Material management method, electronic device and storage medium

Abstract

A material management method, an electronic device and a storage medium. The material management method comprises: acquiring production information of at least one product, wherein the production information comprises process information and material information associated with the process information, the process information is associated with at least one process, the material information is associated with at least one material, and each process corresponds to at least one material; performing production scheduling on the basis of the process information of the at least one product, so as to obtain a production scheduling result, wherein the production scheduling result comprises a process execution sequence for preparing the at least one product; and on the basis of the production scheduling result and the material information, scheduling a material stacking sequence for preparing the at least one product, so as to obtain a material stacking scheduling result, wherein in the material stacking scheduling result, the stacking sequence of at least some materials is opposite to the corresponding process execution sequence.

Description

Material management method, electronic device and storage medium

[0001] The present application claims priority to the Chinese patent application No. 202410832688.3, filed on June 25, 2024, and entitled "A material management method, electronic device and storage medium", the contents of which are understood to be incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to the field of production manufacturing, and in particular, to a material management method, electronic device and storage medium. BACKGROUND

[0003] With the rapid iteration of display panel demand, personalized and customized production is gradually increasing, and flexible production characterized by "small batch and multiple varieties" is gradually becoming the core competitiveness of manufacturing industry. In the future, digital factory needs to realize agile upgrade of the entire supply chain and flexible and efficient production and manufacturing. In the display panel manufacturing process, product production scheduling and material management are one of the key links. SUMMARY

[0004] The following is a summary of the subject matter of the detailed description herein. This summary is not intended to limit the scope of the claims.

[0005] In a first aspect, the embodiments of the present disclosure provide a material management method, comprising:

[0006] obtaining production information of at least one product, the production information comprising process information and material information associated with the process information, the process information being associated with at least one process, and the material information being associated with at least one material, each process corresponding to at least one material;

[0007] scheduling production according to the process information of the at least one product to obtain a production scheduling result, the production scheduling result comprising an execution order of processes for preparing the at least one product;

[0008] scheduling a material stacking order for preparing the at least one product according to the production scheduling result and the material information to obtain a material stacking scheduling result, in which the stacking order of at least part of the materials is opposite to the corresponding execution order of the processes.

[0009] In an exemplary embodiment, the scheduling production according to the process information of the at least one product comprises: constructing a production scheduling model based on the process information of the at least one product, solving the production scheduling model to obtain the production scheduling result, and the production scheduling model comprising a constraint condition of minimizing the time for preparing the at least one product;

[0010] The sequence of process execution in the production scheduling result is a sequence of process execution with the least time for preparing the at least one product.

[0011] In an example embodiment, the production information further comprises production time, and the production scheduling model is constructed based on the process information of the at least one product, comprising: determining a scheduling position of each process according to the production time and the process information, and setting a start time and an end time of each process according to the scheduling position of each process.

[0012] In an example embodiment, the constraint condition of the least time for preparing the at least one product comprises: setting the end time of the last process to be the earliest.

[0013] In an example embodiment, the constraint condition of the production scheduling model comprises: each process has only one scheduling position, and each scheduling position has only one process.

[0014] In an example embodiment, the constraint condition further comprises: subtracting the start time of a corresponding process from the end time of the corresponding process to obtain the duration of the corresponding process.

[0015] In an example embodiment, the constraint condition further comprises: the end time of a previous process is not later than the start time of a next process.

[0016] In an example embodiment, the solving of the production scheduling model comprises: solving the production scheduling model by a solver to obtain the production scheduling result.

[0017] In an example embodiment, the production information further comprises material storage space information, the material storage space information is associated with a material storage space, and each material storage space corresponds to at least one material and at least one process;

[0018] The stacking sequence of the at least part of the materials is opposite to the corresponding sequence of process execution, comprising: in at least one process corresponding to one of the storage spaces, the material stacking time corresponding to a process executed earlier is later than the material stacking time corresponding to a process executed later.

[0019] In an example embodiment, after obtaining the production scheduling result, at least one of equipment utilization, production continuity, and input-output balance is evaluated.

[0020] In an example embodiment, the production information further comprises batch information, and the batch information comprises equipment information, product type, and product output information.

