Dispatching method and device, storage medium and electronic equipment

Abstract

The invention discloses a dispatching method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring production task information; based on the production task information, utilizing a genetic algorithm to calculate the shortest processing period of a first station, and according to a calculation result, determining a product batch distribution and sorting mode corresponding to each device in the first station and outputting the product batch distribution and sorting mode; and based on the production task information, utilizing a genetic algorithm to calculate the shortest processing cycle of the first station and the second station, and according to a calculation result, determining a product batch distribution and sorting mode of each device in the second station and outputting the product batch distribution and sorting mode. By the adoption of the scheme, workers can be dispatched more reasonably, so that the production efficiency is improved, and meanwhile the product quality requirement is met.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a work dispatching method and device, a storage medium, and an electronic device. Background Art

[0002] Semiconductor production workshops have complex production processes and a wide variety of equipment, which involve different production conditions and process requirements. Different products have different production conditions, and different equipment groups require different production parameters. If the same type of products can be processed in the same batch, the waste of production resources can be greatly reduced.

[0003] However, the actual situation on the production line is complicated, and due to the control of product quality, products need to be put into production as soon as possible to reduce waiting. As a result, products cannot always be fully batched and produced. Equipment needs to frequently debug different parameters to adapt to product needs, which ultimately leads to reduced production efficiency and waste of production resources.

[0004] Therefore, how to assign work scientifically to improve production efficiency while meeting product quality requirements has become an urgent problem to be solved. Summary of the invention

[0005] The problem to be solved by the present invention is: how to assign work more reasonably to improve production efficiency while meeting product quality requirements.

[0006] To solve the above problem, an embodiment of the present invention provides a method for dispatching work, the method comprising:

[0007] Obtain production task information;

[0008] Based on the production task information, a genetic algorithm is used to calculate the shortest processing cycle of the first site, and according to the calculation result, the product batch allocation and sorting method corresponding to each device in the first site is determined and output, and the first site is a site that needs to split the product batch of the previous site for parallel production;

[0009] Based on the production task information, a genetic algorithm is used to calculate the shortest processing cycles of the first site and the second site, and according to the calculation results, the product batch allocation and sorting method of each equipment in the second site is determined and output. The second site is a site that needs to combine the product batches of the first site for production.

[0010] Optionally, the production task information includes:

[0011] Product category information;

[0012] Product batch information of the previous site;

[0013] Batch quantity information before product batch splitting;

[0014] Batch quantity information after product batches are split;

[0015] The longest waiting time for each batch at the previous station and the first station;

[0016] Information on the number of equipment available for production at the first site and the second site;

[0017] Information on the time required to switch processes between different products;

[0018] And information on the time required to process various types of products.

[0019] Optionally, the calculating the shortest processing cycle of the first site by using a genetic algorithm based on the production task information, and determining the product batch allocation and sorting method of each device in the first site according to the calculation result, includes:

[0020] Randomly assign and sort the split product batches as the first initial population;

[0021] Calculate the processing cycle of the first station under random allocation and sorting;

[0022] Re-allocate and sort the split product batches, and calculate the processing cycle of the first station under each allocation and sorting, until a first preset number of iterations is reached;

[0023] The product batch allocation and sorting method corresponding to the shortest processing cycle of the first station within the first preset number of iterations is used as the product batch allocation and sorting method for each device in the first station.

[0024] Optionally, the calculating the shortest processing cycles of the first site and the second site by using a genetic algorithm based on the production task information, and determining the product batch allocation and sorting method of each device in the second site according to the calculation result, includes:

[0025] According to the completion order of each product batch in the first station, the product batches of the first station are combined as a second initial population;

[0026] Calculating the processing cycles of the first site and the second site under the second initial population;

[0027] Recombining the product batches in the first station, and calculating the processing cycles of the first station and the second station under each combination until a second preset number of iterations is reached;

[0028] The product batch combination and sorting method corresponding to the shortest processing cycle of the first station and the second station within the second preset number of iterations is used as the product batch allocation and sorting method for each device in the second station.

[0029] Optionally, in the process of calculating the shortest processing cycle of the first station and the second station by using the genetic algorithm, the process further includes:

[0030] When the first preset condition is met, the determined product batch allocation and sorting method corresponding to each device in the first site is used as the first initial population, and a genetic algorithm is used to redetermine the product batch allocation and sorting method corresponding to each device in the first site.

