a step S16; s16, carrying out demand and capacity matching calculation engine operation on each ordered order to obtain a demand and capacity matching plan; s17, selecting a proper matching plan according to the obtained demand and capacity matching plan to obtain a production line capacity table of the order; and S18, executing a corresponding order process according to the obtained production line capacity table.
Description
Technical Field
The invention relates to the technical field of shoemaking, in particular to a method and a system for matching requirements and productivity of a shoe manufacturing enterprise.
Background
For the dominant industry in the process of transformation upgrading, the greater the available market capacity, the easier it is to create economies of scale, and the more transformation upgrading and technological advancement efforts can gain sufficient additional capital and human input. The trend of purchasing and large-scale production among enterprises is aggravated by the shoe manufacturing enterprise of the first echelon in China due to the support of capital and policies, the calculation logic of matching the demand with the capacity is simple because the supply of the capacity side of the enterprise is single (the own factory) in the prior art, the work of matching the demand with the capacity of most of the enterprises is processed by production management personnel by using Excel, and the operation is finished in sections outside the system, so that the data continuity is poor, the timeliness of the work communication of all departments is poor, and the capacity balance is not ideal. In addition, with the increase of the expert grade production lines which are taken over and built by enterprises, the complexity of the problems facing the shoe manufacturing enterprises on the side of matching the requirements with the products is increased exponentially.
For example, patent with publication number CN105427021A discloses an intelligent clothing scheduling method, which includes: stage 1, order model building stage; the stage is mainly used for constructing an order model and determining orders needing to enter a scheduling stage; and 2, establishing a scheduling model. The stage is mainly used for constructing a scheduling model, completing the scheduling according to the material allocation condition, the field production condition and the order task condition, and selecting a reasonable processing production line for the order; stage 3, determining a production scheduling scheme; acquiring the information of the ongoing processing tasks on the field production line, the processing data of workers, the type of equipment and the use state information of the equipment in real time, and updating an order task scheduling scheme; meanwhile, emergency situations such as equipment failure of the production line, order task addition or reduction and the like are dealt with, the processing situation of each order task on the production line after the scheduling is further analyzed, and a detailed order task scheduling scheme is generated. Although it does not require manual calculations of production line capacity and efficiency, etc., and it can ensure that each task completes a predetermined number of tasks within its respective delivery time limit. However, the above patent is implemented by encoding the ordering policy determined in advance by the user, and the ordering policy is not easily adjusted. Therefore, the invention provides a method and a system for matching the requirements and the productivity of a shoe manufacturing enterprise, which integrates the sequencing strategy conventionally used by a user into a rule engine and facilitates the selection of the client. In addition, the user can also carry out sequencing strategy formulation on the order to be sequenced based on the rule engine, and the flexibility is high.
Disclosure of Invention
The invention aims to provide a method and a system for matching requirements and productivity of shoe manufacturing enterprises aiming at the defects of the prior art, which can make a daily plan for matching the requirements and the productivity by aiming at optimization of the shoe manufacturing enterprises under the constraint conditions of financial cost, productivity, requirements and the like, and guide production managers to purchase raw materials, commission and the like.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for matching the requirement and the productivity of a shoe manufacturing enterprise comprises the following steps:
s1, receiving data information related to an order in real time;
s2, operating and screening the received order data information to obtain a list of orders to be processed;
s3, ordering the orders in the obtained list of the orders to be processed based on a rule engine;
s4, judging whether the money production line of each ordered order is empty, if so, matching the money production line corresponding to the order, and executing the step S2 again; if not, go to step S5;
s5, judging whether the delivery period of each ordered order is reasonable or not, if not, modifying the delivery period of the ordered order, and executing the step S2 again; if yes, go to step S6;
s6, carrying out demand and capacity matching calculation engine operation on each ordered order to obtain a demand and capacity matching plan;
s7, selecting a proper matching plan according to the obtained demand and capacity matching plan to obtain a production line capacity table of the order;
and S8, executing a corresponding order process according to the obtained production line capacity table.
Further, step S1 is preceded by:
s0. presetting the management information of the money production line, algorithm parameter, client priority and production capacity production line corresponding to the order.
