Production plan acquisition method and device, computer equipment and storage medium

Abstract

The invention provides a production plan acquisition method and device, computer equipment and a storage medium, and belongs to the technical field of computers. According to the method, a production plan model is obtained according to production data of a production workshop, and then an initial production plan is obtained according to the production plan model. After the initial production plan is simulated, the obtained simulation result reflects the feasibility of the initial production plan, and the production plan model is adjusted according to the simulation result, which means that the initial production plan is adjusted from the source, that is, the related content simulated by the production plan model is adjusted. The feasibility of the production plan obtained according to the adjusted production plan model is improved. Moreover, the production plan is obtained according to the adjusted production plan model, and changes of the production plan corresponding to various products and the influence of the changes on other products are comprehensively considered, so that the production of various products can be completed according to the finally obtained production plan, and the feasibility of the obtained production plan is improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a production plan acquisition method, device, computer equipment and storage medium. Background Art

[0002] As the degree of automation in production workshops continues to increase, some production workshops use computer technology to automatically generate production plans for the production workshops.

[0003] In the process of automatically generating a production plan for a production workshop, after obtaining the production plan, if the execution of the production plan is not ideal, the output of some products in the production plan is adjusted to obtain a new production plan. Since adjusting the output of a certain product in the production plan may affect the production process of other products in the production plan, resulting in other products being unable to be produced according to the production plan, the feasibility of the production plan obtained by the above method is low. Summary of the invention

[0004] The embodiment of the present application provides a production plan acquisition method, device, computer equipment and storage medium for improving the feasibility of production planning. The technical solution is as follows:

[0005] In a first aspect, a method for obtaining a production plan is provided, the method comprising:

[0006] According to the production data of the production workshop, a production planning model is constructed, and the production planning model is used to simulate the cost consumed and the constraints satisfied by the production workshop in the process of producing at least one product;

[0007] According to the production plan model, an initial production plan is obtained, where the production plan includes the output of at least one product on equipment in a corresponding process node in a corresponding period of time, the production process of each product includes at least one process node, and each process node is produced using at least one equipment;

[0008] According to the priority corresponding to each product in the at least one product, according to the initial production plan, the production process of the production workshop is simulated to obtain a simulation result, wherein the priority indicates the production sequence of the products, and the simulation result includes the output and production sequence of the at least one product on the equipment in the corresponding process node in the corresponding time period during the simulation process;

[0009] According to the simulation results, the production planning model is adjusted, and the production plan is obtained according to the adjusted production planning model.

[0010] The production plan acquisition method provided in the embodiment of the present application acquires a production plan model based on the production data of the production workshop, and then acquires the initial production plan based on the production plan model. After simulating the initial production plan, the simulation result obtained reflects the feasibility of the initial production plan. Adjusting the production plan model according to the simulation result is equivalent to adjusting the initial production plan from the root, that is, adjusting the relevant content simulated by the production plan model to improve the feasibility of the production plan acquired according to the adjusted production plan model. In addition, acquiring the production plan according to the adjusted production plan model comprehensively considers the changes in the corresponding production plans of various products and the impact of the changes on other products, so that various products can complete production according to the final production plan, thereby improving the feasibility of the acquired production plan.

[0011] Optionally, the above-mentioned construction of the production planning model according to the production data of the production workshop includes:

[0012] According to the calculation relationship between the production data and cost of the production workshop, the objective function in the production planning model is constructed, and the objective function is used to obtain the cost;

[0013] Construct constraints in the production planning model based on the production data of the production workshop.

[0014] Optionally, the above cost includes extension cost and tangent cost, the extension cost indicates the cost consumed by delayed product delivery, and the tangent cost indicates the cost consumed by switching molds on the equipment. The above objective function in the production planning model constructed based on the calculation relationship between the production data and the cost of the production workshop includes:

[0015] According to the calculation relationship between the production data of the production workshop and the postponement cost and tangent cost, and the corresponding weights of the postponement cost and the tangent cost, the objective function in the production planning model is constructed. The objective function is the weighted sum of the postponement cost and the tangent cost.

[0016] Optionally, the constraints in the above production planning model include at least one of the following: work-in-process balance constraint, mold constraint, production capacity constraint, inventory balance constraint, output constraint, and processing time and work-in-process quantity matching constraint;

[0017] The WIP balance constraint indicates a constraint constructed, for each product of at least one product, based on the relationship between the WIP quantity of the product at each process node and the output of the product;

[0018] The mold constraint indicates a constraint constructed based on the relationship between the number of molds and the products produced by the molds;

[0019] The capacity constraint indicates a constraint constructed according to the maximum capacity of the equipment;

[0020] The inventory balance constraint indicates, for each of at least one of the products, a constraint constructed based on the relationship between the output, inventory, deferral, and demand of the product;

[0021] The yield constraint indicates, for each product of at least one product, a constraint constructed based on a maximum yield and a minimum yield of the product at each process node;

[0022] The processing time and WIP quantity matching constraint indicates a constraint constructed according to a relationship between the WIP quantity of the product at each process node and the process time of the corresponding process node for each product of the at least one product.

[0023] Optionally, the obtaining of the initial production plan according to the production plan model includes:

[0024] Under the constraints simulated by the production planning model, the initial production plan is obtained with the goal of minimizing the cost simulated by the production planning model.

[0025] Optionally, the adjustment of the production planning model includes multiple rounds of iterative adjustment processes. According to the simulation results, the adjustment of the production planning model includes at least one of the following:

[0026] According to the simulation results corresponding to the current round of adjustment process, the parameters in the production plan model adjusted in the previous round are adjusted. The simulation results corresponding to the current round of adjustment process are the simulation results corresponding to the initial production plan corresponding to the current round of adjustment process. The initial production plan corresponding to the current round of adjustment process is the initial production plan obtained according to the production plan model adjusted in the previous round.

[0027] According to the simulation results corresponding to the current round of adjustment process, the constraints in the production plan model after the previous round of adjustment are adjusted.

[0028] Optionally, adjusting the parameters in the production planning model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process includes at least one of the following:

[0029] According to the simulation results corresponding to the current round of adjustment process, the production time in the production plan model after the previous round of adjustment is adjusted, and the production time indicates the length of time consumed in the production process of the product;

[0030] According to the simulation results corresponding to the current round of adjustment process, the equipment parameters in the production plan model after the previous round of adjustment are adjusted.

[0031] Optionally, adjusting the production time in the production plan model after the previous round of adjustment according to the simulation result corresponding to the current round of adjustment process includes:

[0032] According to the lead time corresponding to the product in the simulation result corresponding to the current round of adjustment process and the lead time corresponding to the product in the simulation result corresponding to the previous round of adjustment process, the lead time corresponding to the product in the production plan model after the previous round of adjustment is adjusted, and the lead time indicates the time consumed by the product in the first link of processing;

[0033] According to the waiting time corresponding to the product in the simulation results corresponding to the current round of adjustment process and the waiting time corresponding to the product in the simulation results corresponding to the previous round of adjustment process, adjust the waiting time corresponding to the product in the production plan model after the previous round of adjustment. The waiting time indicates the time consumed by the product from completing the first link to entering the second link. The second link is carried out after the first link.

[0034] Optionally, adjusting the equipment parameters in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process includes:

[0035] According to the equipment capacity in the simulation results corresponding to the current round of adjustment process and the equipment capacity in the initial production plan corresponding to the current round of adjustment process, the equipment capacity coefficient in the production plan model after the previous round of adjustment is adjusted.

[0036] Optionally, adjusting the constraint conditions in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process includes:

[0037] For any equipment in the production workshop, if the capacity of the equipment in the simulation result corresponding to the current round of adjustment process is less than the first capacity, a first constraint condition is added to the production plan model after the previous round of adjustment. The first constraint condition indicates that the capacity of the equipment in the corresponding time period is less than the second capacity corresponding to the time period. The first capacity is related to the initial production plan corresponding to the current round of adjustment process, and the second capacity is related to the simulation result corresponding to the current round of adjustment process.

[0038] For any equipment in the production workshop, if the equipment's production capacity in the simulation results corresponding to the current round of adjustment process is greater than or equal to the third production capacity, a second constraint condition is added to the production plan model corresponding to the previous round of adjustment process. The second constraint condition indicates that the equipment's production capacity in the corresponding time period is greater than or equal to the fourth production capacity corresponding to the time period. The third production capacity is related to the initial production plan corresponding to the current round of adjustment process, and the fourth production capacity is related to the simulation results corresponding to the current round of adjustment process.

[0039] Optionally, the method further comprises at least one of the following:

[0040] According to the simulation result corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process, the second production capacity corresponding to the corresponding time period in the first constraint condition is adjusted;

[0041] According to the simulation result corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process, the fourth production capacity corresponding to the corresponding time period in the second constraint condition is adjusted.

[0042] In a second aspect, a production plan acquisition device is provided, the device comprising:

[0043] A model building module, used to build a production planning model based on the production data of the production workshop, and the production planning model is used to simulate the cost consumed and the constraints satisfied by the production workshop in the process of producing at least one product;

[0044] An initial plan acquisition module is used to acquire an initial production plan according to a production plan model, wherein the production plan includes the output of at least one product on a device in a corresponding process node in a corresponding period of time, the production process of each product includes at least one process node, and each process node is produced using at least one device;

[0045] A simulation module, for simulating the production process of the production workshop according to the priority corresponding to each product of the at least one product and the initial production plan, to obtain a simulation result, wherein the priority indicates the production sequence of the products, and the simulation result includes the output and production sequence of the at least one product on the equipment in the corresponding process node in the corresponding time period during the simulation process;

[0046] The adjustment module is used to adjust the production plan model according to the simulation results, and obtain the production plan according to the adjusted production plan model.