[0021] The evaluating the utilization of the equipment comprises: calculating a proportion of an operating time of the equipment corresponding to the equipment information in natural time to obtain the utilization of each equipment;

[0022] The evaluating the production continuity comprises: for the equipment corresponding to the same equipment information, if a product type of a current product batch is consistent with a product type of a previous product batch, increasing a value of a continuity identifier by 1, and if the product type of the current product batch is inconsistent with the product type of the previous product batch, setting the value of the continuity identifier to 0, and evaluating the production continuity according to the value of the continuity identifier;

[0023] The evaluating the input-output balance comprises: forming a daily input vector from daily input amounts in the material information, calculating a Gini coefficient of the daily input vector to evaluate input balance, and forming a daily output vector from daily output amounts in the product output information, calculating a Gini coefficient of the daily output vector to evaluate output balance.

[0024] In an example embodiment, the evaluating the utilization of the equipment further comprises: calculating an average value of utilization of all devices of the same type to obtain the utilization of each type of equipment.

[0025] In an example embodiment, the obtaining the production information of the at least one product comprises: obtaining initial data of the production information of the at least one product, and preprocessing the initial data to obtain the production information; and the data preprocessing comprises one or more of error value filtering, format conversion, and missing value filling operation.

[0026] In an example embodiment, the constructing the production scheduling model based on the process information of the at least one product further comprises: displaying a production scheduling interface, the production scheduling interface comprising a workflow management area, a modeling component library, a main work area, an outline view, and a console; wherein:

[0027] The workflow management area is configured to store a workflow;

[0028] The modeling component library is configured to store modeling components, and the modeling components can be dragged to the main work area;

[0029] The main work area is configured to edit a flow of the production scheduling model;

[0030] The outline view is configured to display the flow of the production scheduling model;

[0031] The console is configured to display warning information or error information in the flow of the production scheduling model.

[0032] In a second aspect, the embodiments of the present disclosure provide an electronic device, comprising a memory and a processor, wherein the memory stores instructions executable by the processor, and the instructions, when executed by the processor, cause the processor to perform the method according to any one of the embodiments described above.

[0033] In a third aspect, the embodiments of the present disclosure provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform the method according to any one of the embodiments described above.

[0034] Other aspects can become apparent from a review of the drawings and detailed description. BRIEF DESCRIPTION OF DRAWINGS

[0035] The accompanying drawings are included to provide a further understanding of the technical solutions of the present disclosure, constitute a part of the specification, and are used to explain the technical solutions of the present disclosure together with the embodiments of the present disclosure, but do not constitute a limitation on the technical solutions of the present disclosure. The shape and size of each component in the drawings do not reflect the true proportion, and the purpose is only to schematically illustrate the present disclosure.

[0036] FIG. 1 is a flowchart of a material management method according to an embodiment of the present disclosure;

[0037] FIG. 2 is a schematic diagram of a production scheduling interface according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] Hereinafter, the embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present disclosure can be combined with each other without conflict if possible.

[0039] Unless otherwise defined, technical terms or scientific terms used in the embodiments of the present disclosure should be understood as the common meaning understood by a person skilled in the art to which the present disclosure belongs. The terms "first", "second", and the like used in the embodiments of the present disclosure do not represent any order, number, or importance, but are only used to distinguish different components.

[0040] In the production scheduling process of products, manual scheduling has the problem of low efficiency, and there is a certain optimization space in equipment utilization. Especially for large-scale complex production, the scheduling efficiency is low, and the equipment utilization is low. The situation is more prominent; intelligent scheduling algorithms have obvious differences for different manufacturing industries. That is, the standardized general scheduling algorithm still has a large amount of customization and development work when landing. Combined with certain uncertain factors in the production and manufacturing process, such as equipment downtime, temporary insertion, product rework, etc., these uncertain factors will increase the difficulty of the scheduling algorithm. In the field of semiconductor display manufacturing, due to the complexity of the process, the large number of materials, the many constraints, and the characteristics of small batch and multi-species of products, the production scheduling of products is difficult, and the complexity of the factory-level scheduling of the semiconductor display industry is relatively high, which increases the difficulty of intelligent scheduling. Therefore, in the field of semiconductor manufacturing, the production scheduling of products has the technical problems of low efficiency and great difficulty. In addition, in the field of semiconductor manufacturing, the process and material involved are relatively large, and the material storage space is limited. Especially in the production process, the cache space of the material is limited by the execution order of the process, and the material placement order is required to be high. The material required by the process executed first is placed below, and the material required by the process executed later is placed above. The process executed first needs to wait for the material consumption of the process executed later before obtaining the corresponding material, resulting in low production efficiency.

