Distribution method based on workpiece types, terminal, medium, product and assembly line
By acquiring production orders and machine information, selecting target machines, and allocating them based on urgency and time commitment, the problem of inefficient production task allocation was solved, enabling timely and efficient completion of production tasks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HANS CNC SCI & TECH
- Filing Date
- 2024-11-20
- Publication Date
- 2026-05-22
Smart Images
Figure CN122072870A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of printed circuit board manufacturing technology, and in particular to a workpiece type-based allocation method, terminal, medium, product, and production line. Background Technology
[0002] With the rapid development of the electronics industry, especially the rise of new productive forces such as the low-altitude economy, the demand for printed circuit boards (PCBs), as an important component of smart terminals, is constantly increasing. However, in the PCB manufacturing process, production task allocation is a key link affecting overall efficiency. On the one hand, order demands are highly diverse, with different customers having significant differences in PCB specifications and process requirements. On the other hand, the number of processing machines on the production line is often uncertain, affected by factors such as equipment procurement plans, equipment failure and repair, and equipment upgrades.
[0003] The existing production task allocation method is unable to accurately allocate production tasks based on order demand and the status of processing machines when dealing with the complex and rapidly changing production environment, resulting in a significant reduction in production efficiency.
[0004] Therefore, how to efficiently allocate production tasks to improve production efficiency has become an urgent technical problem to be solved. Summary of the Invention
[0005] This invention provides a workpiece type-based allocation method, terminal, medium, product, and production line to solve the problem of low production efficiency caused by existing production task allocation methods.
[0006] Firstly, a workpiece type-based allocation method is provided, including: Obtain production order information and processing machine information; Based on the production order information and the processing machine information, select a target number of processing machines for processing; Determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type; If it can be completed, then calculate the urgency and processing time percentage of each workpiece type in the production processing order information; Based on the urgency of processing, the percentage of processing time, and the target quantity, processing machines are allocated to the workpieces corresponding to each workpiece type.
[0007] In one embodiment, the production processing order information includes work order information and single-trip processing time, wherein the work order information includes the number of processing boards and the delivery date; Before determining whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type, the process includes: Based on the number of processing plates and the single-pass processing time, the target processing time corresponding to each workpiece type is obtained; Based on the target processing time and the delivery date, the average daily processing time corresponding to each workpiece type is obtained; The total processing time is obtained by summing the target processing times for all workpiece types. The average daily processing time for all workpiece types is summarized to obtain the total average daily processing time. Based on the total processing time and the total average daily processing time, determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type.
[0008] In one embodiment, the machining machine information includes tool retrieval time and tool placement time, and the single-trip machining time is determined as follows: Based on the work order information, the drilling height and number of holes in each workpiece type are calculated using the machining program; Based on the tool retrieval time, the tool release time, the drilling height, the number of holes in the single plate, and the processing path time, the single-pass processing time corresponding to each workpiece type is obtained; The machining path duration represents the time required for the machining tool to move from the starting point to the target machining point.
[0009] In one embodiment, calculating the processing urgency and processing time percentage of each workpiece type in the production processing order information includes: Based on the target processing time, the delivery date, and the urgency coefficient, the processing urgency level corresponding to each workpiece type is obtained, wherein the urgency coefficient is determined by the delivery date; Based on the total processing time and the target processing time, the percentage of processing time corresponding to each workpiece type is obtained.
[0010] In one embodiment, the step of allocating processing machines to workpieces corresponding to each workpiece type based on the processing urgency, the processing time percentage, and the target quantity includes: Based on the urgency of the processing, all workpiece types are sorted to determine processing priority; Based on the processing priority, the target quantity, and the processing time ratio of each workpiece type corresponding to the processing priority, a first allocation is performed to determine the target number of machines allocated to each workpiece type. Based on the target processing time and the target number of machines, the first processing time corresponding to each workpiece type is obtained; The next allocation is made based on the first processing time corresponding to each workpiece type and the average processing time of the processing machine. The average processing time of the processing machine is determined by the total processing time and the target number of processing machines.
[0011] In one embodiment, the step of allocating the next processing time based on the first processing time corresponding to each workpiece type and the average processing time of the processing machine includes: The minimum value is selected from the first processing time corresponding to each workpiece type and the average processing time of the processing machine as the minimum processing time; When the minimum processing time is the first processing time corresponding to any of the workpiece types, the first remaining number of workpieces corresponding to each workpiece type is calculated; Based on the first remaining number of workpieces, recalculate the percentage of the first remaining processing time corresponding to the remaining workpiece type; The next allocation will be made based on the processing priority, the percentage of the first remaining processing time, and the target quantity; The allocation ends when the minimum processing time equals the average processing time.