[0047] Optionally, the above model building module includes:

[0048] An objective function building unit is used to build an objective function in a production planning model according to a calculation relationship between production data and costs in a production workshop, and the objective function is used to obtain costs;

[0049] The constraint condition building unit is used to build the constraint conditions in the production plan model according to the production data of the production workshop.

[0050] Optionally, the above cost includes extension cost and tangent cost, the extension cost indicates the cost consumed by delayed product delivery, and the tangent cost indicates the cost consumed by switching molds on the equipment, and the above objective function construction unit is used for:

[0051] According to the calculation relationship between the production data of the production workshop and the postponement cost and tangent cost, and the corresponding weights of the postponement cost and the tangent cost, the objective function in the production planning model is constructed. The objective function is the weighted sum of the postponement cost and the tangent cost.

[0052] Optionally, the constraints in the above production planning model include at least one of the following: work-in-process balance constraint, mold constraint, production capacity constraint, inventory balance constraint, output constraint, and processing time and work-in-process quantity matching constraint;

[0053] The WIP balance constraint indicates a constraint constructed, for each product of at least one product, based on the relationship between the WIP quantity of the product at each process node and the output of the product;

[0054] The mold constraint indicates a constraint constructed based on the relationship between the number of molds and the products produced by the molds;

[0055] The capacity constraint indicates a constraint built according to the maximum capacity of the equipment;

[0056] The inventory balance constraint indicates, for each of at least one of the products, a constraint constructed based on the relationship between the output, inventory, deferral, and demand of the product;

[0057] The yield constraint indicates, for each product of at least one product, a constraint constructed based on a maximum yield and a minimum yield of the product at each process node;

[0058] The processing time and WIP quantity matching constraint indicates a constraint constructed according to a relationship between the WIP quantity of the product at each process node and the process time of the corresponding process node for each product of the at least one product.

[0059] Optionally, the initial plan acquisition module is used to:

[0060] Under the constraints simulated by the production planning model, the initial production plan is obtained with the goal of minimizing the cost simulated by the production planning model.

[0061] Optionally, the adjustment of the production planning model includes multiple rounds of iterative adjustment processes, and the adjustment module includes at least one of the following:

[0062] A parameter adjustment unit, used to adjust the parameters in the production plan model adjusted in the previous round according to the simulation result corresponding to the current round of adjustment process, wherein the simulation result corresponding to the current round of adjustment process is the simulation result corresponding to the initial production plan corresponding to the current round of adjustment process, and the initial production plan corresponding to the current round of adjustment process is the initial production plan obtained according to the production plan model adjusted in the previous round;

[0063] The condition adjustment unit is used to adjust the constraint conditions in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process.

[0064] Optionally, the parameter adjustment unit includes at least one of the following:

[0065] The time adjustment subunit is used to adjust the production time in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process, and the production time indicates the time consumed by the production process of the product;

[0066] The equipment parameter adjustment subunit is used to adjust the equipment parameters in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process.

[0067] Optionally, the time adjustment subunit is used for:

[0068] According to the lead time corresponding to the product in the simulation result corresponding to the current round of adjustment process and the lead time corresponding to the product in the simulation result corresponding to the previous round of adjustment process, the lead time corresponding to the product in the production plan model after the previous round of adjustment is adjusted, and the lead time indicates the time consumed by the product in the first link of processing;

[0069] According to the waiting time corresponding to the product in the simulation results corresponding to the current round of adjustment process and the waiting time corresponding to the product in the simulation results corresponding to the previous round of adjustment process, adjust the waiting time corresponding to the product in the production plan model after the previous round of adjustment. The waiting time indicates the time consumed by the product from completing the first link to entering the second link. The second link is carried out after the first link.

[0070] Optionally, the device parameter adjustment subunit is used to:

[0071] According to the equipment capacity in the simulation results corresponding to the current round of adjustment process and the equipment capacity in the initial production plan corresponding to the current round of adjustment process, the equipment capacity coefficient in the production plan model after the previous round of adjustment is adjusted.

[0072] Optionally, the condition adjustment unit is used to:

[0073] For any equipment in the production workshop, if the capacity of the equipment in the simulation result corresponding to the current round of adjustment process is less than the first capacity, a first constraint condition is added to the production plan model after the previous round of adjustment. The first constraint condition indicates that the capacity of the equipment in the corresponding time period is less than the second capacity corresponding to the time period. The first capacity is related to the initial production plan corresponding to the current round of adjustment process, and the second capacity is related to the simulation result corresponding to the current round of adjustment process.

[0074] For any equipment in the production workshop, if the equipment's production capacity in the simulation results corresponding to the current round of adjustment process is greater than or equal to the third production capacity, a second constraint condition is added to the production plan model corresponding to the previous round of adjustment process. The second constraint condition indicates that the equipment's production capacity in the corresponding time period is greater than or equal to the fourth production capacity corresponding to the time period. The third production capacity is related to the initial production plan corresponding to the current round of adjustment process, and the fourth production capacity is related to the simulation results corresponding to the current round of adjustment process.

[0075] Optionally, the above device further comprises at least one of the following:

[0076] A first constraint adjustment module, used for adjusting the second production capacity corresponding to the corresponding time period in the first constraint condition according to the simulation result corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process;

[0077] The second constraint adjustment module is used to adjust the fourth production capacity corresponding to the corresponding time period in the second constraint condition according to the simulation result corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process.

[0078] In a third aspect, a computer device is provided, comprising a processor and a memory, wherein the memory is used to store at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the operations performed by the production plan acquisition method provided in the first aspect or various optional implementations of the first aspect.

[0079] In a fourth aspect, a computer-readable storage medium is provided, in which at least one computer program is stored. The at least one computer program is loaded and executed by a processor to implement the operations performed by the production plan acquisition method provided in the above-mentioned first aspect or various optional implementations of the first aspect.

[0080] In a fifth aspect, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the operations performed by the production plan acquisition method provided in the above-mentioned first aspect or various optional implementations of the first aspect.

[0081] Based on the implementations provided in the above aspects, this application can also be further combined to provide more implementations. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0083] Figure 1 It is a schematic diagram of an implementation environment of a production plan acquisition method provided in an embodiment of the present application;

[0084] Figure 2 is a flow chart of a production plan acquisition method provided in an embodiment of the present application;

[0085] Figure 3 is a flowchart of another production plan acquisition method provided in an embodiment of the present application;

[0086] Figure 4 It is a schematic diagram of a product production process provided by an embodiment of the present application;

[0087] Figure 5 It is a structural diagram of a production plan acquisition system provided in an embodiment of the present application;

[0088] Figure 6 It is a structural block diagram of a production plan acquisition device provided in an embodiment of the present application;

[0089] Figure 7 It is a structural diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0090] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0091] In this application, the terms "first", "second", etc. are used to distinguish identical or similar items with basically the same effects and functions. It should be understood that there is no logical or temporal dependency between "first", "second", and "nth", nor is there any limitation on quantity and execution order.

[0092] In the present application, the term "at least one" means one or more, and the term "plurality" means two or more.

[0093] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions. For example, the production data involved in this application are all obtained with full authorization.

[0094] The production plan acquisition method provided in the embodiment of the present application can be executed by a computer device. In some embodiments, the computer device is a terminal or a server. The following first takes the computer device as an example of a server to introduce the implementation environment of the production plan acquisition method provided in the embodiment of the present application.

[0095] Figure 1 This is a schematic diagram of the implementation environment of a production plan acquisition method provided in an embodiment of the present application, see Figure 1The implementation environment includes a terminal 101 and a server 102. The terminal 101 and the server 102 can be directly or indirectly connected through a wired network or a wireless network, and this application does not limit this.

[0096] In some embodiments, the terminal 101 is a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, an intelligent voice interaction device, a smart home appliance, a vehicle-mounted terminal, etc., but is not limited thereto. The terminal 101 is installed and runs an application that supports obtaining a production plan. Schematically, the terminal 101 is a terminal used by a user, and the terminal 101 sends a production plan acquisition request to the server 102 through the above application. The production plan acquisition request carries the identification of the production workshop, indicating that the production plan of the production workshop is obtained.

[0097] In some embodiments, the server 102 is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), big data and artificial intelligence platforms. The server 102 is used to provide background services for applications that support obtaining production plans. Schematically, the server 102 receives a production plan acquisition request sent by the terminal 101, obtains the production plan of the production workshop according to the production data of the production workshop indicated by the production plan acquisition request, and returns the production plan to the terminal 101.

[0098] In some embodiments, the implementation environment further includes a database, which is integrated on the server 102, or placed on a cloud or other server. The database is used to store the production data of the production workshop. After receiving the production plan acquisition request, the server 102 acquires the production data of the production workshop from the database according to the identification of the production workshop carried in the production plan acquisition request, and acquires the production plan of the production workshop according to the production data.