[0041] The exemplary embodiments of the present disclosure provide a material management method, which can include:

[0042] Obtaining production information of at least one product, the production information including process information and material information associated with the process information, the process information being associated with at least one process, and the material information being associated with at least one material, each process corresponding to at least one material;

[0043] Performing production scheduling according to the process information of the at least one product to obtain a production scheduling result, the production scheduling result including an execution order of processes for preparing the at least one product;

[0044] Scheduling a material stacking order for preparing the at least one product according to the production scheduling result and the material information to obtain a material stacking scheduling result, in which the stacking order of at least part of the materials is opposite to the corresponding execution order of the processes.

[0045] The material management method provided by the embodiments of the present disclosure can perform production scheduling according to the process information of at least one product, obtain a production scheduling result, the production scheduling result includes the process execution order of preparing the at least one product, perform scheduling on the material stacking order of preparing the at least one product according to the production scheduling result and the material information, and obtain a material stacking scheduling result, in which the stacking order of at least part of the materials is opposite to the corresponding process execution order. The scheme provided by the embodiments of the present disclosure can solve the technical problem that the unreasonable material stacking leads to low production efficiency to some extent.

[0046] In an example embodiment, as shown in FIG. 1, the material management method provided by the example embodiments of the present disclosure can include steps S1 to S3:

[0047] Step S1: obtaining production information of at least one product, the production information including process information and material information associated with the process information, the process information being associated with at least one process, the material information being associated with at least one material, and each process corresponding to at least one material;

[0048] Step S2: performing production scheduling according to the process information of the at least one product, and obtaining a production scheduling result, the production scheduling result including a process execution order of preparing the at least one product;

[0049] Step S3: performing scheduling on the material stacking order of preparing the at least one product according to the production scheduling result and the material information, and obtaining a material stacking scheduling result, in which the stacking order of at least part of the materials is opposite to the corresponding process execution order.

[0050] In an example embodiment, after obtaining the process execution order of the production scheduling result, the material stacking order associated with each process can be scheduled according to the process execution order. The material corresponding to the process executed first can be stacked later, and the material corresponding to the process executed later can be stacked first. In this way, the material associated with the process executed first can be obtained first, without waiting, which can improve the production efficiency. In actual production, when there are many processes and materials, the material corresponding to the process executed first is often stacked below the material corresponding to the process executed later, which often causes the process executed first to wait for the material corresponding to the process executed later to be consumed before obtaining the material of the process executed first, resulting in a waste of waiting time for the process executed first and low production efficiency.

[0051] In some preparation processes, the execution of some processes can be associated. For example, the output of the process executed first can be used as the material of the process executed later, that is, the material can be raw materials purchased from outside or semi-finished products output by the process executed first.

[0052] In the example embodiment, the production information of the product is obtained, and the production information to be produced can be input into the production scheduling system, such as the production time of the product, the product model, etc. The production scheduling system can obtain the process information corresponding to the product model from the inside or from the outside (for example, manual input, or code scanning, or from an external database).

[0053] In the example embodiment, during the preparation of a batch of products, temporary orders are often added or the preparation of a certain product is temporarily cancelled, and then the above steps S1 to S3 can be re-executed. In the case of temporary order addition, the product information of the completed product can be removed and the product information of the temporary order addition can be added in step S1 of the production scheduling system, and then the above steps S2 to S3 are executed. In the case of temporary cancellation of a certain product, the product information of the completed product and the temporarily cancelled product information can be removed in step S1 of the production scheduling system, and then the above steps S2 to S3 are executed. For the case of temporary cancellation or addition of a certain product, the above steps S1 to S3 are re-executed, the stacking order of the material can be temporarily adjusted, the stacking order of the material corresponding to the next process can be reasonably predicted, and the low production efficiency caused by unreasonable material stacking can be avoided.

[0054] In the example embodiment, after the production scheduling system obtains the material stacking order, the robot carrying the material can be controlled (which can be controlled by the production scheduling system or the production scheduling system provides the material stacking order to the robot control platform) to stack the material according to the material stacking order, or the material stacking order can be displayed, and the material can be stacked by artificial according to the material stacking order.

[0055] In the example embodiment, in step S2, the production scheduling based on the process information of the at least one product can include: constructing a production scheduling model based on the process information of the at least one product, solving the production scheduling model to obtain a production scheduling result, and the production scheduling model includes a constraint condition that the time for preparing the at least one product is the least;

[0056] The process execution order in the production scheduling result can be the process execution order in which the time for preparing the at least one product is the least.