[0012] In a second aspect, a smart terminal is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the workpiece type-based allocation method as described in the first aspect above.
[0013] Thirdly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements the workpiece type-based allocation method as described in the first aspect above.
[0014] Fourthly, a computer program product is provided, including a computer program that, when executed by a processor, implements the workpiece type-based allocation method described in the first aspect.
[0015] Fifthly, a workpiece processing production line is provided, the workpiece processing production line including the intelligent terminal described in the second aspect above and multiple processing machines arranged on the workpiece production line, the intelligent terminal implementing the workpiece type-based allocation method as described in the first aspect.
[0016] In the aforementioned scheme implemented based on workpiece type allocation, terminals, media, products, and production lines, a target number of processing machines are selected by acquiring production order information and processing machine information. Next, it is determined whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type. If it can, allocation is performed based on the urgency of the workpiece type, the proportion of processing time, and the target number of processing machines, thus optimizing the processing flow to the greatest extent. For workpiece types with high urgency, sufficient processing machine resources are prioritized to increase their processing speed and reduce production delays caused by excessive waiting time, thereby improving overall production efficiency and ensuring high-quality and timely completion of production tasks. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a flowchart of an allocation method based on workpiece type disclosed in an embodiment of the present invention; Figure 2 This is another flowchart of an allocation method based on workpiece type disclosed in an embodiment of the present invention; Figure 3 This is another flowchart of an allocation method based on workpiece type disclosed in an embodiment of the present invention; Figure 4 This is another flowchart of an allocation method based on workpiece type disclosed in an embodiment of the present invention; Figure 5 This is another flowchart of an allocation method based on workpiece type disclosed in an embodiment of the present invention; Figure 6 This is a schematic diagram of a smart terminal disclosed in an embodiment of the present invention; Figure 7 This is a schematic diagram of a workpiece processing production line disclosed in an embodiment of the present invention. Detailed Implementation
[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0020] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.
[0021] It should also be understood that the term “and / or” as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0022] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."
[0023] Furthermore, in the description of this invention and the appended claims, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.
[0024] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of the invention include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0025] The workpiece type-based allocation method provided in this invention can be widely applied in multiple fields, including but not limited to manufacturing and logistics management. For example, in manufacturing, this method can help factories quickly allocate processing machines across diverse production tasks to meet the processing needs of different workpiece types. In logistics management, this method can optimize the allocation of transportation resources. Specifically, this workpiece type-based allocation method can be applied to smart terminals. These smart terminals include, but are not limited to, various personal computers, laptops, smartphones, and tablets. The workpiece type-based allocation method provided in this invention will be described in detail below.
[0026] In one embodiment, such as Figure 1 As shown, a workpiece type-based allocation method is provided, including the following steps: S10. Obtain production order information and processing machine information.
[0027] In some implementations, the production order information includes work order details, drilling height, number of holes per board, and processing time per trip. The work order information includes workpiece type, production program, diameter table, delivery date, number of boards processed, QUIK (Quickness Limit), board thickness, number of stacks, backing plate thickness, and aluminum sheet thickness. QUIK refers to the reserved clearance height, ensuring that the machining tool does not directly contact the workpiece at the start of machining, protecting both the workpiece and the machining tool. For example, a workpiece type of "A", production program of "2M128241b08-a", diameter table of "QCB-ZG--A", delivery date of "1 day", number of boards processed of "1000", QUIK of "1.5mm", board thickness of "1.4mm", number of stacks of "3", backing plate thickness of "2.5mm", aluminum sheet thickness of "0.15mm", drilling height of "5.96mm", number of holes per board of "50", and processing time per trip of "4 minutes". The workpiece type is "B", the production program is "2303031443-l-0158526k06", the diameter table is "QCB-ZG--A", the delivery time is "1 day", the number of plates to be processed is "1000", the QUIK is "1.5mm", the plate thickness is "1.4mm", the number of stacks is "3 layers", the backing plate thickness is "2.5mm", the aluminum sheet thickness is "0.15mm", the drilling height is "5.96mm", the number of holes per plate is "30", and the processing time per pass is "5 minutes". Similarly, the workpiece type is "C", the production program is "2312121654-l-0210139a04", the diameter table is "QCB-ZG--A", the delivery time is "2 days", the number of processed plates is "500", the QUIK is "1.5mm", the plate thickness is "1.47mm", the number of stacks is "3 layers", the pad thickness is "2.5mm", the aluminum sheet thickness is "0.15mm", the drilling height is "4.7mm", the number of holes per plate is "100", and the processing time per pass is "6 minutes".