[0031] Optionally, the method further includes: storing product batch allocation and sorting methods corresponding to each device in the first site and the second site.

[0032] The embodiment of the present invention further provides a work dispatching device, the device comprising:

[0033] A data acquisition unit, adapted to acquire production task information;

[0034] The first dispatching unit is adapted to calculate the shortest processing cycle of the first site by using a genetic algorithm based on the production task information, and determine the product batch allocation and sorting method corresponding to each device in the first site according to the calculation result, wherein the first site is a site that needs to split the product batch of the previous site for parallel production;

[0035] The second dispatching unit is adapted to calculate the shortest processing cycle of the first site and the second site by using a genetic algorithm based on the production task information, and determine the product batch allocation and sorting method of each device in the second site according to the calculation result, wherein the second site is a site that needs to combine the product batches of the first site for production;

[0036] The output unit is adapted to output the product batch allocation and sorting method corresponding to each device in the first site and the second site.

[0037] Optionally, the device also includes: an adjustment unit, which is suitable for using a genetic algorithm to re-determine the product batch allocation and sorting method corresponding to each device in the first site when a first preset condition is met during the process of calculating the shortest processing cycle of the first site and the second site using a genetic algorithm, using the determined product batch allocation and sorting method corresponding to each device in the first site as the initial population, and using a genetic algorithm to re-determine the product batch allocation and sorting method corresponding to each device in the first site.

[0038] Optionally, the device further comprises:

[0039] The storage unit is adapted to store the product batch allocation and sorting methods corresponding to each device in the first site and the second site.

[0040] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. The computer program is executed by a processor to implement the steps of any of the above methods.

[0041] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and the processor performs the steps of any of the above methods when running the computer program.

[0042] Compared with the prior art, the technical solution of the embodiment of the present invention has the following advantages:

[0043] By applying the solution of the present invention, based on the obtained production task information, a genetic algorithm is used to calculate the shortest processing cycle of the first site, and the product batches corresponding to the shortest processing cycle are allocated and sorted to perform parallel scheduling of each device in the first site. At the same time, a genetic algorithm is used to calculate the shortest processing cycles of the first site and the second site, and the product batches corresponding to the shortest processing cycle are allocated and sorted to perform group batch scheduling of each device in the second site. Since the way of scheduling each device in the first site and the second site will make the processing cycle of the first site and the second site the shortest, the production efficiency can be improved. Moreover, based on the production task information, the scheduling of the first site and the second site can meet the production task requirements, that is, meet the product quality requirements. In this way, by adopting the solution of the present invention, it is possible to meet product quality requirements while improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of a method for dispatching work in an embodiment of the present invention;

[0045] Figure 2 is a flow chart of a method for determining product batch allocation and sorting of each device in a first site and a second site by using a genetic algorithm in an embodiment of the present invention;

[0046] Figure 3 is a schematic diagram of the structure of each station in a manufacturing system according to an embodiment of the present invention;

[0047] Figure 4 It is a structural schematic diagram of a work dispatching device in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In the current actual dispatching, it mainly depends on the arrival time of the product, and the first-input first-output (FIFO) rule is usually adopted for dispatching. At the same time, in order to prevent the waiting time of the product from exceeding the Q-time and causing quality accidents, a more conservative strategy is generally adopted to put the product online in time. In the process of balancing with production efficiency, it is more inclined to maintain the quality target and sacrifice more production efficiency. Ultimately, it leads to reduced production efficiency and waste of production resources.

[0049] In view of this problem, the present invention provides a method for dispatching work. The solution of the present invention is adopted. Based on the obtained production task information, a genetic algorithm is used to calculate the shortest processing cycle of the first site, and the product batches corresponding to the shortest processing cycle are allocated and sorted, and the equipment in the first site is scheduled in parallel. At the same time, a genetic algorithm is used to calculate the shortest processing cycles of the first site and the second site, and the product batches corresponding to the shortest processing cycle are allocated and sorted, and the equipment in the second site is scheduled in batches. In this way, the production efficiency can be improved while meeting the product quality requirements.

[0050] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0051] Reference Figure 1 , an embodiment of the present invention provides a method for dispatching work, which may include the following steps:

[0052] Step 11, obtain production task information.

