An electronic product manufacturing process batch method, device, equipment, and program product

Abstract

The present invention discloses a method, device, equipment and program product for batch grouping of electronic product manufacturing processes, which relates to the field of production planning and scheduling, and is used to improve the resource utilization rate of an electronic product production workshop and reduce production costs. Based on historical scheduling information, the present invention uses a hyper-heuristic method to divide all production tasks into product sub-batch tasks and process sub-batch tasks, calculates the grouped batches for each process of each product sub-batch task, and divides each process of each production task into the corresponding grouped batches to complete the grouped batch operation. The present invention solves the problems of complex processing processes of complex electronic products, long process preparation time, low production efficiency and low resource utilization rate caused by frequent switching of manufacturing resources in mixed-line production of multiple varieties.

Description

Technical Field

[0001] The present invention relates to the field of production planning and scheduling, and in particular to a method, device, equipment and program product for batch grouping of electronic product manufacturing processes. Background Art

[0002] Complex electronic product production workshops are typical multi-variety and variable-batch production models, which are characterized by frequent technological iterations, tight manufacturing cycles, complex technological processes, and multi-variety mixed-line production. To improve production efficiency and reduce production costs, complex electronic product manufacturing enterprises often use batch processing methods to process production tasks, that is, using the same manufacturing resources (human resources, instruments, workstations, tooling fixtures, etc.) to produce multiple sets of products simultaneously (that is, multiple production tasks are carried out simultaneously) to reduce the adjustment frequency of manufacturing resources and reduce manufacturing costs. For example, semiconductor chip pre-burning treatment is a typical batch processing process. In this production mode, it is necessary to group products based on the parallel processing capabilities of manufacturing resources, and divide production tasks into multiple sub-batch tasks. The quality of batch grouping directly affects the production cycle and processing costs, and too large or too small a scale of sub-batch tasks will increase the manufacturing period.

[0003] In existing batch grouping methods, they are divided into methods for flow shops, job shops, and multi-machine parallel processing according to different processing flows, and the batch grouping problem and the shop scheduling problem are often solved collaboratively. The research on such problems mainly focuses on operation sequencing optimization and equipment allocation, and lacks in-depth research on batch grouping methods. Usually, it is necessary to first model the batch grouping process into a complex mathematical model, and then use operations research optimization methods to solve it, and the processing capacity constraints of manufacturing resources are less considered, so it has weak practicality in the actual production planning and management process. Summary of the Invention

[0004] The invention objective of the present invention is: aiming at all or part of the above-mentioned problems, to provide a method, device, equipment and program product for batch grouping of electronic product manufacturing processes, which can, based on prior knowledge, under the constraints of workshop resources and production processes, realize the batch scheduling of production tasks of electronic products at the operation level, so as to improve the resource utilization rate of electronic product production workshops and reduce production costs.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for batch grouping of electronic product manufacturing processes, which includes:

[0007] Obtain production task information, process information of products, and workstation information;

[0008] Based on historical scheduling information, use a hyper-heuristic method to select a first heuristic rule for product batch grouping and a second heuristic rule for operation batch grouping from a benchmark heuristic rule library;

[0009] For all production tasks, use the first heuristic rule to divide the product sub-batch tasks and use the second heuristic rule to divide the process sub-batch tasks;

[0010] Based on the results of the product sub-batch task division and the process sub-batch task division, calculate the grouped batches for each process of each product sub-batch task; divide each process of each production task into the corresponding grouped batches.

[0011] Further, using the first heuristic rule to divide the product sub-batch tasks includes:

[0012] Detect whether there is a new production task from the obtained production task information;

[0013] If so, according to the first heuristic rule, add the production task to the currently existing product sub-batch task and update the task quantity of the product sub-batch task; or add the production task to the newly created product sub-batch task and initialize the task quantity of the newly created product sub-batch task;

[0014] If not, set the maximum batch quantity for each product sub-batch task respectively.