[0028] The machining machine information includes the total number of machining machines, machine model, status (e.g., running, idle, under maintenance), tool retrieval time, tool placement time, and machining efficiency. For example, the total number of machining machines is "20", the machine model is "CNC-XYZ", the status is "running", the tool retrieval time is "35 seconds", the tool placement time is "35 seconds", and the machining efficiency for workpiece A is "4 minutes / piece". It should be noted that the above is only an example and does not constitute a limitation of the present invention.
[0029] By acquiring the above two types of information, the intelligent terminal can better allocate processing machines to workpieces of different types, thereby optimizing the efficiency of processing machine utilization and ensuring that all workpieces are processed within the specified delivery period.
[0030] S20. Based on the production order information and the processing machine information, select a target number of processing machines for processing.
[0031] In some implementations, after obtaining the production order information and processing machine information, the next step is to display this information and then receive the user's initial target number of processing machines selected based on this information. This process, by receiving the user's initial target number of processing machines, demonstrates human-computer interaction and flexibility. Users can make more reasonable choices by combining practical experience with the current status of the processing machines, which helps improve the accuracy and efficiency of production scheduling and fully considers the user's role in production decision-making.
[0032] S30. Determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type.
[0033] In some implementations, after receiving the user's initial target number of processing machines, it is further determined whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified for each workpiece type in the production order information. As an example, the total processing time required to process all workpiece types and the total average daily processing time for each workpiece type can be calculated based on the production order information to determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified for each workpiece type in the production order information. It should be understood that the target processing time represents the time required to complete the processing of all workpieces corresponding to that workpiece type.
[0034] Specifically, such as Figure 2 As shown, the production processing order information includes work order information and single-trip processing time. The work order information includes the number of processing boards and the delivery date. The step of determining whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type includes the following steps: S30A. Based on the number of processing plates and the single-pass processing time, the target processing time corresponding to each workpiece type is obtained; S30B. Based on the target processing time and the delivery date, obtain the average daily processing time corresponding to each workpiece type; S30C: Sum the target processing times for all workpiece types to obtain the total processing time; S30D: Summarize the average daily processing time for all workpiece types to obtain the total average daily processing time. S30E: Based on the total processing time and the total average daily processing time, determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period corresponding to each workpiece type specified in the production processing order information.
[0035] In some implementations, the production processing order information includes work order information and single-trip processing time, where the work order information includes the number of processing plates and the delivery date. First, based on the number of processing plates and single-trip processing time for each workpiece type, the target processing time for each workpiece type is calculated. For example, if workpiece A has 1000 processing plates and a single-trip processing time of 4 minutes, then its target processing time is 1000 × 4 = 4000 minutes. If workpiece B has 1000 processing plates and a single-trip processing time of 5 minutes, then its target processing time is 1000 × 5 = 5000 minutes. Similarly, if workpiece C has 500 processing plates and a single-trip processing time of 6 minutes, then its target processing time is 500 × 6 = 3000 minutes.
[0036] Next, based on the target processing time and specified delivery date for each workpiece type, the average daily processing time for each workpiece type is calculated. Assume the delivery date for workpiece A is 1 day, for workpiece B is 1 day, and for workpiece C is 2 days. Then, the average daily processing time for workpiece A is 4000 / 1 = 4000 minutes, for workpiece B it is 5000 / 1 = 5000 minutes, and for workpiece C it is 3000 / 2 = 1500 minutes.
[0037] Then, the target processing time for all workpiece types is summed to obtain the total processing time. For example, assuming there are workpieces A, B, and C in this case, the total processing time is 4000 minutes + 5000 minutes + 3000 minutes = 12000 minutes. Similarly, the average daily processing time for all workpiece types is also summed to obtain the total average daily processing time, which in this case is 4000 minutes + 5000 minutes + 1500 minutes = 10500 minutes.
[0038] Next, based on the total processing time and the total average daily processing time, it is determined whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type. That is, by using formulas (1) and (2), it is determined whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type.
[0039] Formula (1) Formula (2) in, This represents the maximum delivery date in the production order information.
[0040] As an example, suppose 8 processing machines are selected. In this case, the total processing capacity of the selected machines within the maximum delivery period is 8 machines × 2 (maximum delivery period) × 24 hours × 60 minutes = 23040 minutes, and the total daily processing capacity is 8 machines × 24 hours × 60 minutes = 11520 minutes. Since 23040 minutes is greater than 12000 minutes and 11520 minutes is greater than 12000 minutes, it indicates that the selected target number of processing machines can complete the processing of all workpieces within the delivery period.