[0057] In the example embodiment, the production information further includes the production time, and constructing the production scheduling model based on the process information of the at least one product can include: modeling the execution time of each process according to the scheduling position of each process.

[0058] In an example embodiment, the constraint condition of the minimum time for manufacturing the at least one product can include that the end time of the last process is the earliest.

[0059] In an example embodiment, the constraint condition of the minimum time for manufacturing the at least one product can include that the end time of the last process is the earliest.

[0060] In an example embodiment, the constraint condition of the production scheduling model can include that each process has only one scheduling position and each scheduling position has only one process.

[0061] In an example embodiment, the constraint condition of the scheduling planning model can further include that the duration of each process is set according to the start time and the end time of each process.

[0062] In an example embodiment, the constraint condition of the scheduling planning model can further include that the duration of each process is set according to the start time and the end time of each process.

[0063] In an example embodiment, the constraint condition of the production scheduling model can further include that the end time of the previous process is not later than the start time of the next process.

[0064] In an example embodiment, the constraint condition of the production scheduling model can further include that the end time of the previous process is not later than the start time of the next process.

[0065] In an example embodiment, the production information can further include material storage space information, the material storage space information being associated with the material storage space, each material storage space corresponding to at least one material and at least one process.

[0066] The stacking order of at least part of the materials is opposite to the execution order of the corresponding processes, including that in at least one process corresponding to one of the storage spaces, the material stacking time corresponding to the process executed first is later than the material stacking time corresponding to the process executed later, which can avoid unreasonable waiting time caused by stacking materials and improve production efficiency.

[0067] In the example embodiment, the storage space can be a temporary buffer space for storing materials. In the production process, due to the large amount of materials and the limited temporary buffer space for materials, the materials corresponding to the earlier performed process are stacked for a longer time than the materials corresponding to the later performed process. The storage space of the materials can be reasonably utilized, and the low production efficiency caused by unreasonable stacking of the materials can be avoided.

[0068] In the example embodiment, after obtaining the production scheduling result, the evaluation of at least one of the device utilization rate, the production continuity, and the input-output balance can be further included.

[0069] In the example embodiment, the production information can include batch information, and the batch information can include device information. The evaluation of the device utilization rate can include calculating the proportion of the working time of the device corresponding to the device information in the natural time to obtain the utilization rate of each device.

[0070] In the example embodiment, the evaluation of the device utilization rate can further include calculating the average value of the utilization rates of all devices of the same type to obtain the utilization rate of each type of device.

[0071] In the example embodiment, the batch information can further include device information and product type. The evaluation of the production continuity can include, for the device corresponding to the same device information, when the product type of the current product batch is consistent with the product type of the previous product batch, increasing the value of the continuity identifier by 1, and when the product type of the current product batch is inconsistent with the product type of the previous product batch, setting the value of the continuity identifier to 0, and evaluating the production continuity according to the value of the continuity identifier.

[0072] In the example embodiment, the batch information can further include material information and product output information. The evaluation of the input-output balance can include forming a daily input vector from the daily input amount in the material information, calculating the Gini coefficient of the daily input vector to evaluate the input balance, and forming a daily output vector from the daily output amount in the product output information, calculating the Gini coefficient of the daily output vector to evaluate the output balance.

[0073] In the example embodiment, in step S1, obtaining the production information of at least one product can include obtaining initial data of the production information of at least one product, and preprocessing the initial data to obtain the production information.

[0074] In the example embodiment, the data preprocessing can include one or more of error value filtering, format conversion, and missing value filling operations.

[0075] In an example embodiment, the constructing the production scheduling model based on the process information of at least one product can further include: displaying a production scheduling interface, as shown in FIG. 2, the production scheduling interface including a workflow management area, a modeling component library, a main work area, an outline view, and a console.

[0076] In an example embodiment, the workflow management area can be configured to store a workflow.

[0077] The modeling component library can be configured to store modeling components, which can be dragged to the main work area.

[0078] The main work area can be configured to edit a process of the production scheduling model.

[0079] The outline view can be configured to display the process of the production scheduling model; for example, a summary of the process of the production scheduling model can be displayed.

[0080] The console can be configured to display warning information or error information in the process of the production scheduling model.

[0081] The technical solutions of the embodiments of the present disclosure are described in detail below through specific examples.