[0099] In some embodiments, the server 102 undertakes the main computing work and the terminal 101 undertakes the secondary computing work; or, the server 102 undertakes the secondary computing work and the terminal 101 undertakes the main computing work; or, the server 102 and the terminal 101 adopt a distributed computing architecture to perform collaborative computing.

[0100] Secondly, taking a computer device as a terminal as an example, the implementation environment of the production plan acquisition method provided in the embodiment of the present application is introduced. The terminal can be implemented as various possible implementations of the above-mentioned terminal 101, and an application supporting the acquisition of the production plan is installed and run on the terminal. The terminal obtains the production plan of the production workshop based on the production data of the production workshop through the above-mentioned application.

[0101] Those skilled in the art will appreciate that the number of the above terminals and servers may be more or less. For example, the above terminal may be only one, or the above terminals may be dozens or hundreds, or more. This application does not limit the number and device types of terminals, and the number and device types of servers.

[0102] In some embodiments, the wireless network or wired network described above uses standard communication technology and / or protocols. The network is typically the Internet, but can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a dedicated network or any combination of a virtual private network. In some embodiments, technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data exchanged through the network. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec), etc. can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above data communication technologies.

[0103] The following is a description of the production plan acquisition method provided in the embodiment of the present application. The method can be applied to the above Figure 1 The implementation environment shown. Figure 2 is a flowchart of a production plan acquisition method provided in an embodiment of the present application, such as Figure 2 As shown, the method comprises the following steps:

[0104] 201. The computer equipment constructs a production planning model based on the production data of the production workshop. The production planning model is used to simulate the cost consumed and the constraints satisfied by the production workshop in the process of producing at least one product.

[0105] Among them, the production workshop is used to produce at least one product, for example, the production workshop is used to produce display panels of various models. The production process of each product corresponds to a process route, and each process route includes at least one process node. The process routes of multiple products may overlap, that is, the same equipment may be used to process multiple products during the production process of multiple products. The production data of the production workshop refers to data related to the production of the production workshop, such as the available capacity of the equipment in the production workshop, the products that the equipment can produce, the unit production time of the equipment for a certain product, the type identification of the products produced by the production workshop, and the process route of the products, etc. The following step 301 describes the production data of the production workshop in detail, and the embodiment of this application will not be repeated here.

[0106] The production planning model is a linear programming model, such as a mixed integer programming model. The production planning model simulates the costs consumed by the production workshop in the production process and the constraints satisfied by the production workshop in the production process based on the production data of the production workshop. Among them, there are many costs consumed by the production workshop in the production process, such as the costs incurred by delayed product delivery and the costs caused by equipment switching of the currently produced products, etc., which are not limited in the embodiments of the present application. The constraints satisfied by the production workshop in the production process indicate the restrictions imposed on the production workshop during the production process of the production workshop, for example, the total production capacity of a certain equipment in the production workshop cannot exceed the available production capacity of the equipment, etc. The following step 303 describes the constraints in the production planning model in detail, and the embodiments of the present application will not be repeated here.

[0107] In an embodiment of the present application, a computer device takes the output of at least one product on the equipment in the corresponding process node in the corresponding time period as a variable, and constructs a production planning model based on the production data of the production workshop and the cost consumed by the production workshop in the process of producing the at least one product, the constraints met, and the calculated relationship between the above variables.

[0108] 202. The computer device obtains an initial production plan based on a production plan model. The production plan includes the output of at least one product on equipment in a corresponding process node in a corresponding time period. The production process of each product includes at least one process node, and each process node is produced using at least one device.

[0109] Among them, the production plan of the production workshop is a production plan that integrates multiple dimensions, and the multiple dimensions include product dimension, time period dimension, process node dimension and equipment dimension. From the product dimension, the production plan includes the production plan of at least one product, from the time period dimension, the production plan includes the production plan of at least one time period, from the process node dimension, the production plan includes the production plan of at least one process node, and from the equipment dimension, the production plan includes the production plan of at least one equipment. Accordingly, the production plan that integrates multiple dimensions can be understood as: the production plan includes the production plan of at least one product, and the production plan of each product includes the time period for the production of the product, the process node where the product is located in the time period, and the equipment used by the product at the process node. Alternatively, the production plan that integrates multiple dimensions can be understood as: the production plan includes the production plan of multiple time periods, and the production plan of each time period includes at least one product produced in the time period, the process node where the at least one product is located in the time period, and the equipment used at the process node, and the embodiment of the present application is not limited to this.

[0110] In an embodiment of the present application, a computer device obtains an initial production plan based on the costs and constraints simulated by a production plan model.

[0111] 203. The computer equipment simulates the production process of the production workshop according to the priority corresponding to each product of at least one product and the initial production plan to obtain a simulation result. The priority indicates the production sequence of the products. The simulation result includes the output and production sequence of at least one product on the equipment in the corresponding process node in the corresponding time period during the simulation process.

[0112] The following example is used to illustrate the priority of the above products: if two products are produced using the same equipment in the same period, the product with higher priority will be produced using the equipment first, and the product with lower priority will be produced using the equipment later. The simulation result is the result obtained by simulating the production process according to the initial production plan, including the output and production order of at least one product on the equipment in the corresponding process node in each period obtained through simulation.

[0113] In the embodiment of the present application, the computer device generates multiple production events and the execution order of the multiple production events in the production workshop according to the priority corresponding to each product and the initial production plan. The computer device simulates the production process of the production workshop according to the multiple production events and the execution order of the multiple production events to obtain the simulation results. Among them, a production event indicates the number of products produced by a device on a process node in a period of time.

[0114] 204. The computer device adjusts the production plan model according to the simulation result, and obtains the production plan according to the adjusted production plan model.

[0115] Among them, the simulation results reflect the feasibility of the initial production plan.

[0116] In the embodiment of the present application, the computer device adjusts the production plan model according to the feasibility indicated by the simulation result, such as adding constraints related to feasibility to the production plan model. The computer device then obtains the production plan according to the adjusted production plan model, and can obtain a production plan with higher feasibility.

[0117] The production plan acquisition method provided in the embodiment of the present application acquires a production plan model based on the production data of the production workshop, and then acquires the initial production plan based on the production plan model. After simulating the initial production plan, the simulation result obtained reflects the feasibility of the initial production plan. Adjusting the production plan model according to the simulation result is equivalent to adjusting the initial production plan from the root, that is, adjusting the relevant content simulated by the production plan model to improve the feasibility of the production plan acquired according to the adjusted production plan model. In addition, acquiring the production plan according to the adjusted production plan model comprehensively considers the changes in the corresponding production plans of various products and the impact of the changes on other products, so that various products can complete production according to the final production plan, thereby improving the feasibility of the acquired production plan.

[0118] Above Figure 2 The content shown in the figure illustrates the main process of the production plan acquisition method provided in the embodiment of the present application. Figure 3 , taking a production workshop for producing a variety of products as an example, the detailed process of the method is illustrated. Figure 3 is a flowchart of a production plan acquisition method provided in an embodiment of the present application, such as Figure 3 As shown, the method includes the following steps.

[0119] 301. The computer device obtains the production data of the production workshop in response to the production plan acquisition instruction.

[0120] The production plan acquisition instruction carries the identification of the production workshop, indicating to obtain the production plan of the corresponding production workshop. In some embodiments, the production plan acquisition instruction also carries at least one time period, indicating to obtain the production plan of the corresponding production workshop in the at least one time period. The production data of the production workshop is also called the basic scheduling data, and the production data includes: equipment data, product data, work in process (WIP) data and mold data, etc. These data are described below.

[0121] Equipment data: Equipment data includes the available capacity of each device in the production workshop, the initial state of the equipment, the products produced by the equipment, the unit production time consumed by the equipment to produce the product, and the time consumed by the equipment to switch molds. Among them, the available capacity of the equipment indicates the time the equipment can produce, and the initial state of the equipment indicates the product that the equipment is currently producing. In the case where the equipment is capable of processing multiple products, the molds used by these multiple products on the equipment are the same or different. If the first product and the second product are processed on the equipment in sequence, and the molds used on the equipment are different, then after the equipment completes the processing of the first product and before processing the second product, the equipment must switch the mold on the equipment. The time consumed by the equipment to switch the mold is the time consumed by the switching process.

[0122] Product data: Product data includes the product type identification, the corresponding order delivery date of the product, the product process route, etc. Among them, the product type identification indicates the type of product, and the corresponding order delivery date of the product indicates the delivery deadline of the corresponding order of the product. If the order is not completed after the delivery deadline, the penalty will be paid according to the unfinished output (delayed amount) in the order. The product process route includes the process nodes through which the product is produced and the equipment used by the product at the corresponding process nodes.

[0123] Take the product process route including multiple process nodes as an example. Figure 4 is a schematic diagram of a product production process provided in an embodiment of the present application, Figure 4 Figure 1 shows two process nodes in the product production process, namely process node k and process node k+1. Figure 4 As shown, the production process of the product includes multiple non-bottleneck links and bottleneck links after each non-bottleneck link, and each process node includes a non-bottleneck link and a bottleneck link after the non-bottleneck link. Among them, the non-bottleneck link and the bottleneck link are pre-set, the non-bottleneck link is the link that does not affect the maximum output of the product, the non-bottleneck link has sufficient production capacity to ensure that the bottleneck link runs at full capacity, and the bottleneck link is the link that can affect the maximum output of the product. The time consumed by the product in the production of the non-bottleneck link is the lead time, and the time consumed by the product in the production of the bottleneck link is the processing time. Since the bottleneck link has been running at full capacity, the products processed by the non-bottleneck link may not be able to enter the bottleneck link for processing immediately. These products are called work-in-progress, and the time consumed by the product from completing the processing of the non-bottleneck link to entering the bottleneck link for processing is called waiting time.