Further, the rule engine in step S3 sorts the selected sorting conditions and the designated sorting conditions; the sorting conditions comprise delivery period sorting, head order/supplementary order/key order sorting, client priority sorting and custom sorting.
Further, the step S6 specifically includes:
s61, selecting a forward or backward mode for orders of the co-production line to construct an initial solution;
s62, designing a deletion operator and an insertion operator based on constraint conditions;
s63, circularly solving the designed deletion operator and insertion operator;
s64, judging whether the circulation is finished or not, and if so, obtaining a plan for matching the demand with the capacity.
Further, the deletion operator and the insertion operator are designed in the step S62 and implemented by adopting an A L NS algorithm framework, and the loop solution in the step S63 is implemented based on a small top heap.
Correspondingly, a system for matching the requirements and the productivity of a shoe manufacturing enterprise is also provided, which comprises:
the receiving module is used for receiving data information related to the order in real time;
the screening module is used for operating and screening the received order data information to obtain a list of orders to be processed;
the ordering module is used for ordering the orders in the obtained list of the orders to be processed based on a rule engine;
the first judgment module is used for judging whether the money number production line of each ordered order is empty or not;
the second judgment module is used for judging whether the delivery period of each ordered order is reasonable or not;
the calculation module is used for carrying out demand and capacity matching calculation engine operation on each ordered order to obtain a demand and capacity matching plan;
the selection module is used for selecting a proper matching plan according to the obtained demand and capacity matching plan to obtain a production line capacity table of the order;
and the execution module is used for executing the corresponding order process according to the obtained production line capacity table.
Further, the method also comprises the following steps:
and the preset module is used for presetting the management information of the money number production line, the algorithm parameter, the client priority and the production capacity production line corresponding to the order.
Further, the rule engine in the sorting module sorts by the selected sorting conditions and by the designated sorting conditions; the sorting conditions comprise delivery period sorting, head order/supplementary order/key order sorting, client priority sorting and custom sorting.
Further, the calculation module specifically includes:
the construction module is used for constructing an initial solution in a forward or backward mode for the order of the co-production line;
the design module is used for designing a deletion operator and an insertion operator based on the constraint conditions;
the loop module is used for circularly solving the designed deletion operator and the insertion operator;
and the third judgment module is used for judging whether the circulation is finished or not, and if so, obtaining a plan for matching the demand with the capacity.
Furthermore, the deletion operator and the insertion operator are designed in the design module and realized by adopting an A L NS algorithm framework, and the loop solution in the loop module is realized based on the small top heap.
Compared with the prior art, the method combines a rule engine and a forward or backward strategy to form an initial solution construction module, superimposes special constraint conditions in the shoe manufacturing process on the basis of the design of an A L NS algorithm framework for deleting and inserting operators conventionally, finishes the operator design strongly related to a business scene, introduces a small top stack and always keeps the solver algorithm of the optimal K solutions in the iteration process.
Drawings
FIG. 1 is a flowchart of a method for matching shoe manufacturing enterprise demand with productivity according to one embodiment;
FIG. 2 is a flowchart of a method for matching shoe manufacturing enterprise demand with productivity according to one embodiment;
FIG. 3 is a flow chart of an embodiment for providing a productivity matching based on a rules engine and A L SN algorithm framework;
FIG. 4 is a block diagram of a system for matching shoe manufacturing enterprise requirements with productivity according to the second embodiment.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
The invention aims to provide a method and a system for matching requirements and productivity of a shoe manufacturing enterprise aiming at the defects of the prior art.
Matched in-order capacity of shoe manufacturing enterpriseThe planning generally follows two major principles, namely customer demand priority and production line balance priority, the two major principles respectively correspond to two indexes, namely a delivery period satisfaction rate α and a production line load balance rate β, and different weights w are set for the two indexesiThen the optimization goal of the whole algorithm can be expressed as: obj ═ w1*α+w2β the method for matching demand with capacity of this embodiment is a heuristic, adaptive algorithm with the optimization goal of the weight wiAfter specification, the adjustment of how to predict the delivery period through the order maximizes the value of the objective function obj.