[0015] Further, using the second heuristic rule to divide the process sub-batch tasks includes:

[0016] According to the obtained process information and station information, respectively determine the first maximum batch quantity that can be processed in parallel simultaneously for each process of each production task;

[0017] Based on the first maximum batch quantity, calculate the second maximum batch quantity that can be processed in parallel simultaneously for each process segment according to the process segment where each process is located;

[0018] Adjust the second maximum batch quantity according to the second heuristic rule.

[0019] Further, adjusting the second maximum batch quantity according to the second heuristic rule includes:

[0020] Use the second heuristic rule to configure the minimum quantity that can be processed in parallel simultaneously for some or all process segments;

[0021] For the process segments configured with the minimum quantity that can be processed in parallel simultaneously, when the calculated second maximum batch quantity is lower than the configured minimum quantity, update the second maximum batch quantity with the configured minimum quantity.

[0022] Further, the calculating the grouped batches for each process of each product sub-batch task based on the results of the product sub-batch task division and the process sub-batch task division includes:

[0023] Calculate the number of grouped batches required for each process of each product sub-batch task according to the maximum batch size of each product sub-batch task and the adjusted second maximum batch size, and divide the grouped batches for each process of each product sub-batch task based on this number of grouped batches.

[0024] Further, divide each process of each production task into corresponding grouped batches, including:

[0025] Arrange each production task in each process of each product sub-batch task in sequence;

[0026] Write each sorted production task in sequence into each grouped batch divided by the process it belongs to. Among them, after the number of written tasks in each grouped batch reaches the adjusted second maximum batch size, write the next production task into the next grouped batch.

[0027] Further, the benchmark heuristic rules included in the benchmark heuristic rule library include the Shortest Processing Time (SPT) principle of the same progress, the Same Type (ST) principle, the Same Due Date (SD) principle, the Same Production Line (SL) principle, the principle of batch division by process stage (JP), the principle of batch division by product model (PID), the principle of batch division by product type (PT), and the principle of batch division by product quantity (PA); the first heuristic rule and the second heuristic rule are each composed of at least one benchmark heuristic rule.

[0028] The present invention also provides an electronic product manufacturing process batch grouping device, which includes:

[0029] A first module for obtaining production task information, process information of products, and station information;

[0030] A second module for selecting, based on historical scheduling information and using a hyper-heuristic method, a first heuristic rule for product grouped batches and a second heuristic rule for process grouped batches from the benchmark heuristic rule library;

[0031] A third module for dividing product sub-batch tasks using the first heuristic rule and dividing process sub-batch tasks using the second heuristic rule for all production tasks;

[0032] A fourth module for calculating the grouped batches of each process of each product sub-batch task based on the product sub-batch task division result and the process sub-batch task division result; and dividing each process of each production task into the corresponding grouped batches.

[0033] The present invention also provides an electronic product manufacturing process batch grouping equipment, which includes a processor and a storage medium. A computer program is stored in the storage medium, and the processor is signal-connected to the storage medium. When the processor runs the computer program, it can execute the above-mentioned electronic product manufacturing process batch grouping method.

[0034] On the other hand, the present invention also provides a computer program product, including a computer program which, when run by a processor, executes the above-mentioned method for grouping batches of electronic product manufacturing processes.

[0035] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are as follows:

[0036] In view of the characteristics of complex integration processes, high resource reusability, and diverse product models of electronic products in this application, by using the prior knowledge of experts learned and summarized from historical scheduling information, each process of each production task is grouped in batches at the product level and process level, realizing the process-level scheduling of complex electronic product production tasks under strict resource constraints, solving the problems of complex processing processes of complex electronic products, long process preparation time, low production efficiency, and low resource utilization rate caused by frequent switching of manufacturing resources in mixed-line production of multiple varieties, improving the utilization rate of workshop resources and production efficiency, and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be described by way of examples with reference to the accompanying drawings, where:

[0038] Figure 1 is a flowchart of the method for grouping batches of electronic product manufacturing processes provided by an embodiment of the present application.