[0124] For example, both product a and product b need to be processed through bottleneck link 1. Before bottleneck link 1, the non-bottleneck link corresponding to product a is non-bottleneck link 1, and the non-bottleneck link corresponding to product b is non-bottleneck link 2. Product a completes the processing of non-bottleneck link 1 at time point 1 and enters bottleneck link 1 for processing. Product b completes the processing of non-bottleneck link 2 at time point 2. At this time, bottleneck link 1 is processing product a and cannot immediately process product b. At time point 3, bottleneck link 1 completes the processing of product a. At this time, product b can enter bottleneck link 1 for processing. The time between time point 2 and time point 3 is the waiting time corresponding to product b.

[0125] Work-in-progress data: Work-in-progress data includes the current number of work-in-progress of various products at the corresponding process nodes, which reflects the production status of the product.

[0126] Mold data: Mold data includes the products produced by each mold. The same mold is used to produce one or more products. The equipment in the production workshop cooperates with the mold to produce the corresponding products. Accordingly, in some embodiments, the mold data also includes the correspondence between the mold and the process route or process node.

[0127] In an embodiment of the present application, the computer device responds to the production plan acquisition instruction, and according to the identification of the production workshop carried by the instruction, obtains the production data corresponding to the production workshop from the local or database, that is, reads the data file corresponding to the production workshop.

[0128] 302. The computer device constructs an objective function of a production planning model based on the production data of the production workshop. The production planning model is used to simulate the cost consumed by the production workshop in the process of producing at least one product. The objective function is used to obtain the above cost.

[0129] Among them, the objective function of the production planning model is pre-set, and the objective function corresponds to the optimization objective of the production planning model. The optimization objectives of the production planning model include multiple types, such as the optimization objective is the cost of the production workshop, which includes tangent cost and extension cost, etc. The tangent cost indicates the cost consumed by switching the mold on the equipment, and the extension cost indicates the cost consumed by the delayed delivery of the product. The tangent cost and the extension cost can be expressed in terms of time or amount, and the embodiment of the present application does not limit this. For example, in the case where the tangent cost and the extension cost are expressed in terms of time, the tangent cost is the time consumed by switching the mold, and the extension cost is the time consumed by producing products that cannot be delivered on time. The objective function corresponds to one or more optimization objectives. In the case where the objective function corresponds to one optimization objective, the objective function is used to calculate the optimization objective. In the case where the objective function corresponds to multiple optimization objectives, the objective function is used to calculate the weighted sum of multiple optimization objectives. The embodiment of the present application does not limit the objective function. Taking the optimization objective including tangent cost and extension cost as an example, the objective function is the weighted sum of extension cost and tangent cost, and the objective function is expressed by the following formula (1):

[0130] Objective function = a*tangent cost + b*delay cost (1)

[0131] Wherein, a is used to indicate the weight corresponding to the tangent cost, b is used to indicate the weight corresponding to the extension cost, and a and b are real numbers greater than 0.

[0132] In the embodiment of the present application, the objective function is the weighted sum of the extension cost and the tangent cost. The computer device uses the output of multiple products on the equipment in the corresponding process node in the corresponding period as a variable, and constructs the objective function in the production planning model according to the calculation relationship between the production data of the production workshop and the extension cost, the tangent cost and the above variables, and the weights corresponding to the extension cost and the tangent cost. In the above calculation relationship, the tangent cost is the sum of the tangent costs of each device, the extension cost is the sum of the extension costs of various products, and the tangent cost of a device is the number of mold switching times on the device multiplied by the cost consumed by a single switch. The number of mold switching times is calculated based on the output of the corresponding product. The extension cost of a product is the number of products that failed to be delivered on time multiplied by the cost consumed by the delayed delivery of a single product. The number of products that failed to be delivered on time is calculated based on the output of the product and the number of products required by the order.

[0133] The above-mentioned step 302 is a possible implementation method for a computer device to construct an objective function in a production planning model based on the calculated relationship between the production data of the production workshop and the cost. This implementation method constructs the objective function in the production planning model based on the calculated relationship between the production data of the production workshop and the deferral cost and the tangent cost, and the weights corresponding to the deferral cost and the tangent cost. By introducing weights corresponding to multiple optimization objectives in the objective function, multiple optimization objectives are weighted, which can achieve multiple optimization objectives in the process of obtaining a production plan according to the objective function, thereby improving the effectiveness of the production plan obtained according to the production planning model.

[0134] 303. The computer equipment constructs the constraint conditions of the production planning model based on the production data of the production workshop. The production planning model is used to simulate the constraint conditions satisfied by the production workshop in the process of producing at least one product.

[0135] Among them, the constraints of the production planning model are pre-set. In the embodiment of the present application, the constraints include at least one of the following: work-in-process balance constraints, mold constraints, production capacity constraints, inventory balance constraints, output constraints, and processing time and work-in-process quantity matching constraints. Of course, the production planning model can also include other constraints, which are not limited in the embodiment of the present application. The constraints involved in the embodiment of the present application are described below.

[0136] Work-in-process balance constraint: For each product in at least one product, a constraint is constructed based on the relationship between the number of work-in-process products at each process node and the output of the product. Figure 4 Taking the process shown in the figure as an example, an increase in the output of the product at process node k will increase the number of work-in-progress of the product at process node k+1, and an increase in the output of the product at process node k+1 will reduce the number of work-in-progress of the product at process node k+1. The work-in-progress balance constraint of any product at the corresponding process node in any period of time can be expressed by the following formula (2):

[0137] The number of WIP at a process node = the number of WIP at the process node in the previous period + the output of the previous process node in the previous period – the output of the process node in the previous period (2)

[0138] Mold constraint: The mold constraint of any mold indicates the common relationship of the molds and the number of molds, indicating the constraints constructed based on the relationship between the number of molds and the products produced by the molds. Among them, the common relationship of the mold indicates that multiple products can share the mold. For example, a process node of product a and a process node of product b share mold M. Then the equipment corresponding to mold M can produce both product a and product b. In the process of producing product a and product b, the equipment does not need to consume the equipment's production capacity to switch the molds on the equipment, and no tangent cost will be generated. The number of any mold indicates the maximum number of equipment used to produce the corresponding products of this mold in the same period. For example, if the number of a certain mold is c, then at most c equipment will produce the corresponding products of this mold in the same period, and c is an integer greater than or equal to 0.

[0139] Capacity constraint: The capacity constraint of any equipment indicates the constraint constructed based on the maximum capacity of the equipment in any period of time, such as the maximum capacity of a certain equipment in a day is 24 hours. In the production process of the product, the production of the product and the switching of the molds on the equipment will consume the capacity of the equipment. In any period of time, the capacity constraint of any equipment means that in this period of time, the sum of the capacity consumed by the production of the product using the equipment and the capacity consumed by the mold switching on the equipment is less than or equal to the maximum capacity of the equipment corresponding to the period of time. In the case where the equipment is used to produce multiple products, the capacity consumed by the production of the product using the equipment is the sum of the capacities consumed by the production of multiple products using the equipment, and the capacity consumed by the production of one product is the number of products produced on the equipment multiplied by the unit production time of the product on the equipment. The capacity constraint of the equipment in any period of time can be expressed by the following formula (3):

[0140] The time consumed for product production + the time consumed for mold switching <= the maximum working time of the equipment in this period * the equipment capacity coefficient (3)

[0141] The maximum working time of the equipment in the time period * the equipment capacity coefficient refers to the maximum capacity of the equipment in the time period, and the equipment capacity coefficient indicates the time during which the equipment can work effectively within the maximum working time in the time period.

[0142] Inventory balance constraint: The inventory balance constraint of any product indicates the constraint constructed based on the relationship between the output, inventory, extension and demand of the product. For example, in any period of time, an increase in the output of the product will increase the inventory of the product and reduce the extension of the product. An increase in the demand for the product will reduce the inventory of the product and increase the extension of the product. The inventory balance constraint of any product in the current period can be expressed by the following formula (4):

[0143] Inventory in the previous period - Delay in the previous period + Production in the current period - Demand in the current period = Inventory in the current period - Delay in the current period (4)

[0144] Yield Constraint: The yield constraint of any product indicates the constraint constructed based on the maximum and minimum yields of the product at each process node.

[0145] Processing time and WIP quantity matching constraint: The processing time and WIP quantity matching constraint of any product indicates the constraint constructed according to the relationship between the WIP quantity of the product at each process node and the process time of the corresponding process node. The process time of the process node includes the lead time, waiting time and processing time. The above relationship is explained below: Assume that the sum of the WIP quantity of a certain product (product i) from process node j to the last process node at the current moment is output 1. Since the semi-finished products in the process nodes before process node j will not be completed before the semi-finished products in process node j, the above output 1 is the maximum output corresponding to the completion of the production of the semi-finished products in process node j from the current moment to the last process node. Assume that the sum of the process time of all process nodes from process node j to the last process node of product i is at least t_sum, and the output of product i in the time length of t_sum from the current moment to the end is output 2, then the above processing time and WIP quantity matching constraint is output 2 ≤ output 1.