Example one
The present embodiment provides a method for matching the requirement and the productivity of a shoe manufacturing enterprise, as shown in fig. 1 to 3, comprising the steps of:
s11, receiving data information related to the order in real time;
s12, operating and screening the received order data information to obtain a list of orders to be processed;
s13, ordering the orders in the obtained list of the orders to be processed based on a rule engine;
s14, judging whether the money production line of each ordered order is empty, if so, matching the money production line corresponding to the order, and executing the step S12 again; if not, go to step S15;
s15, judging whether the delivery period of each ordered order is reasonable or not, if not, modifying the delivery period of the ordered order, and executing the step S12 again; if yes, go to step S16;
s16, carrying out demand and capacity matching calculation engine operation on each ordered order to obtain a demand and capacity matching plan;
s17, selecting a proper matching plan according to the obtained demand and capacity matching plan to obtain a production line capacity table of the order;
and S18, executing a corresponding order process according to the obtained production line capacity table.
In this embodiment, it is necessary to make a daily plan of matching the demand with the productivity and guide the production manager to purchase and commission raw materials, etc. with the optimization of the footwear manufacturing enterprise level as a target under the constraint conditions of financial cost, productivity, demand, etc.
In this embodiment, the method further includes step s10, presetting management information of the money number production line, the algorithm parameter, the client priority, and the production capacity production line corresponding to the order.
The money production line corresponding to the order comprises a money outsourcing relation, a money production line relation and the like; the algorithm parameters comprise an order default delivery period, a production basic preparation period, a batch window period, a single-day maximum and minimum batch, production cycle configuration and the like; the production line management comprises the steps of pre-allocation estimation, capacity reservation, automatic capacity occupation under a synchronous list arranging state and the like.
In step S11, data information related to the order is received in real time.
In this embodiment, an order received within a certain time is received and data information related to the order is acquired. The data information includes order type, customer name, order time, etc.
In step S12, the received order data information is operated and filtered to obtain a list of orders to be processed.
And screening the received orders through corresponding data to obtain a list of the orders to be processed.
In step S13, the orders in the obtained list of pending orders are sorted based on a rules engine.
A rules engine based order ordering module:
the rule engine sorts the selected sorting conditions and the appointed sorting conditions; the sorting conditions comprise delivery period sorting, head order/supplementary order/key order sorting, client priority sorting and user-defined sorting
Ordering the orders based on a rule engine, wherein the orders are in a position of starting and ending in the whole process, and on one hand, the module operates on an order set to be planned after being screened by a client; on the other hand, the output of the module can be used as the direct input of the initial solution greedy constructed by the initial solution module, and the initial solution construction module only needs to adopt a forward or backward strategy to sequentially process the ordered orders.
The rule engine module provides great convenience for the customers to frequently adjust the initial ordering of the orders, and production managers of shoe manufacturing enterprises can select ordering conditions by self based on the rule engine module, such as: sorting according to forward sequence of delivery time, sorting according to descending order of client priority, and the like. In addition, the sorting rule can be customized, and the previous rules can be combined in a hierarchy, such as: and sorting according to the forward sequence of the delivery time, and if the delivery time is consistent, sorting according to the descending sequence of the priority of the client.
The rule engine module not only provides convenience for production management personnel, but also can greatly improve the research and development efficiency of product research and development personnel, cannot be deeply sunk into the regular details frequently adjusted by business personnel, and provides a self-service tool for configuration of the business personnel.
In step S14, it is determined whether the money production line of each ordered order is empty, if yes, the money production line corresponding to the order is matched, and step S12 is executed again; if not, step S15 is executed.
After the orders in the order list are sorted, a demand and capacity matching process is triggered, and then it is required to determine whether a money number production line of each order is empty, if yes, corresponding information is inquired in a preset money number production line, a default relationship between the money number and the production line is set, and step S12 is executed again.
In step S15, determining whether the delivery date of each ordered order is reasonable, if not, modifying the delivery date of the ordered order, and re-executing step S12; if yes, go to step S6.
And judging whether the delivery period of each order in the order list is reasonable, if not, prompting to modify the delivery period, modifying the delivery period of the order by the user, and executing the step S12 again.
In step S16, the sorted orders are processed by a demand and capacity matching calculation engine to obtain a demand and capacity matching plan.