[0082] The production scheduling of the product provided by the embodiments of the present disclosure can include four steps (1) to (4):

[0083] (1) Data preprocessing: cleaning and converting user data to prepare for subsequent scheduling;

[0084] (2) Scheduling modeling: converting the business problem of production scheduling into a mathematical model;

[0085] (3) Solver solving: using a third-party solver to obtain an optimal solution; in an example embodiment, the solver can be a third-party solver or a solver of the system itself;

[0086] (4) Result evaluation: evaluating the optimal result obtained by the solver, which can include equipment utilization evaluation, production continuity evaluation, and input / output balance evaluation.

[0087] In an example embodiment, data preprocessing can include error value filtering, format conversion, and missing value filling. In an example embodiment, error value filtering can filter out obviously incorrect information, such as a production time of 3000 years, which needs to be corrected to the correct time; format conversion can include converting the obtained data format to a unified format, for example, 2024 can be changed to 24 years; and missing value filling can be filled with a median or an average number in the case of no specific numerical value.

[0088] In an example embodiment, the scheduling modeling process can include production task modeling, execution time modeling for each production task, optimization target modeling, and constraint modeling.

[0089] In an example embodiment, the production task modeling can model production tasks for a single production line. Assuming that a production line produces 10 products, the processes of different types of products are usually different, and production of a product usually requires multiple processes, a product batch can include one or more types of products, and one process in a product batch can be a production task. A three-dimensional array A[i][j] can be used to represent the production task, where i represents the ith production task in a product batch, the production task is in the form of a process of a product batch, the number of processes of different product batches can be the same or different, for example, there are 10 product batches in total, and the total number of processes of the 10 product batches is 495, and there are 495 production tasks in total; j represents the jth process of the ith production task in the total processes of the 10 product batches, i.e., which position from 1 to 495 each production task in the 495th production task is arranged. In an example embodiment, a product can be divided into 10 batches, and one batch of products can include multiple products or one product. In an example embodiment, in actual production, if there are multiple product batches, the scheduling position of each product batch can be determined according to the production time sequence of the product batches (usually after completing the production of one product batch, the production of the next product batch is performed), and the scheduling position of multiple production tasks in the same product batch and the scheduling position of each production task in the total production tasks in multiple product batches can be determined according to the production time.

[0090] In an example embodiment, the production tasks are scheduled to be completed as quickly as possible with the least total production time. There can be multiple actual schedules, and the scheduling method with the least time is determined from the multiple scheduling methods through production task modeling.

[0091] In an example embodiment, the scheduling can be scheduling of production tasks in a batch. There can be 10 products in a batch, and the 10 products have multiple processes, and the shortest time for the multiple processes of the 10 products is the final scheduling goal. One process can simultaneously produce one or more products in batches, and the production of the 10 products is scheduled according to the production time to achieve the least production time.

[0092] In an example embodiment, modeling execution time of each production task can include setting start time and end time of executing each production task, using an array S1 to represent start time of the i-th production task (i.e., the i-th process), using an array E1 to represent end time of the i-th production task (i.e., the i-th process), and n to represent total number of production tasks (i.e., total number of processes, i is valued from 1 to n). Start time and end time of the first production task to the n-th production task can be represented by the following arrays:

[0093] S1 = [model.addVar(vtype="I", name="S1[%s]" % (i)) for i in range(n)];

[0094] E1 = [model.addVar(vtype="I", name="E1[%s]" % (i)) for i in range(n)];

[0095] S2 = [model.addVar(vtype="I", name="S2[%s]" % (i)) for i in range(n)];

[0096] E2 = [model.addVar(vtype="I", name="E2[%s]" % (i)) for i in range(n)];

[0097] ...

[0098] Sn = [model.addVar(vtype="I", name="Sn[%s]" % (i)) for i in range(n)];

[0099] En = [model.addVar(vtype="I", name="En[%s]" % (i)) for i in range(n)].

[0100] In an example embodiment, modeling optimization objective can include: setting execution time of the last process as the earliest, i.e., time of completing the last process is the earliest, to be used as the optimal scheduling (the optimal scheduling can be understood as using the least time of processes to improve production efficiency). Modeling optimization objective is as follows:

[0101] model.setObjective(En, "minimize").

[0102] In an example embodiment, the constraint modeling can further include setting each production task to be scheduled only once (i.e., executed only once), and there is only 1 production task scheduled at a certain position, modeled as follows:

[0103] for i in range(n):

[0104] model.addCons(quicksum(A[i][j]for j in range(n))==1);

[0105] model.addCons(quicksum(A[j][i]for j in range(n))==1);

[0106] In an example embodiment, the constraint modeling can further include determining the time duration of each production task, modeled as follows:

[0107] for i in range(n):

[0108] model.addCons(E1[i]-S1[i]-quicksum(L1[j]*A[j][i]for j in range(n))==0);

[0109] model.addCons(E2[i]-S2[i]-quicksum(L2[j]*A[j][i]for j in range(n))==0);

[0110] ...