[0146] Among them, output 1 is the output described from the perspective of the process route, which is calculated based on the number of work-in-progress at each process node, and output 2 is the output described from the perspective of process time, which is calculated based on the process time and the unit production time of the product. Since the output described from the perspective of process time may be affected by various factors such as equipment failure, the output described from the perspective of process time is uncertain and will not exceed the output described from the perspective of the process route.

[0147] The following example illustrates the above constraints: the production process of product i includes process nodes 1 to 4. At the current moment, the sum of the number of work-in-progress of product i in process nodes 2, 3, and 4 is P1, and the sum of the process time of process nodes 2, 3, and 4 is 84 hours. When a time period is 24 hours, the sum of the process time can be divided into 3 time periods and 12 hours. The output of product i in the next 3 time periods and 12 hours is P2, and P2≤P1.

[0148] During the production process of the product, affected by various factors such as equipment failure, the process time of the process node is not certain. It can be 1 hour, 2 hours and 30 minutes, or 30 hours, etc., while the time period in the production plan is fixed, such as a time period of 24 hours. Therefore, through the above-mentioned processing time and WIP quantity matching constraints, the WIP quantity of each process node can be reasonably matched to each time period according to the process time and the length of the time period.

[0149] In an embodiment of the present application, the computer device uses the output of multiple products on the equipment in the corresponding process nodes in the corresponding time period as a variable, and constructs the constraints in the production planning model according to the calculation relationship between the production data of the production workshop and the above-mentioned constraints.

[0150] The above-mentioned step 303 is a possible implementation method for the computer device to construct the constraint conditions in the production planning model based on the production data of the production workshop. In this possible implementation method, the computer device constructs at least one of the following constraint conditions based on the production data of the production workshop: work-in-process balance constraint, mold constraint, production capacity constraint, inventory balance constraint, output constraint, and processing time and work-in-process quantity matching constraint, which takes into account the limitations of the production workshop in many aspects and can improve the feasibility of the production plan obtained according to the production planning model.

[0151] The above steps 301 to 303 are a possible implementation method for a computer device to construct a production planning model based on the production data of a production workshop. In this possible implementation method, by weighting multiple optimization objectives in the objective function and considering various restrictions in the constraints, multiple optimization objectives can be achieved in the process of obtaining a production plan based on the production planning model, and the feasibility of the production plan can be improved.

[0152] 304. Under the constraints of the production planning model, the computer equipment obtains an initial production plan with the goal of minimizing the objective function in the production planning model. The production plan includes the output of at least one product on the equipment in the corresponding process node in the corresponding time period. The production process of each product includes at least one process node, and each process node is produced using at least one device.

[0153] This step 304 is a possible implementation method for the computer device to obtain the initial production plan according to the production plan model. This implementation method obtains the initial production plan under the constraints simulated by the production plan model with the goal of minimizing the cost simulated by the production plan model. The variable in the production plan model is the output of at least one product on the equipment in the corresponding process node in the corresponding period. The above process of obtaining the initial production plan is equivalent to obtaining the output that minimizes the cost indicated by the above objective function under the above constraints to obtain the initial production plan. Similar to the above step 202, the embodiments of the present application will not be repeated here. By obtaining the initial production plan in this way, factors such as the delivery deadline of the order and the production capacity of the equipment in the production process are taken into account, so that the delivery delay is minimized and the equipment utilization rate is maximized, so that the obtained initial production plan can be more in line with the production needs of the production workshop.

[0154] 305. The computer equipment simulates the production process of the production workshop according to the priority corresponding to each product of at least one product and the initial production plan to obtain a simulation result. The priority indicates the production sequence of the products. The simulation result includes the output and production sequence of at least one product on the equipment in the corresponding process node in the corresponding time period during the simulation process.

[0155] In the embodiment of the present application, the initial production plan includes the output of multiple products on the equipment in the corresponding process node in the corresponding time period. The computer device combines the initial production plan, the priority corresponding to each product in at least one product, and the production data of the production workshop to formulate the production order of the products on the equipment in the corresponding process node in the corresponding time period, and obtains multiple production events in the production workshop and the execution order of multiple production events. The computer device simulates the production process of the production workshop according to the multiple production events and the execution order of multiple production events to obtain simulation results. Among them, the production data of the production workshop used in the simulation process includes the unit production time of each product, the time consumed by each mold switching, and the initial state of each device, etc., which is not limited in the embodiment of the present application.

[0156] In some embodiments, during the simulation process, the computer device records the number of work-in-progress for each product at the corresponding process node in the corresponding time period, and the computer device calculates the waiting time and advance time corresponding to the process node in the above time period during the simulation process based on the number of work-in-progress.

[0157] The above simulation process uses a discrete event simulation method to simulate the initial production plan, which can verify the feasibility of the initial production plan so that the production plan model can be adjusted more accurately based on the feasibility.

[0158] 306. The adjustment of the production planning model by the computer device includes multiple rounds of iterative adjustment processes. In the first round of adjustment process, the computer device adjusts the above production planning model according to the above simulation results to obtain the production planning model after the first round of adjustment.

[0159] In the embodiment of the present application, the computer device adjusts the production plan model in a variety of ways, for example, the adjustment methods include: the computer device adjusts the parameters in the production plan model according to the simulation results and the computer device adjusts the constraints in the production plan model according to the simulation results. In the process of adjusting the parameters in the production plan module, the computer device adjusts at least one of the lead time, waiting time and equipment capacity coefficient in the production plan model. In the process of adjusting the constraints in the production plan model, the computer device adds new constraints in the production plan model according to the simulation results. These various adjustment methods are described below.

[0160] In some embodiments, the computer device adjusts the parameters in the above production plan model according to the above simulation results. The parameter is pre-set, for example, the parameter is at least one of the lead time, waiting time and equipment capacity coefficient of any equipment corresponding to the process node of any product. Of course, the parameter can also be other parameters in the production plan model, which is not limited in the embodiment of the present application. The above adjustment process is described below taking the above three parameters as examples.

[0161] When the above parameter is the lead time of the process node, the computer device obtains the adjusted parameter through the following formula (5):

[0162] Adjusted lead time = α1*advance time during simulation + α2*preset lead time (5)

[0163] Among them, α1 and α2 are used to indicate the weights corresponding to the lead time and the preset lead time in the simulation process, respectively. The weights are preset, α1+α2=1, and α1 and α2 are real numbers greater than 0.

[0164] When the above parameter is the waiting time of the process node, the computer device obtains the adjusted parameter through the following formula (6):

[0165] Adjusted waiting time = β1*waiting time during simulation + β2*preset waiting time (6)

[0166] Among them, β1 and β2 are used to indicate the weights corresponding to the waiting time and the preset waiting time in the simulation process respectively. The weights are preset, β1+β2=1, and β1 and β2 are real numbers greater than 0.

[0167] When the above parameter is the equipment capacity coefficient, the computer equipment obtains the adjusted parameter through the following formula (7):

[0168] Adjusted equipment capacity coefficient = original equipment capacity coefficient + ((capacity corresponding to the initial production plan – capacity used in the simulation process) / unit time capacity) * γ (7)

[0169] Among them, the original equipment capacity coefficient is the equipment capacity coefficient of the equipment in the production data, the capacity corresponding to the initial production plan is calculated according to the output of various products produced by the equipment in the initial production plan, the capacity used in the simulation process is the capacity of the equipment recorded in the simulation process, and can be calculated according to the output of various products produced by the equipment in the simulation process. The capacity per unit time period is pre-set, or the capacity per unit time period is calculated based on the capacity corresponding to the initial production plan and the number of time periods, or the capacity per unit time period is calculated based on the capacity and the number of time periods used in the simulation process. The embodiment of the present application does not limit this. γ is a pre-set weight, which is a real number greater than 0.

[0170] By adjusting the parameters in the production planning model according to the simulation results, the accuracy of the production planning model can be improved, thereby improving the feasibility of the production plan obtained according to the production planning model.

[0171] In some embodiments, the computer device adjusts the constraint conditions in the production plan model according to the simulation results. During the adjustment process, the computer device adds new constraint conditions in the production plan model according to the simulation results.

[0172] In some embodiments, for any device, if the capacity in the simulation result corresponding to the device is less than the first capacity, a first constraint is added to the above production plan model, and the first constraint indicates that the capacity corresponding to the device in the corresponding time period is less than the second capacity corresponding to the time period. The first capacity is a pre-set capacity, or a certain proportion of the capacity of the above device in the corresponding time period in the initial production plan, and the second capacity is a pre-set capacity, or calculated based on the capacity of the above device in the corresponding time period in the simulation result and the capacity of the above device in the corresponding time period in the initial production plan. The above constraint can be expressed by the following formula (8):

[0173]

[0174] Among them, x ijkt It is used to indicate the output of product i at process node j on equipment k in time period t, P ijk It is used to indicate the production time (capacity consumption) of unit product i on equipment k at process node j, N ktIt is used to indicate the capacity of the device k in the time period t, that is, the second capacity mentioned above.

[0175] The above adjustment method limits the production capacity of the equipment in the corresponding time period by adding corresponding constraints in the production plan model when the production capacity of the equipment in the corresponding time period in the corresponding simulation results is less than a certain proportion of the production capacity in the initial production plan, thereby improving the feasibility of the production plan obtained according to the production plan model.