The method specifically comprises the following steps:
s161, selecting a forward or backward mode for orders of the co-production line to construct an initial solution;
constructing an initial solution module based on a forward or reverse strategy
The module takes an order set with a certain sequence output by a rule engine module as direct input, and takes a forward or backward strategy which is common in the field of scheduling and production as a guide to construct an initial solution, namely, orders to be planned are arranged on different production lines for a certain period of time according to constraint conditions to produce. The advantages and disadvantages of the forward and reverse strategies are as follows:
the positive advantage is that the equipment and people can be fully utilized, and after the production tasks are completed, such as equipment idle or personnel rest, the production tasks can be completed in advance, and the goods cannot be delivered without the delivery date, so that the stocks can be formed.
The advantages and disadvantages of the inverted rows are in contrast, where tasks are completed by the deadline, inventory is minimized, but personnel and equipment may be left idle in the early stages.
The present embodiment allows a production manager to specify either a forward or reverse strategy to generate an initial solution, with the choice of both types of strategies differentiated at the interface by configurable parameters.
S162, designing a deletion operator and an insertion operator based on constraint conditions, wherein the deletion operator and the insertion operator are designed by adopting an A L NS algorithm framework;
designing deletion and insertion operators based on constraint conditions:
the a L NS algorithm framework has a more conventional design mode of deleting or inserting operators, such as:
and (3) deleting an operator:
(1) and (3) randomly deleting an operator: randomly selecting M orders to delete;
(2) the worst deletion operator: according to Δ f-iGreedily deleting M orders;
f' (x, i) represents: cost after order i is deleted, i.e. the size of target value obj
Δf-i＝f(x)-f′(x，i)＝Savingsi+Savingsi+n
Savingsi＝cost(i-1，i)+cost(i，i+1)-cost(i-1，i+1)
An insertion operator:
(1) optimal insertion: insert orders greedily with minimum increase according to cost value;
(2) unfortunately, the insertion: when each order i is inserted, greedy insertion is carried out according to the difference (ascending order) between the suboptimal insertion cost and the optimal insertion cost of the order, namely:
i：＝argmax(Δfi 2-fi 1)
the embodiment superimposes more constraints on the basis of the conventional deletion and insertion operators, such as: whether the delete and insert operators can adjust the production line of the order, allow order deferral, etc.
S163, circularly solving the designed deletion operator and insertion operator; wherein, the circular solution is realized based on the small top heap;
an algorithm loop solving module:
the algorithm loop solving module comprises the steps of operator selection, local search (operator deletion and operator insertion execution), objective function evaluation and solution receiving rules, termination condition judgment and the like, and the approximate flow is as follows:
(1) make the initial solution as the current solution and add the solution to the small heap (Scale K)
(2) Start of cycle
(3) Randomly selecting a pre-designed deletion operator and insertion operator by roulette method
(4) Using the current deleting operator to destroy the current solution, and then using the current inserting operator to repair the solution to obtain a new solution
(5) When the new solution meets a certain condition, the new solution is accepted as the current solution, and the small top heap is updated
(6) If the new solution is better than the historical optimum, recording it as historical optimum, and updating the small top heap
(7) Cycling until a termination condition is met
(8) Yield matching scheme with optimal output history
The optimal K solutions generated in the iterative process are always maintained in the small top heap.
S164, judging whether the circulation is finished or not, and if so, obtaining a plan for matching the demand with the capacity.
In step S17, a suitable matching plan is selected according to the obtained demand and capacity matching plan, and a production line capacity table of the order is obtained.
And obtaining a proper matching plan by manually selecting the obtained demand and capacity matching plan, wherein the manual selection result comprises display indexes: order delivery period achievement rate and production line idle rate; recommending a result; the output detail can be viewed.
And after manual selection, outputting the delivery time of which the demand is matched with the expected capacity, updating the state of the order to be matched with the capacity, obtaining a production line capacity table of the order, outputting capacity occupation summary, outputting capacity occupation and automatically refreshing the capacity table.
In step S18, a corresponding order process is executed according to the obtained production line capacity table.
Compared with the prior art, the method combines a rule engine and a forward or backward strategy to form an initial solution construction module, superimposes special constraint conditions in the shoe manufacturing process on the basis of the design of an A L NS algorithm framework for deleting and inserting operators conventionally, finishes the operator design strongly related to a business scene, introduces a small top stack and always keeps the solver algorithm of the optimal K solutions in the iteration process.
