Work order arrangement method and device, electronic equipment, storage medium and program product
By clustering and optimizing the arrangement of work orders in the printed circuit board assembly production process, the problem of frequent production line changes was solved, achieving efficient resource utilization and improved production efficiency.
Patent Information
- Application Number
- CN202511622343.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-07
- Publication Date
- 2025-12-05
AI Technical Summary
In the existing printed circuit board assembly production process, due to differences in product configuration, BOM materials, process requirements and fixture resources in work orders, production lines are frequently changed, equipment parameters are repeatedly adjusted, and materials are prepared multiple times, which prolongs the production cycle, reduces equipment utilization and capacity output, and causes resource waste.
By acquiring the configuration and demand information of the work orders to be processed, and based on similarity and production line characteristics, the work orders are clustered and arranged to optimize the production sequence, reduce changeover and equipment debugging time, and improve production efficiency.
It has enabled the continuous and stable operation of the production line, reduced waste of materials and human resources, improved production efficiency and equipment utilization, and reduced production costs.
Smart Images
Figure CN121073167A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of computer, and particularly relates to a work order arrangement method and device, electronic equipment, storage medium and program product. BACKGROUND
[0002] In the current Printed Circuit Board Assembly (PCBA) production process, the production line usually directly arranges production according to the submission order or delivery time of a work order. Since different work orders have great differences in product configuration, BOM material, process requirements and clamp jig resources, directly arranging production according to the order will cause frequent line change, repeated adjustment of equipment parameters, and multiple material preparation of the production line. This extensive production arrangement mode not only prolongs the overall production cycle, but also limits the equipment utilization rate and production capacity output, causing serious waste of human and material resources. SUMMARY
[0003] Embodiments of the present application provide a work order arrangement method, device, electronic equipment, storage medium and program product, so as to achieve fine analysis and integration of the inherent characteristics of the work order and reduce resource waste.
[0004] In a first aspect, embodiments of the present application provide a work order arrangement method, comprising:
[0005] obtaining configuration information and demand information corresponding to a plurality of to-be-processed work orders;
[0006] based on the configuration information and a plurality of production lines, clustering and dividing a plurality of the to-be-processed work orders to obtain a plurality of the to-be-processed work orders corresponding to each of the production lines;
[0007] based on the demand information, arranging a plurality of the to-be-processed work orders corresponding to each of the production lines to obtain a processing order of a plurality of the to-be-processed work orders corresponding to each of the production lines;
[0008] controlling each of the production lines to process the to-be-processed work orders according to the processing order.
[0009] In a possible implementation, the plurality of production lines includes a plurality of production types.
[0010] The configuration information includes work order property information and product type information of the to-be-processed work order.
[0011] The clustering and dividing of a plurality of the to-be-processed work orders based on the configuration information and a plurality of production lines to obtain a plurality of the to-be-processed work orders corresponding to each of the production lines comprises:
[0012] Based on the work order nature information of each work order to be processed, the production type corresponding to the work order to be processed is determined; multiple production types correspond one-to-one with multiple work order nature information.
[0013] For multiple pending work orders belonging to the same production type, based on the product type information of the pending work orders, multiple pending work orders corresponding to each production line.
[0014] In one possible implementation, before merging the multiple pending work orders corresponding to each of the production lines based on the demand information to obtain at least one merged work order corresponding to each of the production lines, the method further includes:
[0015] Obtain the forklift program information corresponding to each of the work orders to be processed;
[0016] Based on the forklift program information, the pending work orders corresponding to each production line are subjected to secondary clustering to obtain multiple work order clusters; each work order cluster contains at least one of the pending work orders.
[0017] In one possible implementation, the step of arranging the multiple pending work orders corresponding to each of the production lines based on the demand information to obtain the processing order of the multiple pending work orders corresponding to each of the production lines includes:
[0018] For each work order cluster, based on the demand information, determine the similarity between any two work orders to be processed.
[0019] Based on the similarity, the multiple pending work orders corresponding to each production line are arranged to obtain the processing order of the multiple pending work orders corresponding to each production line.
[0020] In one possible implementation, the requirement information includes process information, material information, and fixture information;
[0021] For each of the work orders in the work order cluster, determining the similarity between any two work orders based on the demand information includes:
[0022] For each work order cluster, based on the process information of the work order, a first similarity is determined between any two work orders; based on the material information of the work order, a second similarity is determined between any two work orders; and based on the fixture information of the work order, a third similarity is determined between any two work orders.