[0053] In the actual product manufacturing process, semiconductor raw materials undergo multiple processes to form the final semiconductor product. Each process may be performed by one device or by more than two devices. A group of devices that perform the same process is called a site. Semiconductor raw materials are processed by multiple sites in sequence to obtain the final semiconductor product.

[0054] Among all the sites, there is usually only one site that needs to split the product batch of the previous site for parallel production. In the embodiment of the present invention, the site that needs to split the product batch of the previous site for parallel production is called the first site. The site after the first site usually needs to combine the product batch of the first site for production. In the embodiment of the present invention, the site that needs to combine the product batch of the first site for production is called the second site. Except for the first site and the second site, the other sites usually have the same product batch as the previous site.

[0055] In a specific implementation, the production task information refers to the information required for subsequent production task allocation to the first site and the second site.

[0056] In the specific implementation, in order to improve production efficiency, the production task information includes but is not limited to:

[0057] Product category information;

[0058] Product batch information of the previous site;

[0059] Product quantity information for each batch before product batch splitting;

[0060] Product quantity information of each batch after the product batch is split;

[0061] Information on the number of equipment available for production at the first site and the second site;

[0062] Information on the time required to switch processes between different products;

[0063] And information on the time required to process various types of products.

[0064] The previous site refers to the previous site of the first site. The first site needs to split the product batches of the previous site for parallel production, so it is necessary to know the product batch information of the previous site and the batch quantity information before and after the product batch splitting, so as to obtain the product batch quantity of the first site and the product quantity of each product batch. In addition, based on the time required for the conversion process between different products and the time required for processing various types of products, the processing cycle of the first site and the second site can be better calculated.

[0065] In the specific implementation, in order to ensure product quality at the same time, the production task information also includes: the longest waiting time (Q-time) of each batch at the previous station and the first station. Each batch of products needs to flow to the next station within the Q-time, otherwise it will affect the product quality.

[0066] Step 12, based on the production task information, using a genetic algorithm, calculate the shortest processing cycle of the first site, and according to the calculation result, determine and output the product batch allocation and sorting method corresponding to each device in the first site.

[0067] The first site is a site that needs to split the product batch of the previous site for parallel production.

[0068] Genetic algorithm is a method for searching for the optimal solution by simulating the natural evolution process. In the embodiment of the present invention, the genetic algorithm is used to search for the shortest processing cycle of the first site, so that the product batch allocation and sorting method corresponding to the shortest processing cycle can be used as the product batch allocation and sorting method corresponding to each device in the first site and output.

[0069] In a specific implementation, based on the production task information, a genetic algorithm is used to determine the product batch allocation and sorting method for each device in the first site. The split product batches can be randomly allocated and sorted as the first initial population, and then the processing cycle of the first site under the random allocation and sorting is calculated. Then, the split product batches are reallocated and sorted, and the processing cycle of the first site under each allocation and sorting is calculated until a first preset number of iterations is reached. Finally, the product batch allocation and sorting method corresponding to the shortest processing cycle of the first site within the first preset number of iterations is used as the product batch allocation and sorting method for each device in the first site.

[0070] Step 13, based on the production task information, using a genetic algorithm, calculate the shortest processing cycle of the first site and the second site, and according to the calculation result, determine and output the product batch allocation and sorting method of each device in the second site.

[0071] The second site is a site that needs to combine and produce the product batches of the first site.

[0072] In a specific implementation, the product batches of the first site can be combined according to the completion order of each product batch in the first site as the second initial population, and then the processing cycle of the first site and the second site under the second initial population is calculated, and then the product batches of the first site are recombined, and the processing cycle of the first site and the second site under each combination is calculated until the second preset number of iterations is reached. Finally, the product batch combination and sorting method corresponding to the shortest processing cycle of the first site and the second site within the second preset number of iterations can be used as the product batch allocation and sorting method for each device in the second site.

[0073] The processing cycle of the first and second stations is the shortest, which can maximize production efficiency. Therefore, the corresponding product batch combination and sorting method when the processing cycle of the first and second stations is the shortest is used as the product batch allocation and sorting method for each device in the second station, which can improve production efficiency.

[0074] In a specific implementation, the method may further include: storing the product batch allocation and sorting method corresponding to each device in the first site and the second site.

[0075] In a specific implementation, the output data is stored in a database. When the amount of data in the database is large enough, a first initial population and a second initial population can be generated through machine learning, thereby greatly improving the efficiency of each algorithm operation.