[0111] model.addCons(En[i]-Sn[i]-quicksum(Ln[j]*A[j][i]for j in range(n))==0)。

[0112] In an example embodiment, the constraint modeling can further include setting the start time of the first production task to be 0, modeled as follows:

[0113] model.addCons(S1[0]==0);

[0114] In an example embodiment, the constraint modeling can further include that each production task starts after the previous production task ends, so that the production times of different production tasks on the same process are staggered, and the execution times of the previous and next production tasks are contiguous, modeled as follows:

[0115] for i in range(n):

[0116] model.addCons(S2[i]-E1[i]>=0);

[0117] model.addCons(S3[i]-E2[i]>=0);

[0118] ...

[0119] model.addCons(Sn[i]-En[i]>=0);

[0120] for i in range(n-1):

[0121] model.addCons(S1[i+1]-E1[i]==0);

[0122] model.addCons(S2[i+1]-E2[i]==0);

[0123] ...

[0124] model.addCons(Sn[i+1]-En[i]==0).

[0125] In an example embodiment, the solver solving can include: after the scheduling business model is built, inputting the model into a third-party solver or a solver of the system itself, and running to obtain a scheduling result.

[0126] In an example embodiment, the equipment utilization in the result evaluation can be divided into two kinds: one is the utilization of each equipment, which can be represented by the proportion of the equipment working time in the natural time; the other is the utilization of each kind of equipment, which can be represented by the average value of the utilization of all equipment of the same type.

[0127] In an example embodiment, the production continuity evaluation in the result evaluation can be evaluated based on the equipment production continuity evaluation method of the cumulative incremental index: for each equipment, if the product type produced by the equipment does not change for each batch, it is marked as 1, and if the next batch still does not change, it is sequentially increased by 1, and if it changes, it is reset to zero; thereby reflecting whether the product type produced by each equipment changes, and the more batches of the same type of product produced, the more points given, reflecting the higher production continuity.

[0128] In the example embodiment, the input / output balance evaluation in the result evaluation can be evaluated by the Gini coefficient material input and product output balance evaluation method. The balance of material input can ensure the stability of material demand and transportation; the balance of product output can ensure the stability of the workload of downstream processes. The daily input of material input can be composed into a vector, and the Gini coefficient of the vector is calculated to reflect the balance of material input; the daily output of product output can be composed into a vector, and the Gini coefficient of the vector is calculated to reflect the balance of product output. In the example embodiment, the larger the Gini coefficient is, the more unbalanced it is.

[0129] In the example embodiment, the production scheduling system of the product can be displayed through a production scheduling interface, as shown in FIG. 2. The production scheduling interface can include a workflow management area, a modeling component library, a main work area, an outline view, a console, etc. The workflow management area is used to store various workflows; the modeling component library stores various modeling components, which can be freely dragged and used by users; the main work area is used to edit the user's scheduling modeling process (i.e., the process of building a production scheduling model); the outline is used to show the process overview of the production scheduling model; and the console is used to display warning and error information in the process of the production scheduling model.

[0130] In the example embodiment, the principle of the production scheduling system of the product is as follows: mathematical programming is to seek the solution that makes the objective function reach the maximum or minimum value under certain constraint conditions. The research field of mathematical programming covers eight aspects: linear programming, nonlinear programming, dynamic programming, integer programming, stochastic programming, multi-objective programming, combinatorial programming, and parameter programming. Among them, parameter programming is a mathematical programming that contains continuous variables, discrete variables and parameters, which is often used to solve multi-objective engineering problems, uncertain scheduling problems, etc. Sometimes the optimization problem requires some variables to be integer variables, then this kind of problem is called integer programming problem.