[0176] In some embodiments, the second capacity is calculated by the following formula (9):

[0177]

[0178] in, It is used to indicate the production capacity of equipment k in the simulation result corresponding to time period t. It is used to indicate the capacity of equipment k in the initial production plan within time period t, and λ and μ are pre-set parameters. This process can improve the accuracy of the newly added first constraint by adjusting the second capacity according to the simulation results and the initial production plan.

[0179] In some embodiments, for any device, if the capacity in the simulation result corresponding to the device is greater than or equal to the third capacity, a second constraint is added to the above production plan model, and the second constraint indicates that the capacity corresponding to the device in the corresponding time period is greater than or equal to the fourth capacity corresponding to the time period. The third capacity is a pre-set capacity, or a certain proportion of the capacity of the above device in the corresponding time period in the initial production plan, and the fourth capacity is a pre-set capacity, or calculated based on the capacity of the above device in the corresponding time period in the simulation result and the capacity of the above device in the corresponding time period in the initial production plan. The above constraint can be expressed by the following formula (10):

[0180]

[0181] Among them, N kt Used to indicate the capacity of device k in time period t, that is, the fourth capacity mentioned above. In some embodiments, the fourth capacity can also be calculated by the above formula (9). The formula (9) is a possible implementation method in which the computer device adjusts the second capacity corresponding to the corresponding time period in the first constraint condition and adjusts the fourth capacity corresponding to the corresponding time period in the second constraint condition according to the simulation results corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process. By adjusting the second capacity, the accuracy of the newly added first constraint condition can be improved, and by adjusting the fourth capacity, the accuracy of the newly added second constraint condition can be improved.

[0182] The above adjustment method constrains the production capacity of the equipment in the corresponding time period by adding corresponding constraints in the production plan model when the production capacity of the corresponding time period in the corresponding simulation results of the above equipment is greater than or equal to a certain proportion of the production capacity corresponding to the initial production plan, thereby improving the feasibility of the production plan obtained according to the production plan model.

[0183] The above adjustment of the constraints in the production planning model is only an example. The computer device can also add other constraints to the above production planning model according to the above simulation results, or delete some constraints in the production planning model, etc. The embodiments of the present application are not limited to this.

[0184] It should be noted that the embodiment of the present application describes multiple ways of adjusting the production plan model in step 306. In the process of adjusting the production plan model, the computer device can use one of the above two methods to adjust the production plan model, and can also use the above two adjustment methods to adjust the production plan model. The embodiment of the present application does not limit this. The above process adjusts the production plan model according to the simulation results, and then obtains the production plan according to the adjusted production plan model. Compared with adjusting the production plan directly according to the simulation results, it comprehensively considers the changes in the corresponding production plans of various products and the impact of the changes on other products, so that various products can be produced according to the final production plan, which improves the feasibility of the obtained production plan.

[0185] 307. During the i-th round of adjustment, the computer device obtains the simulation result corresponding to the i-th round of adjustment according to the production plan model after the i-1-th round of adjustment, where i is an integer greater than 1.

[0186] In an embodiment of the present application, under the constraints of the production planning model after the i-1th round of adjustment, the computer device takes minimizing the objective function in the production planning model after the i-1th round of adjustment as the goal, obtains the initial production plan corresponding to the i-th round of adjustment process, and simulates the production process of the production workshop according to the priority corresponding to each product and the initial production plan corresponding to the i-th round of adjustment process to obtain the simulation result corresponding to the i-th round of adjustment process.

[0187] 308. If the simulation result corresponding to the i-th round of adjustment process does not meet the preset conditions, the computer device adjusts the production plan model after the i-1th round of adjustment according to the simulation result corresponding to the i-th round of adjustment process to obtain the production plan model after the i-th round of adjustment.

[0188] Among them, the preset condition is that in the simulation results corresponding to the i-th round of adjustment process, the difference between the advance time of a certain proportion of products at the corresponding process node and the advance time corresponding to the i-1th round of adjustment process is less than the first preset difference. The preset condition can also be that in the simulation results corresponding to the i-th round of adjustment process, the difference between the waiting time of a certain proportion of products at the corresponding process node and the waiting time corresponding to the i-1th round of adjustment process is less than the second preset difference. The preset condition can also be that in the simulation results corresponding to the i-th round of adjustment process, the difference between the sum of the advance time and the waiting time of a certain proportion of products at the corresponding process node and the sum of the advance time and the waiting time corresponding to the i-1th round of adjustment process is less than the third preset difference. The preset condition can also be that in the simulation results corresponding to the i-th round of adjustment process, the difference between the output of a certain proportion of equipment and the output corresponding to the i-1th round of adjustment process is less than the fourth preset difference. The preset condition can also be that the time consumed by the iterative adjustment process is greater than or equal to the preset time, or the number of rounds of iterative adjustment is greater than or equal to the preset number of rounds, etc., which is not limited in the embodiments of the present application.

[0189] When the adjustment method is to adjust the parameters in the production plan model after the i-1th round of adjustment, the above step 308 is to adjust the parameters in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process. The simulation results corresponding to the current round of adjustment process are the simulation results corresponding to the initial production plan corresponding to the current round of adjustment process. The initial production plan corresponding to the current round of adjustment process is the initial production plan obtained according to the production plan model after the previous round of adjustment. The adjustment process is the same as the adjustment process in the above step 306. It should be noted that in the process of adjusting the production plan model after the i-1th round of adjustment, the computer equipment can adjust the production plan model after the i-1th round of adjustment in combination with the simulation results corresponding to the i-1th round of adjustment process and the simulation results corresponding to the i-th round of adjustment process, so that the adjustment of the production plan model after the i-1th round of adjustment is within a reasonable range, thereby improving the accuracy of the production plan model after the i-th round of adjustment.

[0190] For example, when the above parameter is the lead time of the process node, the computer device obtains the adjusted parameter through the following formula (11):

[0191] Adjusted lead time = α1*the lead time of the simulation process corresponding to the i-th round of adjustment process + α2*the lead time of the simulation process corresponding to the i-1-th round of adjustment process (11)

[0192] Formula (11) is a possible implementation method for a computer device to adjust the lead time corresponding to a product in a production plan model after a previous round of adjustment according to the lead time corresponding to the product in the simulation results corresponding to the current round of adjustment and the lead time corresponding to the product in the simulation results corresponding to the previous round of adjustment, wherein the lead time indicates the time consumed by the product in the first link of processing, and the first link indicates the above-mentioned non-bottleneck link.

[0193] When the above parameter is the waiting time of the process node, the computer device obtains the adjusted parameter through the following formula (12):

[0194] Adjusted waiting time = β1*the waiting time of the simulation process corresponding to the i-th round of adjustment process + β2*the waiting time of the simulation process corresponding to the i-1-th round of adjustment process (12)

[0195] Formula (12) is a possible implementation method for a computer device to adjust the waiting time corresponding to the product in the production plan model after the previous round of adjustment according to the waiting time corresponding to the product in the simulation results corresponding to the current round of adjustment process and the waiting time corresponding to the product in the simulation results corresponding to the previous round of adjustment process, wherein the waiting time indicates the time consumed by the product from completing the first link to entering the second link, the second link is performed after the first link, and the second link indicates the bottleneck link after the above-mentioned non-bottleneck link.

[0196] The above formula (11) and formula (12) are a possible implementation method for the computer device to adjust the production time in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process. The production time indicates the length of time consumed in the production process of the product, where the production time is the waiting time or the lead time.

[0197] When the above parameter is the equipment capacity coefficient, the computer equipment obtains the adjusted parameter through the following formula (13):

[0198] Adjusted equipment capacity coefficient = equipment capacity coefficient corresponding to the i-1th round of adjustment process + ((equipment capacity in the initial production plan corresponding to the i-th round of adjustment process – equipment capacity in the simulation process corresponding to the i-th round of adjustment process) / unit time capacity) * γ (13)

[0199] The above formula (13) is a possible implementation method for the computer device to adjust the equipment parameters in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process, wherein the equipment parameter is the equipment capacity coefficient, and the computer device adjusts the equipment capacity coefficient in the production plan model after the previous round of adjustment according to the equipment capacity in the simulation results corresponding to the current round of adjustment process and the equipment capacity in the initial production plan corresponding to the current round of adjustment process.

[0200] In the case where the adjustment method is to adjust the constraints in the production plan model after the i-1th round of adjustment, the above step 308 is to adjust the constraints in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process. The adjustment process is similar to the relevant content in the above step 306, that is, for any equipment in the production workshop, if the capacity of the equipment in the simulation results corresponding to the current round of adjustment process is less than the first capacity, the computer device adds a first constraint to the production plan model after the previous round of adjustment, and the first constraint indicates that the capacity corresponding to the equipment in the corresponding time period is less than the second capacity corresponding to the time period, and the first capacity is related to the initial production plan corresponding to the current round of adjustment process, and the second capacity is related to the simulation results corresponding to the current round of adjustment process. If the capacity of the equipment in the simulation results corresponding to the current round of adjustment process is greater than or equal to the third capacity, a second constraint is added to the production plan model corresponding to the previous round of adjustment process, and the second constraint indicates that the capacity corresponding to the equipment in the corresponding time period is greater than or equal to the fourth capacity corresponding to the time period, and the third capacity is related to the initial production plan corresponding to the current round of adjustment process, and the fourth capacity is related to the simulation results corresponding to the current round of adjustment process. The embodiments of this application will not be repeated here.