[0076] Figure 2This is a flow chart of using a genetic algorithm to determine the product batch allocation and sorting method for each device in the first site and the second site in one embodiment of the present invention.

[0077] Specifically, please refer to Figure 2 , when using a genetic algorithm to determine the product batch allocation and sorting method of each device in the first site, the following steps may be included:

[0078] Step 201: Generate a first initial population.

[0079] For example, the split product batches are randomly allocated and sorted as the first initial population. Of course, other methods can also be used to generate the first initial population, which is not limited here.

[0080] Step 202, calculating the processing cycle of the first station.

[0081] Specifically, the total processing cycle of each product manufactured at the first site may be calculated based on the production task information.

[0082] Step 203, determine whether to terminate.

[0083] In a specific implementation, a first preset number of iterations may be set, and the current number of iterations being equal to the first preset number of iterations is used as an iteration termination condition.

[0084] When the current number of iterations is equal to the first preset number of iterations, the iteration process is stopped and step 204 is executed; otherwise, step 205 is executed.

[0085] Step 204 , using the product batch allocation and sorting method corresponding to the shortest processing cycle of the first station within the first preset number of iterations as the product batch allocation and sorting method for each device in the first station.

[0086] Step 205, updating population individuals.

[0087] That is to say, the split product batches are reallocated and sorted again.

[0088] After each population individual is updated, step 202 is re-executed, that is, the processing cycle of the first site is recalculated. Step 205, step 202 and step 203 are repeated until the current number of iterations is equal to the first preset number of iterations. In each iteration process, a processing cycle of the first site can be calculated. Finally, the product batch allocation and sorting method corresponding to the shortest processing cycle in all iterations is selected as the product batch allocation and sorting method for each device in the first site.

[0089] When using a genetic algorithm to determine the product batch allocation and sorting method of each device in the second site, the following steps may be included:

[0090] Step 206: Generate a second initial population.

[0091] For example, the completion order of each product batch in the first site can be used to combine each product batch in the first site as the second initial population. Of course, other methods can also be used to generate the second initial population, which is not limited here.

[0092] Step 207, calculating the processing cycles of the first station and the second station.

[0093] That is to calculate the sum of the processing cycles of the first station and the second station.

[0094] Step 208, determine whether to terminate.

[0095] In a specific implementation, a second preset number of iterations may be set, and the current number of iterations being equal to the second preset number of iterations is used as an iteration termination condition.

[0096] When the current number of iterations is equal to the second preset number of iterations, the iteration process is stopped and step 209 is executed; otherwise, step 210 is executed.

[0097] Step 209: The product batch combination and sorting method corresponding to the shortest processing cycle of the first site and the second site within the second preset number of iterations are used as the product batch allocation and sorting method for each device in the second site.

[0098] Step 210, updating the population individuals, that is, recombining the product batches in the first site.

[0099] After each population individual is updated, step 207 is re-executed to calculate the processing cycle of the first site and the second site after the recombination. Steps 210, 207 and 208 are repeated until the current number of iterations is equal to the second preset number of iterations. In each iteration process, a processing cycle can be calculated. Finally, the product batch allocation and sorting method corresponding to the shortest processing cycle in all iterations is selected as the product batch allocation and sorting method for each device in the second site.

[0100] In one embodiment of the present invention, in the process of calculating the shortest processing cycle of the first site and the second site using a genetic algorithm, the method may also include: when a first preset condition is met, the determined product batch allocation and sorting method corresponding to each device in the first site is used as the first initial population, and the genetic algorithm is used to re-determine the product batch allocation and sorting method corresponding to each device in the first site.

[0101] Among them, the first preset condition is not limited. For example, a random number can be generated after each calculation of the processing cycle of the first site and the second site. When the random number is the same as the pre-stored first data, it is considered that the first preset condition is met, otherwise the first preset condition is not met. When the first preset condition is met, the product batch allocation and sorting method corresponding to each device in the first site determined in step 204 are used as the first initial population, and the genetic algorithm is used to re-determine the product batch allocation and sorting method corresponding to each device in the first site. In this way, the result of the batch decision can be used to adjust the result of the parallel scheduling, optimize the overall processing time, and further improve production efficiency.

[0102] Specifically, combined Figure 2 After executing step 207, execute step 211 to generate a random number.