Example two
The present embodiment provides a system for matching the requirement and the productivity of a shoe manufacturing enterprise, as shown in fig. 4, including:
the receiving module 11 is used for receiving data information related to the order in real time;
the screening module 12 is configured to operate and screen the received order data information to obtain a list of orders to be processed;
a sorting module 13, configured to sort the orders in the obtained to-be-processed order list based on a rule engine;
the first judging module 14 is configured to judge whether a money production line of each ordered order is empty;
the second judging module 15 is used for judging whether the delivery period of each ordered order is reasonable or not;
the calculation module 16 is configured to perform a demand and capacity matching calculation engine operation on each ordered order to obtain a demand and capacity matching plan;
the selection module 17 is configured to select a suitable matching plan according to the obtained demand and capacity matching plan, so as to obtain a production line capacity table of the order;
and the execution module 18 is used for executing a corresponding order process according to the obtained production line capacity table.
Further, the method also comprises the following steps:
and the preset module is used for presetting the management information of the money number production line, the algorithm parameter, the client priority and the production capacity production line corresponding to the order.
Further, the rule engine in the sorting module sorts by the selected sorting conditions and by the designated sorting conditions; the sorting conditions comprise delivery period sorting, head order/supplementary order/key order sorting, client priority sorting and custom sorting.
Further, the calculation module specifically includes:
the construction module is used for constructing an initial solution in a forward or backward mode for the order of the co-production line;
the design module is used for designing a deletion operator and an insertion operator based on the constraint conditions;
the loop module is used for circularly solving the designed deletion operator and the insertion operator;
and the third judgment module is used for judging whether the circulation is finished or not, and if so, obtaining a plan for matching the demand with the capacity.
Furthermore, the deletion operator and the insertion operator are designed in the design module and realized by adopting an A L NS algorithm framework, and the loop solution in the loop module is realized based on the small top heap.
It should be noted that the system for matching the requirement and the productivity of the shoe manufacturing enterprise provided by the embodiment is similar to the embodiment, and will not be described herein again.
Compared with the prior art, the method combines a rule engine and a forward or backward strategy to form an initial solution construction module, superimposes special constraint conditions in the shoe manufacturing process on the basis of the design of an A L NS algorithm framework for deleting and inserting operators conventionally, finishes the operator design strongly related to a business scene, introduces a small top stack and always keeps the solver algorithm of the optimal K solutions in the iteration process.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for matching the requirement and the productivity of a shoe manufacturing enterprise is characterized by comprising the following steps:
s1, receiving data information related to an order in real time;
s2, operating and screening the received order data information to obtain a list of orders to be processed;
s3, ordering the orders in the obtained list of the orders to be processed based on a rule engine;
s4, judging whether the money production line of each ordered order is empty, if so, matching the money production line corresponding to the order, and executing the step S2 again; if not, go to step S5;
s5, judging whether the delivery period of each ordered order is reasonable or not, if not, modifying the delivery period of the ordered order, and executing the step S2 again; if yes, go to step S6;
s6, carrying out demand and capacity matching calculation engine operation on each ordered order to obtain a demand and capacity matching plan;
s7, selecting a proper matching plan according to the obtained demand and capacity matching plan to obtain a production line capacity table of the order;
and S8, executing a corresponding order process according to the obtained production line capacity table.
2. The method of claim 1, wherein the step S1 is preceded by the step of matching the shoe manufacturing enterprise demand with the productivity further comprising:
s0. presetting the management information of the money production line, algorithm parameter, client priority and production capacity production line corresponding to the order.
3. The method as claimed in claim 1, wherein the rules engine of step S3 comprises selecting a sorting criteria for sorting, and assigning a sorting criteria for sorting; the sorting conditions comprise delivery period sorting, head order/supplementary order/key order sorting, client priority sorting and custom sorting.
4. The method as claimed in claim 1, wherein the step S6 comprises:
s61, selecting a forward or backward mode for orders of the co-production line to construct an initial solution;
s62, designing a deletion operator and an insertion operator based on constraint conditions;
s63, circularly solving the designed deletion operator and insertion operator;
s64, judging whether the circulation is finished or not, and if so, obtaining a plan for matching the demand with the capacity.