[0023] According to the preset weight configuration strategy, the first similarity, the second similarity, and the third similarity are weighted to obtain the similarity between any two of the work orders to be processed.
[0024] In one possible implementation, the step of arranging the multiple pending work orders corresponding to each of the production lines based on the similarity to obtain the processing order of the multiple pending work orders corresponding to each of the production lines includes:
[0025] For any of the pending work orders, based on the similarity between the remaining pending work orders and the current pending work order, the remaining pending work orders are arranged in descending order of similarity to determine the processing order.
[0026] Secondly, embodiments of this application provide a work order arrangement device, comprising:
[0027] The acquisition module is used to acquire configuration and requirement information corresponding to multiple pending work orders.
[0028] The segmentation module is used to cluster and segment multiple work orders to be processed based on the configuration information and multiple production lines, so as to obtain multiple work orders to be processed corresponding to each production line.
[0029] The arrangement module is used to arrange the multiple pending work orders corresponding to each production line based on the demand information, so as to obtain the processing order of the multiple pending work orders corresponding to each production line.
[0030] The control module is used to control each of the production lines to process the work orders to be processed according to the processing sequence.
[0031] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;
[0032] The memory stores computer-executed instructions;
[0033] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.
[0034] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.
[0035] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.
[0036] The work order arrangement method, apparatus, electronic device, storage medium, and program product provided in this application cluster and arrange multiple work orders to be processed adjacently based on the configuration and demand information of different work orders to be processed. This minimizes the changeover time, equipment debugging time, and program loading time required for switching between different work orders on the production line, enabling the production line to operate continuously and stably for a longer period of time. This allows more production time to be devoted to producing the products themselves, avoiding material surplus and waste caused by frequent changeovers. Furthermore, it reduces the time wasted by production line workers on the production line on frequent and scattered material preparation and changeovers for different work orders to be processed, reducing the consumption of human resources. While reducing the production cost of the production line, it also significantly improves the production efficiency of the production line. Attached Figure Description
[0037] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0038] Figure 1 A schematic diagram illustrating the work order arrangement method provided in this application;
[0039] Figure 2 A flowchart illustrating the work order arrangement method provided in this application;
[0040] Figure 3 A schematic diagram of the work order arrangement device provided in this application;
[0041] Figure 4 A schematic diagram of the structure of the electronic device provided in this application.
[0042] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation
[0043] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0044] The work order arrangement method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network.
[0045] For example, the work order arrangement method is applied to terminal 102. Terminal 102 can obtain configuration information and demand information corresponding to multiple pending work orders from the data storage system of server 104. Then, based on the configuration information and multiple production lines, the multiple pending work orders are clustered to obtain multiple pending work orders corresponding to each production line. Based on the demand information, the multiple pending work orders corresponding to each production line are arranged to obtain the processing order of the multiple pending work orders corresponding to each production line. Finally, according to the processing order, each production line is controlled to process the pending work orders. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. Server 104 can be implemented using a standalone server or a server cluster composed of multiple servers. Terminal 102 and server 104 can be directly or indirectly connected via wired or wireless communication, such as through a network connection.
[0046] For example, the work order arrangement method is applied to server 104. Server 104 can obtain configuration information and demand information corresponding to multiple pending work orders from the data storage system. Then, based on the configuration information and multiple production lines, the multiple pending work orders are clustered to obtain multiple pending work orders corresponding to each production line. Based on the demand information, the multiple pending work orders corresponding to each production line are arranged to obtain the processing order of the multiple pending work orders corresponding to each production line. Finally, according to the processing order, each production line is controlled to process the pending work orders. It can be understood that the data storage system can be an independent storage device, or the data storage system can be located on server 104, or the data storage system can be located on another terminal.
[0047] In one embodiment, a work order arrangement method is provided. This embodiment illustrates the application of this work order arrangement method to a terminal. It is understood that this work order arrangement method can also be applied to a server, and can also be applied to a system including a terminal and a server, and implemented through the interaction between the terminal and the server. Figure 2 As shown, the work order arrangement method includes:
[0048] Step 202: Obtain the configuration information and requirement information corresponding to multiple pending work orders.
[0049] A pending work order refers to a production task unit that is planned to be put into production but has not yet been assigned a specific production time and sequence. Pending work orders are usually used to instruct the production of a specific quantity and model of products.