[0103] After executing step 211, step 212 is executed to determine whether the first preset condition is satisfied, that is, to determine whether the random number generated in step 211 is the same as the pre-stored first data.

[0104] When the first preset condition is not met, step 208 is executed. When the first preset condition is met, step 213 is executed to update the first initial population. Thus, the current iteration process is stopped, and steps 201 to 205 are executed. Based on the updated first initial population, the product batch allocation and sorting method corresponding to each device in the first site is obtained again, and then steps 206 to 212 are continued.

[0105] Assume that the first site is site B, the second site is site C, and the site before the first site is site A. Figure 3 , Site B has 5 devices available for processing selection, namely Device 1, Device 2, Device 3, Device 4 and Device 5. Site C has 1 device available for processing selection. Site B splits the product batches of Site A and performs parallel production. The allocation and sorting of product batches for each device in Site B is called parallel scheduling. Site C combines the product batches of Site B for production. The allocation and sorting of product batches for each device in Site C is called group batch scheduling. In one embodiment, the entire manufacturing process only includes Site A, Site B and Site C. The time from the start of work at Site A to the end of work at Site C is called the production cycle of the product.

[0106] The obtained production task information is shown in Tables 1 to 3. Table 1 is the production task information of Site A. Table 2 is the production task information of Site B. Table 3 is the time required for the transition process between different products at Site A.

[0107] As can be seen from Table 1, the product types of Site A include A, B and C. Among them, at Site A, there are two batches of product A, namely Lot1 and Lot2. There are two batches of product B, namely Lot3 and Lot4. Product C is one batch, Lot5. In product batches Lot1 to Lot5, the number of products in each batch is the same, all 25pcs. The longest waiting time for each product batch in Site A is greater than 96 hours (h).

[0108] Site B's splitting requirement for product batch Lot1 is to split product batch Lot1 into 5 batches, namely Lot1-1, Lot1-2, Lot1-3, Lot1-4 and Lot1-5 (as shown in Table 2). The number of products in each batch is 5pcs.

[0109] Table 1

[0110]

[0111] Site B's splitting requirement for product batch Lot2 is to split product batch Lot2 into 5 batches, namely Lot2-1, Lot2-2, Lot2-3, Lot2-4 and Lot2-5 (as shown in Table 2). The number of products in each batch is 5pcs.

[0112] Site B's splitting requirement for product batch Lot3 is to split product batch Lot3 into 3 batches, namely Lot3-1, Lot3-2 and Lot3-3 (as shown in Table 2). The number of products in each batch is 8pcs, 8pcs and 9pcs respectively.

[0113] Site B's splitting requirement for product batch Lot4 is to split product batch Lot4 into 3 batches, namely Lot4-1, Lot4-2 and Lot4-3 (as shown in Table 2). The number of products in each batch is 8pcs, 8pcs and 9pcs respectively.

[0114] Site B's splitting requirement for product batch Lot5 is to split product batch Lot5 into two batches, Lot5-1 and Lot5-2 (as shown in Table 2). The number of products in each batch is 13pcs and 12pcs respectively.

[0115] Table 2

[0116] product Lot Batch quantity (pcs / lot) Q-time A Lot1-1 5 2h A Lot 1-2 5 2h A Lot 1-3 5 2h A Lot 1-4 5 2h A Lot 1-5 5 2h A Lot2-1 5 2h A Lot2-2 5 2h A Lot 2-3 5 2h A Lot 2-4 5 2h A Lot 2-5 5 2h B Lot3-1 8 24h B Lot3-2 8 24h B Lot3-3 9 24h B Lot4-1 8 24h B Lot4-2 8 24h B Lot 4-3 9 24h C Lot5-1 12 96h C Lot5-2 13 96h

[0117] The time required for the process change between product batches at site A is shown in Table 3. “-” indicates that no process change is required between the corresponding product batches. For example, the time required for the equipment to change from producing product batch Lot1 to producing product batch Lot3 is 2 minutes each time.

[0118] Table 3

[0119] Lot 1 Lot2 Lot 3 Lot4 Lot5 Lot 1 - - 2 1 3 Lot2 - - 2.5 1 1.5 Lot 3 2 2.5 - - 2 Lot4 1 1 - - 1.5 Lot5 3 1.5 2 1.5 -

[0120] For example, referring to Table 4, the product batches allocated to equipment 1 are Lot 1-1, Lot 1-2, Lot 2-1 and Lot 2-2, and the processing order is: Lot 1-1→Lot 1-2→Lot 2-1→Lot 2-2.