[0131] Production scheduling belongs to the combinatorial optimization problem, which aims to find the optimal resource allocation scheme, and through reasonable arrangement of production order and time, to achieve the optimization of performance indicators and the optimization of enterprise operation objectives. Production scheduling algorithms are divided into classical optimization algorithms and intelligent optimization algorithms. (1) In the classical optimization algorithm, branch and bound method and cutting plane method are used to solve integer programming problems; feasible direction method and penalty function method are mainly used to solve constrained optimization problems. The advantages of classical optimization algorithm are: mathematical theory foundation program, fast optimization speed, and clear convergence condition; the disadvantages are: high requirements for model, differentiable function, and model meeting the standard form, which is difficult to meet the conditions of actual scheduling problem, and with the increase of problem size, the complexity of such algorithm increases exponentially. (2) Intelligent optimization algorithm includes genetic algorithm, ant colony algorithm, particle swarm algorithm, simulated annealing algorithm, etc. The advantages of intelligent optimization algorithm are: self-intelligent search ability, and ability to adapt to complex scheduling model; the disadvantages are: convergence speed and optimization progress are difficult to grasp, and algorithm parameter selection depends on experience.

[0132] In production scheduling, the mixed integer linear / non-linear programming (MILP / MINLP) scheduling model based on discrete time expression is generally solved by integer programming algorithm. Typical mathematical programming solvers include: scipopt, glpk.

[0133] In the example embodiment, the production scheduling method of the product provided by the embodiment of the present disclosure can reduce labor costs on the one hand. If relying on manual scheduling, the experience requirement for personnel is relatively high, and the planner needs to spend a lot of time and effort, especially when the plan needs to be adjusted temporarily, relying on personnel may not be able to respond in time. On the other hand, the method can improve the utilization rate of equipment. The planner relies on past experience to judge the capacity of the production line when scheduling, and is also limited by past experience, and cannot explore various possibilities like an algorithm, so that a better utilization rate of equipment can be obtained.

[0134] (1) Linear programming (LP): the simplest and basic optimization problem, the objective function and the constraint condition are linear, the independent variable x is a real variable, and the P problem (polynomial time solvable).

[0135] (2) Non-linear programming (NLP): the objective function or the constraint condition is non-linear, for example, a quadratic function.

[0136] (3) Mixed Intage Linear Programming (MILP): variables have integer values, NP-hard problem (exponential algorithm complexity).

[0137] (4) Dynamically Programming (DP): multi-stage decision problem. Markov chain. Typical problems include dynamic inventory control problem, traveling salesman problem, etc.

[0138] (5) Heuristic algorithm: proposed relative to optimization algorithm. The optimal algorithm of a problem obtains the optimal solution of each instance of the problem. Heuristic algorithm refers to an algorithm constructed based on intuition or experience, which gives a feasible solution of each instance of the combinatorial optimization problem to be solved under acceptable cost (referring to calculation time and space), and the deviation degree of the feasible solution from the optimal solution generally cannot be predicted.

[0139] (6) Advanced Planning and Scheduling (APS).

[0140] (7) Flexible Job-shop Scheduling Problem (FJSP) is an extension of the classic JSP, which allows each process to be processed on any of a set of available machines. FJSP is more difficult than traditional JSP because it introduces another decision content in addition to sequencing, namely job path.

[0141] In the example embodiment, the product production scheduling method can be applied to at least part of the structure in the display device, for example, can be applied to the production of display substrate in the display device, and the display device can be any product or component with display function, such as mobile phone, tablet computer, television, display, notebook computer, digital photo frame or navigator, etc.

[0142] The embodiment of the present disclosure provides an electronic device, including a memory and a processor, the memory stores instructions executable by the processor, and the instructions make the processor execute the method of any of the above embodiments when executed by the processor.

[0143] The embodiment of the present disclosure provides a non-transitory computer readable storage medium storing computer instructions, the computer instructions are used to make the computer execute the method of any of the above embodiments.

[0144] The product material management method, the electronic device and the storage medium provided by the embodiments of the present disclosure, in the product material management method, production scheduling is performed according to process information of at least one product, and a production scheduling result is obtained, the production scheduling result includes a process execution sequence of preparing the at least one product; the material stacking sequence of preparing the at least one product is scheduled according to the production scheduling result and material information, and a material stacking scheduling result is obtained, in the material stacking scheduling result, the stacking sequence of at least part of the materials is opposite to the corresponding process execution sequence; the scheme provided by the embodiments of the present disclosure can solve the technical problem that the unreasonable material stacking leads to low production efficiency to a certain extent.

[0145] In the case of no conflict, the features in the embodiments of the present disclosure, that is, the features in the embodiments, can be combined with each other to obtain new embodiments.

[0146] Although the embodiments disclosed by the embodiments of the present disclosure are as above, the content described is only the embodiments adopted for the purpose of facilitating the understanding of the embodiments of the present disclosure, and is not intended to limit the embodiments of the present disclosure. Any person skilled in the art of the present disclosure can make any modification and change in the form and details without departing from the spirit and scope of the embodiments of the present disclosure, but the patent protection scope of the embodiments of the present disclosure shall be subject to the scope defined by the appended claims.