[0050] Configuration information refers to a set of static data that characterizes the inherent technical attributes and production resource requirements of the product corresponding to the work order to be processed. Configuration information can, for example, define the product's physical structure, process path, and the dedicated resources required for production.
[0051] Demand information refers to the set of static parameters of the technical elements and resource constraints necessary for the production execution of a work order. For example, demand information can define the manufacturing process, material composition, and specialized equipment that must be followed in the production of the product corresponding to the work order.
[0052] Step 204: Based on the configuration information and multiple production lines, cluster the multiple pending work orders to obtain multiple pending work orders corresponding to each production line.
[0053] A production line refers to a physical assembly line composed of multiple production devices with different functions. Different production lines have their specific capacity, technical strengths, and applicable scope.
[0054] The process of clustering multiple pending work orders can be understood as classifying and grouping them into different clusters based on the similarity between them, and then assigning each cluster to the most suitable production line for production.
[0055] Step 206: Based on the demand information, arrange the multiple pending work orders corresponding to each production line to obtain the processing order of the multiple pending work orders corresponding to each production line.
[0056] This step is used to indicate the process of determining the execution order of multiple pending work orders that have been assigned to a production line for processing.
[0057] Step 208: Control each production line to process pending work orders according to the processing sequence.
[0058] The aforementioned work order arrangement method clusters and arranges multiple pending work orders adjacent to each other based on their configuration and demand information. This minimizes the time required for production line switching, equipment debugging, and program loading between different pending work orders, allowing the production line to operate continuously and stably for longer periods. This enables more production time to be devoted to producing the products themselves, avoiding material surplus and waste caused by frequent line changes. Furthermore, it reduces the time wasted by production line workers on frequent and scattered material preparation and line changes for different pending work orders, lowering human resource consumption and significantly improving production line efficiency while reducing production costs.
[0059] In some alternative embodiments, multiple production lines include multiple production types;
[0060] Configuration information includes the nature of the work order and the product type information of the work order to be processed;
[0061] Step 204 includes:
[0062] Based on the work order nature information of each work order to be processed, the production type corresponding to the work order to be processed is determined; multiple production types correspond one-to-one with multiple work order nature information.
[0063] For multiple pending work orders belonging to the same production type, based on the product type information of the pending work orders, multiple pending work orders corresponding to each production line are processed.
[0064] Work order nature information can be used to indicate the urgency of pending work orders and the level of demand for production resources.
[0065] Product type information can be used to indicate the specific model, series, and other information of the products corresponding to different pending work orders, and to distinguish the technical specifications and physical form of different products.
[0066] Production lines can be categorized into large-scale production lines and small-scale production lines. Large-scale production lines refer to high-speed, mass-production lines, while small-scale production lines refer to flexible, pilot-production lines. For example, if the work order nature information of one pending work order indicates it is a mass-production motherboard work order, and the work order nature information of another pending work order indicates it is a pilot-production motherboard or sub-board work order, then it can be determined that the production line type corresponding to the former pending work order is a large-scale production line, and the production line type corresponding to the latter pending work order is a small-scale production line.
[0067] Furthermore, the product type information of the pending work order may include, for example, the specific model of the product corresponding to the pending work order. For instance, for two production lines of the same production type, if the product type information of the first pending work order indicates that the product corresponding to the pending work order is a type A PCBA, the product type information of the second pending work order indicates that the product corresponding to the pending work order is a type B PCBA, and the product type information of the third pending work order indicates that the product corresponding to the pending work order is a type A PCBA, it can be determined that the first and third pending work orders correspond to the same production line, while the second pending work order corresponds to a different production line.
[0068] The above-mentioned work order arrangement method ensures that high-volume pending work orders can be produced by high-capacity, high-speed mass production lines, guaranteeing the delivery capability of major products with high demand. At the same time, it also guides flexible pilot production boards to flexible pilot production lines for production, avoiding frequent line changeovers caused by work orders for products with lower demand and lower priority entering high-speed mass production lines. Furthermore, it can allocate pending work orders for the same or similar products to the same production line for processing according to product type information, thereby minimizing production line changeovers and eliminating the huge time costs caused by material and fixture changes on the production line as much as possible.
[0069] In some optional embodiments, prior to step 206, the following steps are also included:
[0070] Obtain the forklift program information corresponding to each pending work order;
[0071] Based on the forklift program information, the pending work orders corresponding to each production line are subjected to secondary clustering to obtain multiple work order clusters; each work order cluster contains at least one pending work order.