[0121] Table 4

[0122]

[0123] By adopting the dispatching method in the embodiment of the present invention, the product batch allocation and sorting scheme in site C can be obtained as shown in Table 5. In site C, Lot 1-1 to Lot 1-4 can be combined and produced at the same time, and then Lot 1-5 and Lot 2-5 can be combined and produced at the same time. Then, Lot 2-1 to Lot 2-4 can be combined and produced at the same time, and then Lot 3-1, Lot 4-1, Lot4-2, and Lot 3-2 can be combined and produced at the same time. Then, Lot 5-1, Lot 3-3, Lot 4-3 and Lot 5-2 can be produced in sequence.

[0124] Table 5

[0125]

[0126] By adopting the dispatching method in the embodiment of the present invention, the production tasks of different batches of multiple devices are sorted and allocated, so as to optimize the overall processing time, realize the overall scheduling optimization of the system, and realize the maximization of production efficiency and resource utilization.

[0127] In order to enable those skilled in the art to better understand and implement the present invention, the user terminal and computer-readable storage medium corresponding to the above method are described in detail below.

[0128] Reference Figure 4 The embodiment of the present invention provides a work dispatching device, which may include: a data acquisition unit 41, a first work dispatching unit 42, a second work dispatching unit 43 and an output unit 44. Wherein:

[0129] The data acquisition unit 41 is adapted to acquire production task information;

[0130] The first dispatching unit 42 is adapted to calculate the shortest processing cycle of the first site by using a genetic algorithm based on the production task information, and determine the product batch allocation and sorting method corresponding to each device in the first site according to the calculation result, wherein the first site is a site that needs to split the product batch of the previous site for parallel production;

[0131] The second dispatching unit 43 is adapted to calculate the shortest processing cycle of the first site and the second site by using a genetic algorithm based on the production task information, and determine the product batch allocation and sorting method of each device in the second site according to the calculation result, wherein the second site is a site that needs to combine the product batches of the first site for production;

[0132] The output unit 44 is adapted to output the product batch allocation and sorting method corresponding to each device in the first site and the second site.

[0133] In one embodiment of the present invention, the dispatching device may further include: an adjustment unit 45. The adjustment unit 45 is adapted to, in the process of calculating the shortest processing cycle of the first station and the second station by using a genetic algorithm, when a first preset condition is met, use the determined product batch allocation and sorting method corresponding to each device in the first station as the initial population, and use the genetic algorithm to re-determine the product batch allocation and sorting method corresponding to each device in the first station.

[0134] In an embodiment of the present invention, the work dispatching device may further include: a storage unit 46. The storage unit 46 is adapted to store the product batch allocation and sorting method corresponding to each device in the first site and the second site.

[0135] The dispatching device may be: a chip or a chip module. The above-mentioned functional units may be implemented with reference to the above-mentioned description of the method steps, which will not be described in detail here.

[0136] Regarding the various modules / units included in the various devices and products described in the above embodiments, they can be software modules / units, or hardware modules / units, or they can be partially software modules / units and partially hardware modules / units. For example, for various devices and products applied to or integrated in a chip, the various modules / units included therein can all be implemented in the form of hardware such as circuits, or at least some of the modules / units can be implemented in the form of software programs, which run on a processor integrated inside the chip, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits; for various devices and products applied to or integrated in a chip module, the various modules / units included therein can all be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component (such as a chip, circuit module, etc.) or different components of the chip module, or at least some of the modules / units can be implemented in the form of hardware such as circuits. The element can be implemented in the form of a software program, which runs on the processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in hardware such as circuits; for each device or product applied to or integrated in the terminal, each module / unit contained therein can be implemented in hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal, or at least some modules / units can be implemented in the form of a software program, which runs on the processor integrated inside the terminal, and the remaining (if any) modules / units can be implemented in hardware such as circuits. The embodiment of the present invention also provides another computer-readable storage medium, which stores computer instructions, and when the computer instructions are executed, the steps of the control method of the electronic device described in any of the above embodiments are executed, which will not be repeated.

[0137] The embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of any of the above methods.

[0138] In a specific implementation, the computer-readable storage medium may include: ROM, RAM, magnetic disk or optical disk, etc.