[0039] Figure 2 is a flowchart of the execution of the hyper-heuristic strategy in an embodiment of the present application.

[0040] Figure 3 is a flowchart of the division of product sub-batch tasks in an embodiment of the present application.

[0041] Figure 4 is a flowchart of the division of process sub-batch tasks in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] All features disclosed in this specification, or all steps in any disclosed method or process, except for mutually exclusive features and / or steps, can be combined in any manner.

[0043] Any feature disclosed in this specification (including any additional claims, abstract) can be replaced by other equivalent or similar-purpose alternative features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only an example of a series of equivalent or similar features.

[0044] In view of the problems that the existing grouping batch method has weak practical value and poor applicability to the electronics product manufacturing workshop with complex process, the embodiments of this application provide a grouping batch method, device, equipment and program product for electronics product manufacturing processes, aiming to overcome the deficiencies of increased non-operation time of processes caused by frequent adjustment of manufacturing resources in the production mode of multi-variety and variable batch of complex electronics products, resulting in reduced production efficiency, increased manufacturing costs and low resource utilization rate, so as to improve the resource utilization rate and production efficiency of the electronics product manufacturing workshop and reduce production costs.

[0045] The embodiments of this application provide a grouping batch method for electronics product manufacturing processes, as Figure 1 shown, this method includes the following processes:

[0046] S1. Obtain production task information, process information of products and station information.

[0047] The production task information indicates all the production tasks that the electronics product manufacturing workshop is currently or planned to carry out, such as all the production tasks to be carried out on a certain day or a certain period of time. The production task information includes the quantity of products to be produced, product models, production progress, delivery date, etc. The production task information can be obtained from the order management system.

[0048] The process information indicates the production process of the product, and different products have different production processes. The process information includes the number of processes, process names, process segments, station requirements, etc. The process information can be obtained from the process management system.

[0049] The station information indicates the station resource information of the workshop. The station information includes station types, the number of stations, applicable models, the number of products that can be processed in parallel (i.e., the number of products that can be produced in parallel), etc. The station information can be obtained from the resource management system.

[0050] For example, as shown in Table 1 is the production task information on a certain date date. On this date, it is planned to process two types of products, the product models are K0001 and K0002 respectively, and there are a total of 16 sets of production tasks for the two types of products. Among them, there are 8 sets of products of model K0001, and the product numbers are SER023 - SER030 in sequence. There are 8 sets of products of model K0002, and the product numbers are SER031 - SER038 in sequence.

[0051] Table 1 Production task information table of the workshop on date date

[0052]

[0053] The process information of K0001 and K0002 is shown in Table 2.

[0054] Table 2 Process information table

[0055]

[0056] Table 3 shows the workstation information table of the workshop.

[0057] Table 3 Workstation Information Table

[0058]

[0059] S2. Based on the historical scheduling information, using the hyper-heuristic method, select the first heuristic rule for product group batching and the second heuristic rule for process group batching from the benchmark heuristic rule library.

[0060] The benchmark heuristic rule library stores a variety of benchmark heuristic rules for selection or combination during group batching.

[0061] As an optional implementation method, the benchmark heuristic rules included in the benchmark heuristic rule library include the Shortest Processing Time (SPT) principle of the same schedule, the Same Type (ST) principle, the Same Due Date (SD) principle, the Same Production Line (SL) principle, the principle of batch by process stage (JP), the principle of batch by product model (PID), the principle of batch by product type (PT), and the principle of batch by product quantity (PA), as shown in Table 4.

[0062] Table 4 Detailed List of Benchmark Heuristic Rule Library

[0063]

[0064] As Figure 2 shown, by obtaining the historical scheduling information and using the hyper-heuristic method, automatically select one or more benchmark heuristic rules from the benchmark heuristic rules included in the benchmark heuristic rule library to obtain a heuristic rule combination suitable for different sub-batch task division purposes. Among them, it includes the first heuristic rule for product group batching and the second heuristic rule for process group batching. The first heuristic rule and the second heuristic rule are each composed of at least one benchmark heuristic rule.