[0072] Fork board program information refers to information used to indicate that a work order currently pending processing needs to simultaneously assemble multiple different small PCBs on a large substrate during the production process. Fork board program information is usually in the form of a unique program number or name, associated with specific parameters that need to be loaded by the pick-and-place machine, testing equipment, etc.
[0073] By clustering multiple pending work orders corresponding to the same production line based on the fork plate program information, it can be ensured that multiple pending work orders within the same work order cluster correspond to the same fork plate program information. For example, all pending work orders within a work order cluster are assembled on a large board of the same size.
[0074] As an example, there are ten pending work orders on the current production line. The corresponding forklift program information indicates that the current pending work order uses program A, program B, program A, program A, program C, program B, program B, program C, program A, program C. Then the terminal can group the 1st, 3rd, 4th, and 9th pending work orders into one work order cluster, the 2nd, 6th, and 7th pending work orders into another work order cluster, and the 5th, 8th, and 10th pending work orders into yet another work order cluster.
[0075] The above-described work order arrangement method can cluster multiple pending work orders corresponding to a production line based on the forklift program information, so that all pending work orders in a work order cluster can be arranged for continuous production. In subsequent actual production, the production line only needs to load the program corresponding to the forklift program information once when processing the first pending work order in each work order cluster, and can then continuously produce the remaining pending work orders in the current work order cluster without needing to switch programs again. This saves a lot of equipment downtime and program call time, and improves the efficiency of subsequent production on the production line.
[0076] In some alternative embodiments, step 206 includes:
[0077] For the pending work orders in each work order cluster, the similarity between any two pending work orders is determined based on the demand information.
[0078] Based on similarity, multiple pending work orders corresponding to each production line are arranged to obtain the processing order of multiple pending work orders corresponding to each production line.
[0079] Similarity refers to a numerical metric used to quantify the degree of similarity in demand information between two work orders to be processed. The higher the similarity, the more similar the two work orders are, and the lower the changeover cost required for production lines when they are produced adjacently.
[0080] Similarity-based sorting is an optimization algorithm process that aims to find an order in which adjacent work orders are arranged to maximize the overall similarity between them in the entire production sequence.
[0081] Specifically, the requirements information includes process information, material information, and fixture information;
[0082] For each work order cluster, the steps to determine the similarity between any two work orders based on demand information include:
[0083] For the pending work orders in each work order cluster, the first similarity between any two pending work orders is determined based on the process information of the pending work orders, the second similarity between any two pending work orders is determined based on the material information of the pending work orders, and the third similarity between any two pending work orders is determined based on the fixture information of the pending work orders.
[0084] According to the preset weight configuration strategy, the first similarity, the second similarity, and the third similarity are weighted to obtain the similarity between any two work orders to be processed.
[0085] Process information can include the process step sequences of two work orders to be processed. The first similarity refers to comparing the process step sequences of the two work orders to be processed and calculating the length of their common sequence or the degree of overlap of steps.
[0086] Material information can include the materials used in two pending work orders. The second similarity refers to the proportion of identical materials in the bills of materials of the two pending work orders out of the total number of material types. For example, if pending work order A has 100 types of materials and pending work order B has 110 types of materials, and 95 of them are the same, then the second similarity between the two pending work orders can be calculated as 2*95 / (100+110)≈0.905.
[0087] The fixture information can include the fixtures required for two pending work orders. The third similarity refers to whether the fixtures required for the two pending work orders are exactly the same. For example, if the fixtures required for the two pending work orders are exactly the same, the third similarity is 1; otherwise, it is 0. Alternatively, a score can be calculated based on the proportion of shared fixtures.
[0088] The weighting strategy refers to pre-setting a set of weight coefficients W1, W2, and W3 based on actual production pain points, representing the importance of the first, second, and third similarities, respectively. As an example, W2 can have the highest weight because material changeover is the most frequent changeover activity.
[0089] In some optional embodiments, the step of arranging multiple pending work orders corresponding to each production line based on similarity to obtain the processing order of multiple pending work orders corresponding to each production line includes:
[0090] For any pending work order, based on the similarity between the remaining pending work orders and the current pending work order, the remaining pending work orders are arranged in descending order of similarity to determine the processing order.
[0091] The above-mentioned work order arrangement method can arrange multiple work orders to be processed based on similarity, so that the overall similarity between adjacent work orders to be processed in the entire production sequence is the highest. This minimizes the workload of switching when the same production line is producing products corresponding to different work orders to be processed, thereby saving the time required for the switching process. Furthermore, through the weight configuration strategy, the optimization focus can be directly directed to the most time-consuming and resource-intensive links in the current production, thereby accurately improving the efficiency of subsequent production on the production line.