5. The method of claim 4, wherein the step S62 of designing the delete operator and the insert operator is performed using the A L NS algorithm framework, and the step S63 of performing the loop solving is performed based on the small top heaps.
6. A system for matching shoe manufacturing enterprise demand with productivity, comprising:
the receiving module is used for receiving data information related to the order in real time;
the screening module is used for operating and screening the received order data information to obtain a list of orders to be processed;
the ordering module is used for ordering the orders in the obtained list of the orders to be processed based on a rule engine;
the first judgment module is used for judging whether the money number production line of each ordered order is empty or not;
the second judgment module is used for judging whether the delivery period of each ordered order is reasonable or not;
the calculation module is used for carrying out demand and capacity matching calculation engine operation on each ordered order to obtain a demand and capacity matching plan;
the selection module is used for selecting a proper matching plan according to the obtained demand and capacity matching plan to obtain a production line capacity table of the order;
and the execution module is used for executing the corresponding order process according to the obtained production line capacity table.
7. The system of claim 6, further comprising:
and the preset module is used for presetting the management information of the money number production line, the algorithm parameter, the client priority and the production capacity production line corresponding to the order.
8. The system of claim 6, wherein the rules engine of the order module comprises a selected order condition for ordering, a designated order condition for ordering; the sorting conditions comprise delivery period sorting, head order/supplementary order/key order sorting, client priority sorting and custom sorting.
9. The system of claim 6, wherein the computing module comprises:
the construction module is used for constructing an initial solution in a forward or backward mode for the order of the co-production line;
the design module is used for designing a deletion operator and an insertion operator based on the constraint conditions;
the loop module is used for circularly solving the designed deletion operator and the insertion operator;
and the third judgment module is used for judging whether the circulation is finished or not, and if so, obtaining a plan for matching the demand with the capacity.
10. The system of claim 9, wherein the design module is configured to design delete operators and insert operators using an a L NS algorithm framework, and the loop module is configured to perform the loop solution based on a small top pile.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112396323A (en) * | 2020-11-18 | 2021-02-23 | 广东赛意信息科技有限公司 | Production plan-based process sheet distribution method and system |
| CN112396322A (en) * | 2020-11-18 | 2021-02-23 | 广东赛意信息科技有限公司 | Production plan-based process technology unit productivity assessment method and system |
| CN112561253A (en) * | 2020-11-18 | 2021-03-26 | 广东赛意信息科技有限公司 | Order assignment method, system, platform and storage medium based on production plan |
| CN113361902A (en) * | 2021-06-02 | 2021-09-07 | 汕头市俊国机电科技有限公司 | High-efficiency regulation and control intelligent production scheduling system |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05216889A (en) * | 1991-11-28 | 1993-08-27 | Nec Corp | Automatic scheduling system for printed schedule plan |
| JPH07282140A (en) * | 1994-04-08 | 1995-10-27 | Hitachi Ltd | Production schedule system |
| JP2003256020A (en) * | 2002-03-01 | 2003-09-10 | Jfe Steel Kk | Production plan preparing method for intermediate steel product and steel product, its device, program for realizing method and device, and manufacturing method of intermediate steel product and steel product |
| JP2004110767A (en) * | 2002-09-13 | 2004-04-08 | Kaka Kagi Kofun Yugenkoshi | Scheduling system |