[0139] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and the processor executes the steps of any of the above methods when running the computer program, which will not be repeated here.

[0140] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the scope defined by the claims.

Claims

1. A method for dispatching work, characterized in that: include: Obtain production task information; Based on the production task information, a genetic algorithm is used to calculate the shortest processing cycle of the first site, and according to the calculation result, the product batch allocation and sorting method corresponding to each device in the first site is determined and output, and the first site is a site that needs to split the product batch of the previous site for parallel production; Based on the production task information, a genetic algorithm is used to calculate the shortest processing cycles of the first site and the second site, and according to the calculation results, the product batch allocation and sorting method of each equipment in the second site is determined and output. The second site is a site that needs to combine the product batches of the first site for production.

2. The method for dispatching work according to claim 1, characterized in that: The production task information includes: Product category information; Product batch information of the previous site; Batch quantity information before product batch splitting; Batch quantity information after product batches are split; The longest waiting time for each batch at the previous station and the first station; Information on the number of equipment available for production at the first site and the second site; Information on the time required to switch processes between different products; And information on the time required to process various types of products.

3. The method for dispatching work according to claim 1, characterized in that: The method of calculating the shortest processing cycle of the first site by using a genetic algorithm based on the production task information, and determining the product batch allocation and sorting method of each device in the first site according to the calculation result, includes: Randomly assign and sort the split product batches as the first initial population; Calculate the processing cycle of the first station under random allocation and sorting; Re-allocate and sort the split product batches, and calculate the processing cycle of the first station under each allocation and sorting, until a first preset number of iterations is reached; The product batch allocation and sorting method corresponding to the shortest processing cycle of the first station within the first preset number of iterations is used as the product batch allocation and sorting method for each device in the first station.

4. The method for dispatching work according to claim 1, characterized in that: The method of calculating the shortest processing cycle of the first site and the second site by using a genetic algorithm based on the production task information, and determining the product batch allocation and sorting method of each device in the second site according to the calculation result, includes: According to the completion order of each product batch in the first station, the product batches of the first station are combined as a second initial population; Calculating the processing cycles of the first site and the second site under the second initial population; Recombining the product batches in the first station, and calculating the processing cycles of the first station and the second station under each combination until a second preset number of iterations is reached; The product batch combination and sorting method corresponding to the shortest processing cycle of the first station and the second station within the second preset number of iterations is used as the product batch allocation and sorting method for each device in the second station.

5. The method for dispatching work according to any one of claims 1 to 4, characterized in that: In the process of calculating the shortest processing cycle of the first station and the second station by using the genetic algorithm, it also includes: When the first preset condition is met, the determined product batch allocation and sorting method corresponding to each device in the first site is used as the first initial population, and a genetic algorithm is used to redetermine the product batch allocation and sorting method corresponding to each device in the first site.

6. The method for dispatching work according to claim 1, characterized in that: Also includes: The product batch allocation and sorting method corresponding to each device in the first site and the second site are stored.

7. A work dispatching device, characterized in that: include: A data acquisition unit, adapted to acquire production task information; The first dispatching unit is adapted to calculate the shortest processing cycle of the first site by using a genetic algorithm based on the production task information, and determine the product batch allocation and sorting method corresponding to each device in the first site according to the calculation result, wherein the first site is a site that needs to split the product batch of the previous site for parallel production; The second dispatching unit is adapted to calculate the shortest processing cycle of the first site and the second site by using a genetic algorithm based on the production task information, and determine the product batch allocation and sorting method of each device in the second site according to the calculation result, wherein the second site is a site that needs to combine the product batches of the first site for production; The output unit is adapted to output the product batch allocation and sorting method corresponding to each device in the first site and the second site.

8. The dispatching device according to claim 7, characterized in that: Also includes: The adjustment unit is suitable for using the genetic algorithm to calculate the shortest processing cycle of the first site and the second site. When the first preset condition is met, the product batch allocation and sorting method corresponding to each device in the first site is determined as the initial population, and the product batch allocation and sorting method corresponding to each device in the first site is re-determined using the genetic algorithm.

9. The dispatching device according to claim 7, characterized in that: Also includes: The storage unit is adapted to store the product batch allocation and sorting methods corresponding to each device in the first site and the second site.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement the steps of the method according to any one of claims 1 to 6.

11. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor runs the computer program, the steps of the method according to any one of claims 1 to 6 are performed.

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