[0092] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.
[0093] Based on the same inventive concept, this application also provides a cooperative control device for implementing the cooperative control method described above. The solution provided by this cooperative control device is similar to the solution described in the cooperative control method above. Therefore, the specific limitations in one or more device embodiments provided below can be found in the limitations of the cooperative control method described above, and will not be repeated here.
[0094] In one embodiment, such as Figure 3 As shown, a work order arrangement device 300 is provided, comprising:
[0095] The acquisition module 302 is used to acquire configuration information and requirement information corresponding to multiple pending work orders;
[0096] The partitioning module 304 is used to cluster and partition multiple pending work orders based on configuration information and multiple production lines to obtain multiple pending work orders corresponding to each production line.
[0097] The arrangement module 306 is used to arrange multiple pending work orders corresponding to each production line based on demand information, so as to obtain the processing order of multiple pending work orders corresponding to each production line.
[0098] The control module 308 is used to control each production line to process pending work orders according to the processing sequence.
[0099] In some alternative embodiments, multiple production lines include multiple production types;
[0100] Configuration information includes the nature of the work order and the product type information of the work order to be processed;
[0101] The partitioning module 304 is also configured as follows:
[0102] Based on the work order nature information of each work order to be processed, the production type corresponding to the work order to be processed is determined; multiple production types correspond one-to-one with multiple work order nature information.
[0103] For multiple pending work orders belonging to the same production type, the multiple pending work orders corresponding to each pending work order are determined based on the product type information of the pending work orders.
[0104] In some alternative embodiments, the arrangement module 306 is further configured to:
[0105] Obtain the forklift program information corresponding to each pending work order;
[0106] Based on the forklift program information, the pending work orders corresponding to each production line are subjected to secondary clustering to obtain multiple work order clusters; each work order cluster contains at least one pending work order.
[0107] In some alternative embodiments, the arrangement module 306 is further configured to:
[0108] For the pending work orders in each work order cluster, the similarity between any two pending work orders is determined based on the demand information.
[0109] Based on similarity, multiple pending work orders corresponding to each production line are arranged to obtain the processing order of multiple pending work orders corresponding to each production line.
[0110] In some optional embodiments, the requirements information includes process information, material information, and fixture information;
[0111] Arrangement module 306 is also configured as follows:
[0112] For the pending work orders in each work order cluster, the first similarity between any two pending work orders is determined based on the process information of the pending work orders, the second similarity between any two pending work orders is determined based on the material information of the pending work orders, and the third similarity between any two pending work orders is determined based on the fixture information of the pending work orders.
[0113] According to the preset weight configuration strategy, the first similarity, the second similarity, and the third similarity are weighted to obtain the similarity between any two work orders to be processed.
[0114] In some alternative embodiments, the arrangement module 306 is further configured to:
[0115] For any pending work order, based on the similarity between the remaining pending work orders and the current pending work order, the remaining pending work orders are arranged in descending order of similarity to determine the processing order.
[0116] Each module in the above-mentioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.
[0117] Figure 4 A schematic diagram of the structure of the electronic device provided in this application. Figure 4 As shown, the electronic device 400 provided in this embodiment includes at least one processor 401 and a memory 402. Optionally, the device 400 further includes a communication component 403. The processor 401, memory 402, and communication component 403 are connected via a bus 404.
[0118] In a specific implementation, at least one processor 401 executes computer execution instructions stored in memory 402, causing at least one processor 401 to perform the above-described method.
[0119] The specific implementation process of processor 401 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.
[0120] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.
[0121] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.
[0122] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.
[0123] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.
[0124] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.
[0125] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.
[0126] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.
[0127] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.
[0128] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0129] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0130] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0131] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[0132] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.