Claims

1. A material management method, comprising: obtaining production information of at least one product, the production information comprising process information associated with at least one process and material information associated with at least one material, each process corresponding to at least one material; scheduling production according to the process information of the at least one product to obtain a production scheduling result, the production scheduling result comprising an execution sequence of the processes for producing the at least one product; scheduling a material stacking sequence for producing the at least one product according to the production scheduling result and the material information to obtain a material stacking scheduling result, in which the stacking sequence of at least part of the materials is opposite to the execution sequence of the corresponding processes.

2. The material management method according to claim 1, wherein, The scheduling production according to the process information of the at least one product comprises: constructing a production scheduling model based on the process information of the at least one product, and solving the production scheduling model to obtain the production scheduling result, the production scheduling model comprising a constraint condition of using the least time to produce the at least one product. The execution sequence of the processes in the production scheduling result is the execution sequence of the processes using the least time to produce the at least one product.

3. The method of claim 2, wherein, The production information further comprises production time, and the constructing a production scheduling model based on the process information of the at least one product comprises: determining a scheduling position of each process according to the production time and the process information, and setting a start time and an end time of each process according to the scheduling position of each process.

4. The method of claim 3, wherein, The constraint condition of using the least time to produce the at least one product comprises: setting the end time of the last process to be the earliest.

5. The method of claim 3, wherein, The constraint condition of the production scheduling model comprises: each process has only one scheduling position, and each scheduling position has only one process.

6. The method of material management according to claim 5, wherein, The constraint condition further comprises: subtracting the start time of each process from the end time of each process to obtain the duration of each process.

7. The method of claim 5, wherein, The constraint condition further comprises: the end time of a previous process is not later than the start time of a next process.

8. The method of claim 2, wherein, The solving the production scheduling model comprises: solving the production scheduling model by a solver to obtain the production scheduling result.

9. The material management method according to any one of claims 1 to 8, wherein, The production information further comprises material storage space information, the material storage space information being associated with material storage spaces, each material storage space corresponding to at least one material and at least one process; The stacking sequence of the at least part of the materials being opposite to the execution sequence of the corresponding processes comprises: in at least one process corresponding to one of the material storage spaces, the material stacking time corresponding to a process executed earlier is later than the material stacking time corresponding to a process executed later.

10. The material management method according to any one of claims 1 to 8, wherein, After obtaining the production scheduling result, the method further comprises: evaluating at least one of device utilization, production continuity, and input-output balance.

11. The method of material management according to claim 10, wherein, The production information further comprises batch information, the batch information comprising device information, product type, and product output information; The evaluating the device utilization comprises: calculating the proportion of the working time of the device corresponding to the device information in natural time to obtain the utilization of each device. The evaluation of the production continuity comprises: for the same equipment corresponding to the equipment information, if the product type of the current product batch is consistent with the product type of the last product batch, increasing the value of the continuity identifier by 1, and if the product type of the current product batch is inconsistent with the product type of the last product batch, setting the value of the continuity identifier to 0; and evaluating the production continuity according to the value of the continuity identifier. The evaluation of the input-output balance comprises: forming a daily input vector by using the daily input amount in the material information, calculating the Gini coefficient of the daily input vector to evaluate the input balance; and forming a daily output vector by using the daily output amount in the product output information, calculating the Gini coefficient of the daily output vector to evaluate the output balance.

12. The method of material management of claim 11, wherein, The evaluation of the equipment utilization rate further comprises: calculating the average value of the utilization rates of all equipment of the same type to obtain the utilization rate of each type of equipment.

13. The method of material management according to any one of claims 2 to 8, wherein, The production scheduling model is constructed based on the process information of the at least one product, and further comprises: displaying a production scheduling interface, the production scheduling interface comprising a workflow management area, a modeling component library, a main work area, an outline view, and a console; wherein: The workflow management area is configured to store a workflow; The modeling component library is configured to store modeling components, and the modeling components can be dragged to the main work area; The main work area is configured to edit the process of the production scheduling model; The outline view is configured to display the process of the production scheduling model; The console is configured to display warning information or error information in the process of the production scheduling model. 14.An electronic device, comprising a memory and a processor, wherein the memory stores instructions executable by the processor, and the instructions, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 13. 15.A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform the method according to any one of claims 1 to 13.

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