[0065] Table 5 shows the first heuristic rule and the second heuristic rule for each production task obtained according to the historical scheduling information.

[0066] Table 5 Heuristic Rule Combination Table

[0067]

[0068] S3. For all production tasks, use the first heuristic rule to divide the product sub-batch tasks and use the second heuristic rule to divide the process sub-batch tasks.

[0069] As an optional implementation method, the above-mentioned use of the first heuristic rule to divide the product sub-batch tasks includes:

[0070] Detect whether there is a new production task based on the obtained production task information;

[0071] If so, according to the first heuristic rule, add the production task to the existing product sub-batch task, and update the task quantity of the product sub-batch task; or add the production task to a newly created product sub-batch task, and initialize the task quantity of the newly created product sub-batch task;

[0072] If not, set the maximum batch quantity of each product sub-batch task respectively.

[0073] As Figure 3 shown, in some feasible implementation manners, the process of dividing product sub-batch tasks includes:

[0074] S31. Detect production task information. After detecting a new production task, judge whether a new product sub-batch task needs to be created according to the first heuristic rule. If it is not necessary to create a new one, add the production task to the existing product sub-batch task i, , where n is the total quantity of product sub-batch tasks, and increase the task quantity of the sub-batch task i by 1; if it is necessary to create a new one, go to step S32. If no new production task is detected, go to step S33.

[0075] In some feasible implementation manners, for a new production task, according to the product model, production progress, and delivery date indicated by the production task information, use the first heuristic rule to identify all product sub-batch tasks to determine whether to write the new production task into an existing product sub-batch task or create a new product sub-batch task for it. For example, for the production task of model K0001 with product number SER023, a new product sub-batch task BA001 is created. When the production task with product number SER024 is detected, according to its product model, production progress, and delivery date, it is found that it is the same as the existing production tasks in sub-batch task BA001, so it is added to product sub-batch task BA001. For the production task with product number SER026, although its product model and delivery date are the same as those in product sub-batch task BA001, its production progress has reached process 5. According to the first heuristic rule, a new product sub-batch task with sub-batch number BA002 is created for it. When it comes to the production task with product number SER031, its product model is K0002, which is different from the product models of the existing product sub-batch tasks, so a new product sub-batch task with sub-batch number BA003 is created for it.

[0076] ​S32. Create a sub-batch task for the product type belonging to the production task according to the product type of the production task, generate a sub-batch number for this product sub-batch task, record the product type, product number, product model, delivery date, etc. of this production task, and initialize the task quantity of the newly created product sub-batch task as 1.

[0077] S33. Record the task quantity of each product sub-batch task , and set the maximum batch quantity of each product sub-batch task .

[0078] As shown in Table 6, the product sub-batch tasks divided for the above production tasks are a total of 3 product sub-batch tasks, and the sub-batch numbers are BA001, BA002, and BA003 respectively.

[0079] Table 6 Product Sub-batch Task Division Table

[0080]

[0081] For the division of process sub-batch tasks, as an optional implementation method, it includes the following process:

[0082] According to the obtained process information and station information, determine the first maximum batch quantity that can be processed in parallel for each process of each production task respectively;

[0083] Based on the first maximum batch quantity, calculate the second maximum batch quantity that can be processed in parallel for each process segment from the process segments where each process is located;

[0084] Adjust the second maximum batch quantity according to the second heuristic rule.

[0085] In some feasible implementation methods, as Figure 4 shown, the process of dividing process sub-batch tasks includes:

[0086] S34. According to the station requirements of each process, screen out the available stations for each process from the station information according to "station type - product model", and determine the first maximum batch quantity of each process according to the number of processes that can be processed in parallel by the available stations, as shown in Table 3 , where j represents the process sequence number.