Claims
1. A method for arranging work orders, characterized in that, The method comprises the following steps: obtaining configuration information and demand information corresponding to a plurality of to-be-processed work orders; based on the configuration information and a plurality of production lines, clustering and dividing a plurality of to-be-processed work orders to obtain a plurality of to-be-processed work orders corresponding to each production line; based on the demand information, arranging a plurality of to-be-processed work orders corresponding to each production line to obtain a processing order of a plurality of to-be-processed work orders corresponding to each production line; controlling each production line to process the to-be-processed work orders according to the processing order; a plurality of production lines include a plurality of production types; the production types include high-speed mass production type and flexible trial production type; the configuration information includes work order property information and product type information of the to-be-processed work orders; based on the configuration information and a plurality of production lines, clustering and dividing a plurality of to-be-processed work orders to obtain a plurality of to-be-processed work orders corresponding to each production line, comprising: based on the work order property information of each to-be-processed work order, determining the production type corresponding to the to-be-processed work order; a plurality of production types correspond to a plurality of work order property information one by one; the work order property information is used to indicate the urgency and demand level of production resources of the to-be-processed work order; for a plurality of to-be-processed work orders belonging to the same production type, based on the product type information of the to-be-processed work order, a plurality of to-be-processed work orders corresponding to each production line are determined; before the step of based on the demand information, arranging a plurality of to-be-processed work orders corresponding to each production line to obtain a processing order of a plurality of to-be-processed work orders corresponding to each production line, further comprising: obtaining fork board program information corresponding to each to-be-processed work order; based on the fork board program information, a plurality of work order clusters are obtained by secondary clustering and dividing the to-be-processed work orders corresponding to each production line; the work order cluster contains at least one to-be-processed work order.
2. The method of claim 1, wherein, based on the demand information, arranging a plurality of to-be-processed work orders corresponding to each production line to obtain a processing order of a plurality of to-be-processed work orders corresponding to each production line, comprising: for the to-be-processed work orders in each work order cluster, based on the demand information, determining the similarity between any two to-be-processed work orders; based on the similarity, arranging a plurality of to-be-processed work orders corresponding to each production line to obtain a processing order of a plurality of to-be-processed work orders corresponding to each production line.
3. The method of claim 2, wherein, the demand information includes process information, material information and clamp information; for the to-be-processed work orders in each work order cluster, based on the demand information, determining the similarity between any two to-be-processed work orders, comprising: for the to-be-processed work orders in each work order cluster, based on the process information of the to-be-processed work order, determining the first similarity between any two to-be-processed work orders, based on the material information of the to-be-processed work order, determining the second similarity between any two to-be-processed work orders, and based on the clamp information of the to-be-processed work order, determining the third similarity between any two to-be-processed work orders; According to a preset weight configuration strategy, the first similarity, the second similarity, and the third similarity are configured with weights to obtain a similarity between any two of the to-be-processed work orders.
4. The method of claim 2, wherein, The arrangement of the plurality of to-be-processed work orders corresponding to each production line based on the similarity comprises: For any to-be-processed work order, based on the similarity between the remaining to-be-processed work orders and the current to-be-processed work order, the remaining to-be-processed work orders are arranged in descending order of the similarity to determine the processing order.
5. A work order arrangement device, characterized by, Comprise: An acquisition module configured to acquire configuration information and demand information corresponding to a plurality of to-be-processed work orders; A division module configured to cluster and divide the plurality of to-be-processed work orders based on the configuration information and a plurality of production lines to obtain a plurality of to-be-processed work orders corresponding to each production line; An arrangement module configured to arrange the plurality of to-be-processed work orders corresponding to each production line based on the demand information to obtain a processing order of the plurality of to-be-processed work orders corresponding to each production line; A control module configured to control each production line to process the to-be-processed work orders according to the processing order; The plurality of production lines comprise a plurality of production types; the production types comprise high-speed mass production type and flexible trial production type; The configuration information comprises work order property information and product type information of the to-be-processed work orders; The division module is further configured to: determine the production type corresponding to the to-be-processed work order based on the work order property information of each to-be-processed work order; the plurality of production types correspond one-to-one to a plurality of work order property information; the work order property information is used to indicate the urgency and demand level for production resources of the to-be-processed work order; for a plurality of to-be-processed work orders belonging to the same production type, determine the plurality of to-be-processed work orders corresponding to each production line based on the product type information of the to-be-processed work order; The arrangement module is further configured to: acquire forkboard program information corresponding to each to-be-processed work order; based on the forkboard program information, perform secondary clustering and division on the to-be-processed work orders corresponding to each production line to obtain a plurality of work order clusters; each work order cluster contains at least one to-be-processed work order. 6.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-5 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the method in claims 1-4.
7. A computer-readable storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to implement the steps of the method in claims 1-4.
8. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in claims 1-4.
Citation Information
Patent Citations
Intelligent order distribution method and system for furniture production line
CN118886656A