| CN101311952A (en) * | 2007-05-24 | 2008-11-26 | 鸿富锦精密工业（深圳）有限公司 | Production plan reverse scheduling system and method |
| CN104732346A (en) * | 2015-03-23 | 2015-06-24 | 浪潮通用软件有限公司 | Unified finite capacity production scheduling method based on metadata |
| CN104751297A (en) * | 2015-04-20 | 2015-07-01 | 海安县申菱电器制造有限公司 | Productivity allocation method for mixed-model production line |
| CN105389653A (en) * | 2015-10-30 | 2016-03-09 | 广东石油化工学院 | Adaptive material requirement plan (MRP) calculation method |
| CN105741036A (en) * | 2016-01-29 | 2016-07-06 | 苏州浙远自动化工程技术有限公司 | Production scheduling system and method of smart factory of traditional Chinese medicines |
| CN106327058A (en) * | 2016-08-10 | 2017-01-11 | 苏州博众精工科技有限公司 | Intelligent convenient production line scheduling method |
| CN106408112A (en) * | 2016-08-31 | 2017-02-15 | 广州亿澳斯软件股份有限公司 | Production order production scheduling management method and production scheduling optimizer system |
| CN109784531A (en) * | 2018-12-12 | 2019-05-21 | 广州永霸信息科技股份有限公司 | A kind of production plan generates processing method, system, platform and storage medium |
| CN110472829A (en) * | 2019-07-11 | 2019-11-19 | 天津大学 | A kind of method of automatic scheduled production |
| CN110705818A (en) * | 2019-08-15 | 2020-01-17 | 珠海格力电器股份有限公司 | Order scheduling method and device and computer equipment |
-
2020
- 2020-02-18 CN CN202010098816.8A patent/CN111489048A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05216889A (en) * | 1991-11-28 | 1993-08-27 | Nec Corp | Automatic scheduling system for printed schedule plan |
| JPH07282140A (en) * | 1994-04-08 | 1995-10-27 | Hitachi Ltd | Production schedule system |
| JP2003256020A (en) * | 2002-03-01 | 2003-09-10 | Jfe Steel Kk | Production plan preparing method for intermediate steel product and steel product, its device, program for realizing method and device, and manufacturing method of intermediate steel product and steel product |
| JP2004110767A (en) * | 2002-09-13 | 2004-04-08 | Kaka Kagi Kofun Yugenkoshi | Scheduling system |
| CN101311952A (en) * | 2007-05-24 | 2008-11-26 | 鸿富锦精密工业（深圳）有限公司 | Production plan reverse scheduling system and method |
| CN104732346A (en) * | 2015-03-23 | 2015-06-24 | 浪潮通用软件有限公司 | Unified finite capacity production scheduling method based on metadata |
| CN104751297A (en) * | 2015-04-20 | 2015-07-01 | 海安县申菱电器制造有限公司 | Productivity allocation method for mixed-model production line |
| CN105389653A (en) * | 2015-10-30 | 2016-03-09 | 广东石油化工学院 | Adaptive material requirement plan (MRP) calculation method |
| CN105741036A (en) * | 2016-01-29 | 2016-07-06 | 苏州浙远自动化工程技术有限公司 | Production scheduling system and method of smart factory of traditional Chinese medicines |
| CN106327058A (en) * | 2016-08-10 | 2017-01-11 | 苏州博众精工科技有限公司 | Intelligent convenient production line scheduling method |
| CN106408112A (en) * | 2016-08-31 | 2017-02-15 | 广州亿澳斯软件股份有限公司 | Production order production scheduling management method and production scheduling optimizer system |
| CN109784531A (en) * | 2018-12-12 | 2019-05-21 | 广州永霸信息科技股份有限公司 | A kind of production plan generates processing method, system, platform and storage medium |
| CN110472829A (en) * | 2019-07-11 | 2019-11-19 | 天津大学 | A kind of method of automatic scheduled production |
| CN110705818A (en) * | 2019-08-15 | 2020-01-17 | 珠海格力电器股份有限公司 | Order scheduling method and device and computer equipment |
Non-Patent Citations (2)
| Title |
|---|
| 杨毅;李昭原;徐玮;: "高级排产模型及其可配置构件系统设计" * |
| 杨毅;李昭原;徐玮;: "高级排产模型及其可配置构件系统设计", 计算机工程与设计, no. 04 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112396323A (en) * | 2020-11-18 | 2021-02-23 | 广东赛意信息科技有限公司 | Production plan-based process sheet distribution method and system |
| CN112396322A (en) * | 2020-11-18 | 2021-02-23 | 广东赛意信息科技有限公司 | Production plan-based process technology unit productivity assessment method and system |
| CN112561253A (en) * | 2020-11-18 | 2021-03-26 | 广东赛意信息科技有限公司 | Order assignment method, system, platform and storage medium based on production plan |
| CN113361902A (en) * | 2021-06-02 | 2021-09-07 | 汕头市俊国机电科技有限公司 | High-efficiency regulation and control intelligent production scheduling system |
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