[0087] S35. According to the processing route of the production task, obtain the process segment information where each process is located, and calculate the second maximum batch quantity that can be processed in parallel for each process segment according to the first maximum batch quantity of each process determined in step S34 , there is , where L represents the process segment, represents the number of process segments in the product sub-batch task i, represents the task quantity of the product sub-batch task i, It represents finding the maximum value of the first maximum batch quantity for each process j in process section L of product sub-batch task i. of the maximum value.

[0088] As shown in Table 7, the first maximum batch quantity calculated for each process of production tasks of model K0001 and model K0002 and the second maximum batch quantity of the corresponding process section .

[0089] Table 7 Maximum Batch Quantity Table

[0090]

[0091] S36. Adjust the second maximum batch quantity according to the second heuristic rule .

[0092] In some feasible embodiments, for the second maximum batch quantity the adjustment methods include:

[0093] Using the second heuristic rule, configure the minimum number of processes that can be processed in parallel simultaneously for some or all process sections; for the process sections configured with the minimum number of processes that can be processed in parallel simultaneously, when the calculated second maximum batch quantity is lower than the configured minimum number, update the second maximum batch quantity with the configured minimum number.

[0094] For example, for the assembly stage and debugging stage of model K0001, set coefficient a to indicate the minimum number of processes that can be processed in parallel for these two process sections. Assuming a = 6, there is an adjustment strategy table for the second maximum batch quantity as shown in Table 8.

[0095] Table 8 Second Maximum Batch Quantity Adjustment Strategy Table

[0096]

[0097] It can also be seen from Table 8 that for the adjustment method of the second maximum batch quantity, it can also include:

[0098] Using the second heuristic rule, update the second maximum batch quantity of some or all process sections to the maximum batch quantity of the corresponding product sub-batch task i .

[0099] Finally, through the above adjustment methods, the adjustment results of the second maximum batch quantity for each process section are shown in Table 7.

[0100] S4. Based on the product sub-batch task division result and the process sub-batch task division result, calculate the grouped batch for each process of each product sub-batch task; divide each process of each production task into the corresponding grouped batch.

[0101] As an alternative implementation, calculating the grouped batches for each process of each product sub-batch task based on the product sub-batch task division result and the process sub-batch task division result includes:

[0102] S41. According to the maximum batch quantity of each product sub-batch task (or ) and the adjusted second maximum batch quantity , calculate the number of grouped batches required to be divided for each process of each product sub-batch task , and divide the grouped batches for each process of each product sub-batch task according to the number of grouped batches .

[0103] For example, for process 1 (belonging to the first process segment) in sub-batch number BA001 (the first product sub-batch task), it includes 3 production tasks for product numbers SER023 - SER025, that is, the maximum batch quantity of its product sub-batch task is 3, and the adjusted second maximum batch quantity of this process 1 is 6. According to , where represents rounding up for , then , indicating that the number of grouped batches for process 1 of sub-batch number BA001 is 1. Similarly, the number of grouped batches for processes 5 and 6 in sub-batch number BA001 (in the test stage, the maximum batch quantity of the product sub-batch task is 5, and the adjusted second maximum batch quantity is 4) can be calculated as 2.

[0104] After dividing the grouped batches for each process of each product sub-batch task, add the corresponding process of each production task to the corresponding grouped batch, and then the grouping of all production tasks is completed.

[0105] In some feasible implementations, the method of dividing each process of each production task into the corresponding grouped batch includes:

[0106] S42. Arrange each production task in each process of each product sub-batch task in sequence.

[0107] For each production task indicated by the previous production task information, after performing product sub-batch division, according to the processing route indicated by the process information, in the logical order of each process, sort each production task in ascending order of product number in each process (usually, the earlier the production task, the smaller the product number).

[0108] S43. Write each sorted production task sequentially into each grouped batch divided for the process where it is located. Among them, after the number of written tasks in each grouped batch reaches the adjusted second maximum batch quantity, write the next production task into the next grouped batch.