[0201] 309. If the simulation result corresponding to the i-th round of adjustment process meets the preset conditions, the computer device outputs the production plan corresponding to the production plan model after the i-1-th round of adjustment as the production plan of the production workshop.

[0202] In an embodiment of the present application, if the simulation result corresponding to the i-th round of adjustment process meets the preset conditions, the computer device stops iterating and outputs the production plan corresponding to the production plan model after the i-1th round of adjustment as the production plan of the production workshop.

[0203] The above steps 306 to 309 are a possible implementation method of adjusting the production planning model according to the simulation results, and obtaining the production plan according to the adjusted production planning model. This implementation method gradually adjusts the production planning model through iteration, which can improve the accuracy of the production planning model, and further improve the accuracy of the production plan obtained according to the production planning model.

[0204] The production plan acquisition method provided in the embodiment of the present application acquires the production plan model according to the production data of the production workshop, and then acquires the initial production plan according to the production plan model. After simulating the initial production plan, the simulation result obtained reflects the feasibility of the initial production plan. Adjusting the production plan model according to the simulation result is equivalent to adjusting the initial production plan from the root, that is, adjusting the relevant content simulated by the production plan model to improve the feasibility of the production plan acquired according to the adjusted production plan model. In addition, the production plan is acquired according to the adjusted production plan model, and the changes in the corresponding production plans of various products and the impact of the changes on other products are comprehensively considered, so that various products can be completed according to the final production plan. The feasibility of the acquired production plan is improved, and the capacity utilization rate of the production workshop can also be improved, the delay amount corresponding to the order is reduced, and the automated operation of the production workshop is optimized.

[0205] It can be seen from the above description that the production plan acquisition method provided in the embodiment of the present application can be Figure 5 The system shown is implemented as Figure 5 As shown, the system includes a production data module, a plan generation module, a simulation module and a control module. Among them, the production data module is used to obtain the production data of the production workshop, and the production data can be used to build a production plan model and simulate the production process. The plan generation module is used to build a production plan model according to the production data of the production workshop, and obtain the initial production plan according to the production plan model. The simulation module includes a processing production model of each device, which is used to simulate the production process of each device. The simulation module also includes the unit production time, priority, and switching time of various molds of various products. The simulation module also includes a work-in-progress data model on the corresponding process route of various products, etc. The work-in-progress data model can simulate the production status of the product at the corresponding process node, and give the lead time, waiting time and number of work-in-progress of each product at the corresponding process node. The simulation module is used to simulate the production process of the production workshop according to the initial production plan to obtain the simulation results. The control module is used to evaluate the feasibility of the initial production plan according to the simulation results, determine whether it is necessary to adjust the production plan according to the simulation results, and then re-iterate to obtain the initial production plan. Feedback adjustment is performed between the plan generation module and the simulation module through the control module, which can improve the feasibility of the production plan obtained according to the adjusted production plan model.

[0206] This method can be applied to the Array link on the display panel production line, etc., and the embodiments of the present application are not limited to this.

[0207] Figure 6 is a structural block diagram of a production plan acquisition device provided in an embodiment of the present application. The device is used to execute the steps of the above production plan acquisition method. Figure 6 , the production plan acquisition device comprises:

[0208] A model building module 601 is used to build a production planning model based on the production data of the production workshop, and the production planning model is used to simulate the cost consumed and the constraints satisfied by the production workshop in the process of producing at least one product;

[0209] The initial plan acquisition module 602 is used to acquire an initial production plan according to the production plan model, wherein the production plan includes the output of at least one product on the equipment in the corresponding process node in the corresponding period, the production process of each product includes at least one process node, and each process node is produced by at least one equipment;

[0210] A simulation module 603 is used to simulate the production process of the production workshop according to the priority corresponding to each product of the at least one product and the initial production plan to obtain a simulation result, wherein the priority indicates the production sequence of the products, and the simulation result includes the output and production sequence of the at least one product on the equipment in the corresponding process node in the corresponding time period during the simulation process;

[0211] The adjustment module 604 is used to adjust the production plan model according to the simulation results, and obtain the production plan according to the adjusted production plan model.

[0212] In some embodiments, the model building module 601 includes:

[0213] An objective function building unit is used to build an objective function in a production planning model according to a calculation relationship between production data and costs in a production workshop, and the objective function is used to obtain costs;

[0214] The constraint condition building unit is used to build the constraint conditions in the production plan model according to the production data of the production workshop.

[0215] In some embodiments, the above cost includes extension cost and tangent cost, the extension cost indicates the cost consumed by delayed product delivery, and the tangent cost indicates the cost consumed by switching molds on the equipment, and the above objective function construction unit is used to:

[0216] According to the calculation relationship between the production data of the production workshop and the postponement cost and tangent cost, and the corresponding weights of the postponement cost and the tangent cost, the objective function in the production planning model is constructed. The objective function is the weighted sum of the postponement cost and the tangent cost.

[0217] In some embodiments, the constraints in the production planning model include at least one of the following: work-in-process balance constraints, mold constraints, capacity constraints, inventory balance constraints, output constraints, and processing time and work-in-process quantity matching constraints;

[0218] The WIP balance constraint indicates a constraint constructed, for each product of at least one product, based on the relationship between the WIP quantity of the product at each process node and the output of the product;

[0219] The mold constraint indicates a constraint constructed based on the relationship between the number of molds and the products produced by the molds;

[0220] The capacity constraint indicates a constraint built according to the maximum capacity of the equipment;

[0221] The inventory balance constraint indicates, for each of at least one of the products, a constraint constructed based on the relationship between the output, inventory, deferral, and demand of the product;

[0222] The yield constraint indicates, for each product of at least one product, a constraint constructed based on a maximum yield and a minimum yield of the product at each process node;

[0223] The processing time and WIP quantity matching constraint indicates a constraint constructed according to a relationship between the WIP quantity of the product at each process node and the process time of the corresponding process node for each product of the at least one product.

[0224] In some embodiments, the initial plan acquisition module 602 is used to:

[0225] Under the constraints simulated by the production planning model, the initial production plan is obtained with the goal of minimizing the cost simulated by the production planning model.

[0226] In some embodiments, the adjustment of the production planning model includes multiple rounds of iterative adjustment processes, and the adjustment module 604 includes at least one of the following:

[0227] A parameter adjustment unit, used to adjust the parameters in the production plan model adjusted in the previous round according to the simulation result corresponding to the current round of adjustment process, wherein the simulation result corresponding to the current round of adjustment process is the simulation result corresponding to the initial production plan corresponding to the current round of adjustment process, and the initial production plan corresponding to the current round of adjustment process is the initial production plan obtained according to the production plan model adjusted in the previous round;

[0228] The condition adjustment unit is used to adjust the constraint conditions in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process.

[0229] In some embodiments, the parameter adjustment unit includes at least one of the following:

[0230] The time adjustment subunit is used to adjust the production time in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process, and the production time indicates the time consumed by the production process of the product;

[0231] The equipment parameter adjustment subunit is used to adjust the equipment parameters in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process.

[0232] In some embodiments, the time adjustment subunit is used to:

[0233] According to the lead time corresponding to the product in the simulation result corresponding to the current round of adjustment process and the lead time corresponding to the product in the simulation result corresponding to the previous round of adjustment process, the lead time corresponding to the product in the production plan model after the previous round of adjustment is adjusted, and the lead time indicates the time consumed by the product in the first link of processing;

[0234] According to the waiting time corresponding to the product in the simulation results corresponding to the current round of adjustment process and the waiting time corresponding to the product in the simulation results corresponding to the previous round of adjustment process, adjust the waiting time corresponding to the product in the production plan model after the previous round of adjustment. The waiting time indicates the time consumed by the product from completing the first link to entering the second link. The second link is carried out after the first link.

[0235] In some embodiments, the device parameter adjustment subunit is used to:

[0236] According to the equipment capacity in the simulation results corresponding to the current round of adjustment process and the equipment capacity in the initial production plan corresponding to the current round of adjustment process, the equipment capacity coefficient in the production plan model after the previous round of adjustment is adjusted.

[0237] In some embodiments, the condition adjustment unit is used to:

[0238] For any equipment in the production workshop, if the capacity of the equipment in the simulation result corresponding to the current round of adjustment process is less than the first capacity, a first constraint condition is added to the production plan model after the previous round of adjustment. The first constraint condition indicates that the capacity of the equipment in the corresponding time period is less than the second capacity corresponding to the time period. The first capacity is related to the initial production plan corresponding to the current round of adjustment process, and the second capacity is related to the simulation result corresponding to the current round of adjustment process.

[0239] For any equipment in the production workshop, if the equipment's production capacity in the simulation results corresponding to the current round of adjustment process is greater than or equal to the third production capacity, a second constraint condition is added to the production plan model corresponding to the previous round of adjustment process. The second constraint condition indicates that the equipment's production capacity in the corresponding time period is greater than or equal to the fourth production capacity corresponding to the time period. The third production capacity is related to the initial production plan corresponding to the current round of adjustment process, and the fourth production capacity is related to the simulation results corresponding to the current round of adjustment process.