[0109] For all processes of sub-batch number BA001, processes 1-4 and process 7 of sub-batch number BA002, and all processes of sub-batch number BA003, since the number of grouped batches is only 1 for each, all production tasks in the product sub-batch tasks can be respectively divided into this only 1 grouped batch. For processes 5 and 6 of sub-batch number BA002, there are 2 grouped batches, and the maximum number of products that can be processed simultaneously in each grouped batch is the adjusted second largest batch quantity (i.e., 4). Then, according to the order, the first 4 production tasks (product numbers SER026 - SER029) in sub-batch number BA002 are assigned to the first grouped batch. The remaining production task in this product sub-batch task is only product number SER030, which is less than 4, so the remaining production task is all assigned to the second grouped batch. Finally, the grouped batch results shown in Table 9 are obtained.

[0110] Table 9 Grouped Batch Result Table

[0111]

[0112] According to the idea of this application, in an embodiment of this application, an electronic product manufacturing process grouping batch device is further provided, which includes:

[0113] A first module, configured to obtain production task information, process information of products, and station information.

[0114] A second module, configured to select a first heuristic rule for product grouped batches and a second heuristic rule for process grouped batches from a benchmark heuristic rule library based on historical scheduling information by using a hyper-heuristic method.

[0115] A third module, configured to divide product sub-batch tasks by using the first heuristic rule and divide process sub-batch tasks by using the second heuristic rule for all production tasks.

[0116] A fourth module, configured to calculate the grouped batches of each process of each product sub-batch task based on the product sub-batch task division result and the process sub-batch task division result; divide each process of each production task into the corresponding grouped batch.

[0117] The features configured in the first module, the second module, the third module, and the fourth module in the above device can be correspondingly referred to the steps S1, S2, S3, and S4 in the embodiment of the electronic product manufacturing process grouping batch method described above.

[0118] On the other hand, an equipment for batch processing of electronic product manufacturing processes is also provided in an embodiment of the present application. The equipment includes a processor and a storage medium. A computer program is stored in the storage medium, and the processor is in signal connection with the storage medium. When the processor runs the computer program, the method for batch processing of electronic product manufacturing processes in the above embodiment can be executed.

[0119] In addition, a computer program product is also provided in an embodiment of the present application, including a computer program. When the computer program is run by a processor, the method for batch processing of electronic product manufacturing processes in the above embodiment is executed.

[0120] The present invention is not limited to the foregoing specific embodiments. The present invention extends to any new feature or any new combination disclosed in this specification, as well as any new combination of steps of any new method or process disclosed.

Claims

1. A method for batch processing of an electronic product manufacturing process, characterized in that, Including: Obtaining production task information, process information of products, and station information; Based on historical scheduling information, using a hyper-heuristic method to select a first heuristic rule for product grouping batches and a second heuristic rule for process grouping batches from a benchmark heuristic rule library; For all production tasks, using the first heuristic rule to perform product sub-batch task division, including: detecting whether there is a new production task by the obtained production task information; if so, according to the first heuristic rule, adding the production task to the currently existing product sub-batch task and updating the task quantity of the product sub-batch task; or adding the production task to a newly created product sub-batch task and initializing the task quantity of the newly created product sub-batch task; if not, respectively setting the maximum batch quantity of each product sub-batch task; using the second heuristic rule to perform process sub-batch task division, including: respectively determining the first maximum batch quantity that can be simultaneously and parallelly processed for each process of each production task according to the obtained process information and station information; based on the first maximum batch quantity, calculating the second maximum batch quantity that can be simultaneously and parallelly processed for each process segment by the process segment where each process is located; adjusting the second maximum batch quantity according to the second heuristic rule, including: using the second heuristic rule to configure the minimum quantity that can be simultaneously and parallelly processed for some or all process segments, and for the process segments with the configured minimum quantity that can be simultaneously and parallelly processed, when the calculated second maximum batch quantity is lower than the configured minimum quantity, updating the second maximum batch quantity with the configured minimum quantity; Based on the product sub-batch task division result and the process sub-batch task division result, calculating the grouping batches for each process of each product sub-batch task, including: calculating the number of grouping batches required to be divided for each process of each product sub-batch task according to the maximum batch quantity of each product sub-batch task and the adjusted second maximum batch quantity, and dividing the grouping batches for each process of each product sub-batch task according to the number of grouping batches; dividing each process of each production task into the corresponding grouping batches.

2. The method for batch processing of electronic product manufacturing processes according to claim 1, wherein Dividing each process of each production task into the corresponding grouping batches, including: Sequentially arranging each production task in each process of each product sub-batch task; Sequentially writing the sorted each production task into each grouping batch divided by the process where it is located, wherein, after the writing quantity of each grouping batch reaches the adjusted second maximum batch quantity, writing the next production task into the next grouping batch.

3. The method for batch processing of electronic product manufacturing processes according to claim 1, wherein The benchmark heuristic rules included in the benchmark heuristic rule library include the Shortest Processing Time (SPT) principle of the same progress, the Same Type (ST) principle of the same model, the Same Delivery Date (SD) principle, the Same Production Line (SL) principle, the principle of batch by process stage (JP), the principle of batch by product model (PID), the principle of batch by product type (PT), and the principle of batch by product quantity (PA); the first heuristic rule and the second heuristic rule are respectively composed of at least one benchmark heuristic rule.

4. An electronic product manufacturing process batch device, characterized in that, Including: A first module for obtaining production task information, process information of products, and station information; A second module, configured to select, based on historical scheduling information and by using a hyper-heuristic method, a first heuristic rule for grouping batches of products and a second heuristic rule for grouping batches of processes from a benchmark heuristic rule library; A third module, configured to, for all production tasks, use the first heuristic rule to divide product sub-batch tasks, including: detecting, by using the obtained production task information, whether there is a new production task; if so, adding the production task to the currently existing product sub-batch task according to the first heuristic rule, and updating the task quantity of the product sub-batch task; or adding the production task to a newly created product sub-batch task and initializing the task quantity of the newly created product sub-batch task; if not, respectively setting the maximum batch quantity of each product sub-batch task; using the second heuristic rule to divide process sub-batch tasks, including: determining, according to the obtained process information and station information, a first maximum batch quantity that can be simultaneously and parallelly processed for each process of each production task; calculating, based on the first maximum batch quantity and according to the process segments where each process is located, a second maximum batch quantity that can be simultaneously and parallelly processed for each process segment; adjusting the second maximum batch quantity according to the second heuristic rule, including: using the second heuristic rule to configure the minimum quantity that can be simultaneously and parallelly processed for some or all process segments, and for a process segment configured with the minimum quantity that can be simultaneously and parallelly processed, when the calculated second maximum batch quantity is lower than the configured minimum quantity, updating the second maximum batch quantity with the configured minimum quantity; A fourth module, configured to calculate, based on the results of dividing product sub-batch tasks and process sub-batch tasks, the grouped batches of each process of each product sub-batch task, including: calculating, according to the maximum batch quantity of each product sub-batch task and the adjusted second maximum batch quantity, the number of grouped batches required to be divided for each process of each product sub-batch task, and dividing the grouped batches for each process of each product sub-batch task according to the number of grouped batches; dividing each process of each production task into the corresponding grouped batches.

5. An electronic product manufacturing process batch equipment, characterized in that, It includes a processor and a storage medium, where a computer program is stored in the storage medium, the processor is signal-connected to the storage medium, and when the processor runs the computer program, it can execute the method for grouping batches in an electronic product manufacturing process according to any one of claims 1-3.

6. A computer program product comprising a computer program, characterized in that, When the computer program is run by the processor, it executes the method for grouping batches in an electronic product manufacturing process according to any one of claims 1-3.

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