[0240] In some embodiments, the above device further comprises at least one of the following:

[0241] A first constraint adjustment module, used for adjusting the second production capacity corresponding to the corresponding time period in the first constraint condition according to the simulation result corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process;

[0242] The second constraint adjustment module is used to adjust the fourth production capacity corresponding to the corresponding time period in the second constraint condition according to the simulation result corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process.

[0243] It should be noted that: the device provided in the above embodiment only uses the division of the above functional modules as an example to illustrate when obtaining the production plan. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0244] Figure 7 It is a structural diagram of a computer device provided in an embodiment of the present application. The computer device 700 may have relatively large differences due to different configurations or performances, and may include one or more CPUs (Central Processing Units, processors) 701 and one or more memories 702, wherein the memory 702 stores at least one computer program, and the at least one computer program is loaded and executed by the processor 701 to implement the production plan acquisition method provided by the above-mentioned various method embodiments. Of course, the computer device may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The computer device may also include other components for realizing the functions of the device, which will not be described in detail here.

[0245] The embodiment of the present application also provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is loaded and executed by the processor of the computer device to implement the operation performed by the computer device in the production plan acquisition method of the above embodiment. For example, the computer-readable storage medium can be ROM (Read-Only Memory), RAM (Random Access Memory), CD-ROM (Compact Dis c Read-Only Memory), magnetic tape, floppy disk and optical data storage device, etc.

[0246] The embodiment of the present application also provides a computer program product or a computer program, which includes a computer program code, and the computer program code is stored in a computer-readable storage medium. The processor of the computer device reads the computer program code from the computer-readable storage medium, and the processor executes the computer program code, so that the computer device executes the production plan acquisition method provided in the above various optional implementations.

[0247] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0248] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A production plan acquisition method, characterized in that: The method comprises: Constructing a production planning model based on the production data of the production workshop, wherein the production planning model is used to simulate the cost consumed and the constraints satisfied by the production workshop in the process of producing at least one product; According to the production plan model, an initial production plan is obtained, wherein the production plan includes the output of at least one product on the equipment in the corresponding process node in the corresponding time period, the production process of each product includes at least one process node, and each process node is produced by at least one equipment; According to the priority corresponding to each product of the at least one product, and in accordance with the initial production plan, the production process of the production workshop is simulated to obtain a simulation result, wherein the priority indicates the production sequence of the products, and the simulation result includes the output and production sequence of the at least one product on the equipment in the corresponding process node in the corresponding time period during the simulation process; The production planning model is adjusted according to the simulation result, and the production plan is obtained according to the adjusted production planning model.

2. The method according to claim 1, characterized in that The construction of the production planning model according to the production data of the production workshop includes: According to the calculation relationship between the production data of the production workshop and the cost, constructing the objective function in the production planning model, wherein the objective function is used to obtain the cost; According to the production data of the production workshop, the constraint conditions in the production planning model are constructed.

3. The method according to claim 2, characterized in that The cost includes a deferral cost and a tangent cost, wherein the deferral cost indicates the cost consumed by delayed product delivery, and the tangent cost indicates the cost consumed by switching molds on equipment. The objective function in the production planning model is constructed based on the calculation relationship between the production data of the production workshop and the cost, including: According to the calculation relationship between the production data of the production workshop and the extension cost and the tangent cost, and the weights corresponding to the extension cost and the tangent cost respectively, the objective function in the production planning model is constructed, and the objective function is the weighted sum of the extension cost and the tangent cost.

4. The method according to claim 2, characterized in that: The constraints in the production planning model include at least one of the following: work-in-process balance constraint, mold constraint, capacity constraint, inventory balance constraint, output constraint, and processing time and work-in-process quantity matching constraint; The WIP balance constraint indicates a constraint constructed for each of the at least one product according to a relationship between the WIP quantity of the product at each process node and the output of the product; The mold constraint indicates a constraint constructed according to a relationship between the number of molds and products produced by the molds; The capacity constraint indicates a constraint constructed according to a maximum capacity of a device; The inventory balance constraint indicates a constraint constructed according to a relationship between a production volume, an inventory volume, a postponement volume, and a demand volume of each of the at least one product; The yield constraint indicates a constraint constructed according to a maximum yield and a minimum yield of the product at each process node for each of the at least one product; The processing time and WIP quantity matching constraint indicates a constraint constructed, for each of the at least one product, according to a relationship between the WIP quantity of the product at each process node and the process time of the corresponding process node.

5. The method according to claim 1, characterized in that The obtaining of the initial production plan according to the production plan model comprises: Under the constraints simulated by the production planning model, the initial production plan is obtained with the goal of minimizing the cost simulated by the production planning model.

6. The method according to claim 1, characterized in that The adjustment of the production planning model includes multiple rounds of iterative adjustment processes, and the adjustment of the production planning model according to the simulation results includes at least one of the following: According to the simulation results corresponding to the current round of adjustment process, the parameters in the production plan model adjusted in the previous round are adjusted. The simulation results corresponding to the current round of adjustment process are the simulation results corresponding to the initial production plan corresponding to the current round of adjustment process. The initial production plan corresponding to the current round of adjustment process is the initial production plan obtained according to the production plan model adjusted in the previous round. According to the simulation results corresponding to the current round of adjustment process, the constraints in the production plan model after the previous round of adjustment are adjusted.

7. The method according to claim 6, characterized in that The adjusting of the parameters in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process includes at least one of the following: According to the simulation results corresponding to the current round of adjustment process, the production time in the production plan model adjusted in the previous round is adjusted, and the production time indicates the time consumed in the production process of the product; According to the simulation results corresponding to the current round of adjustment process, the equipment parameters in the production plan model after the previous round of adjustment are adjusted.

8. The method according to claim 7, characterized in that The step of adjusting the production time in the production plan model after the previous round of adjustment according to the simulation result corresponding to the current round of adjustment process includes: According to the lead time corresponding to the product in the simulation result corresponding to the current round of adjustment process and the lead time corresponding to the product in the simulation result corresponding to the previous round of adjustment process, the lead time corresponding to the product in the production plan model after the previous round of adjustment is adjusted, and the lead time indicates the time consumed by the product in the first link processing; According to the waiting time corresponding to the product in the simulation results corresponding to the current round of adjustment process and the waiting time corresponding to the product in the simulation results corresponding to the previous round of adjustment process, adjust the waiting time corresponding to the product in the production plan model after the previous round of adjustment. The waiting time indicates the time consumed by the product from completing the first link to entering the second link. The second link is performed after the first link.

9. The method according to claim 7, characterized in that: The step of adjusting the equipment parameters in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process includes: According to the equipment capacity in the simulation results corresponding to the current round of adjustment process and the equipment capacity in the initial production plan corresponding to the current round of adjustment process, the equipment capacity coefficient in the production plan model after the previous round of adjustment is adjusted.

10. The method according to claim 6, characterized in that The step of adjusting the constraints in the production plan model after the previous round of adjustment according to the simulation results corresponding to the current round of adjustment process includes: For any equipment in the production workshop, if the capacity of the equipment in the simulation result corresponding to the current round of adjustment process is less than the first capacity, a first constraint condition is added to the production plan model after the previous round of adjustment, wherein the first constraint condition indicates that the capacity of the equipment in the corresponding time period is less than the second capacity corresponding to the time period, the first capacity is related to the initial production plan corresponding to the current round of adjustment process, and the second capacity is related to the simulation result corresponding to the current round of adjustment process; For any equipment in the production workshop, if the production capacity of the equipment in the simulation results corresponding to the current round of adjustment process is greater than or equal to the third production capacity, a second constraint condition is added to the production plan model corresponding to the previous round of adjustment process. The second constraint condition indicates that the production capacity of the equipment in the corresponding time period is greater than or equal to the fourth production capacity corresponding to the time period. The third production capacity is related to the initial production plan corresponding to the current round of adjustment process, and the fourth production capacity is related to the simulation results corresponding to the current round of adjustment process.

11. The method according to claim 10, characterized in that The method further comprises at least one of the following: According to the simulation result corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process, adjusting the second production capacity corresponding to the corresponding time period in the first constraint condition; According to the simulation results corresponding to the current round of adjustment process and the initial production plan corresponding to the current round of adjustment process, the fourth production capacity corresponding to the corresponding time period in the second constraint condition is adjusted.

12. A production plan acquisition device, characterized in that: The device comprises: A model building module, used to build a production planning model based on the production data of the production workshop, wherein the production planning model is used to simulate the cost consumed and the constraints satisfied by the production workshop in the process of producing at least one product; An initial plan acquisition module is used to acquire an initial production plan according to the production plan model, wherein the production plan includes the output of at least one product on the equipment in the corresponding process node in the corresponding time period, the production process of each product includes at least one process node, and each process node is produced by at least one equipment; a simulation module, configured to simulate the production process of the production workshop according to the priority corresponding to each product of the at least one product and the initial production plan, to obtain a simulation result, wherein the priority indicates a production sequence of the products, and the simulation result includes an output and a production sequence of the at least one product on a device in a corresponding process node in a corresponding time period during the simulation process; An adjustment module is used to adjust the production plan model according to the simulation result, and obtain a production plan according to the adjusted production plan model.

13. A computer device, characterized in that: The computer device comprises a processor and a memory, wherein the memory is used to store at least one computer program, and the at least one computer program is loaded by the processor to execute the method according to any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store at least one computer program, and the at least one computer program is used to execute the method according to any one of claims 1 to 11.

15. A computer program product, characterized in that The method comprises a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

Images