[0041] As another example, suppose 4 processing machines are selected. In this case, the total processing capacity of the selected machines within the maximum delivery period is 4 machines × 2 (maximum delivery period) × 24 hours × 60 minutes = 11520 minutes. Since 11520 minutes is less than 12000 minutes, it means that the selected number of processing machines cannot complete the processing of all workpieces within the delivery period. Therefore, the number of selected machines is automatically increased by 1. The number of processing machines after the increase is now 5, and the corresponding total processing capacity is 5 machines × 2 (maximum delivery period) × 24 hours × 60 minutes = 14400 minutes. Since 1440 minutes is greater than 12000 minutes, we continue to judge whether the daily processing capacity is greater than the total daily average processing time. Since the daily processing capacity is 5 machines × 24 hours × 60 minutes = 7200 minutes which is less than 10500 minutes, it means that the selected target number of processing machines cannot complete the processing of all workpieces within the delivery period. At this time, we continue to increase the number of processing machines until the conditions of formula (1) and formula (2) are met. Here, it is 8 machines. Then we determine that the selected target number of processing machines can complete the processing of all workpieces within the delivery period.
[0042] Through the above steps, the capability of the selected target number of processing machines to complete the processing of each workpiece type in the production order information on time has been fully evaluated, thus providing reliable data support and decision-making basis for subsequent dynamic allocation. Furthermore, it can adapt to the production capacity of factories of different sizes, allowing large factories to find the minimum number of processing machines to reduce costs through quantity, while small factories can minimize order processing time to increase order volume and efficiency. For example, small factories can select more idle processing machines for processing, thereby increasing order volume and efficiency.
[0043] The processing machine information includes tool retrieval time and tool release time, and the single-trip processing time is determined in the following way: Based on the work order information, the drilling height and number of holes in each workpiece type are calculated using the machining program; Based on the tool retrieval time, the tool release time, the drilling height, the number of holes in the single plate, and the processing path time, the single-pass processing time corresponding to each workpiece type is obtained; The machining path duration represents the time required for the machining tool to move from the starting point to the target machining point.
[0044] In some implementations, both the tool retrieval time and the tool placement time can be set to 35 seconds per cycle, which is not a limitation here. As an example, based on the workpiece type, production program, diameter table, delivery date, number of processed plates, QUIK, plate thickness, stack number, backing plate thickness, and aluminum sheet thickness in the work order information, a pre-set processing program can be invoked to calculate the drilling height and number of holes per plate corresponding to each workpiece type.
[0045] Next, based on the calculated drilling height, number of holes in a single plate and feed speed, the feed time is calculated using formula (5); based on the calculated drilling height, number of holes in a single plate and retraction speed, the retraction time is calculated using formula (6).
[0046] Formula (5) Formula (6) in, This refers to the feed rate (e.g., 200 m / min). Where N is the retraction speed (e.g., 100 m / min), Z is the number of holes in a single plate, and Z is the drilling depth. .
[0047] Then, based on the coordinates of the starting point of the machining tool to the target machining point, the maximum value S of one of the X and Y directions between the two coordinate points is calculated. Then, the corresponding machining path duration is calculated according to formula (7).
[0048] or Formula (7) in, Let X be the acceleration in the direction of travel (assuming, =1.4 ), The acceleration in the Y direction ( =1.2 S is the maximum value of one of the X and Y directions between the two coordinate points from the starting point to the target processing point.
[0049] Finally, the single-trip machining time is: Single-trip machining time = Tool retrieval time + Tool placement time + Tool feed time + Tool retraction time + Machining path time.
[0050] Taking workpiece A as an example, its single-pass machining time is calculated as follows: 35 seconds (tool retrieval time) + 35 seconds (tool placement time) + 75 seconds (tool feed time) + 75 seconds (tool retraction time) + 20 seconds (machining path time) = 240 seconds = 4 minutes.
[0051] It should be noted that the above is merely an example and does not constitute a limitation of the present invention.
[0052] It should be understood that when calculating the number of holes in a single board, it is necessary to determine whether a hole enlargement command (e.g., G84R) or a slotting command (e.g., G85) is included. If a hole enlargement command is included, the number of holes in the single board is calculated based on the perimeter of the enlarged hole. If a slotting command is included, the number of holes in the single board is calculated using the coordinates of the two holes.
[0053] S40. If it can be completed, calculate the processing urgency and processing time percentage of each workpiece type in the production processing order information.
[0054] In one embodiment, if the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type, the urgency and processing time percentage of each workpiece type will be further calculated. Specifically, according to steps S30A to S30D, the total processing time for all workpiece types and the target processing time for each workpiece type can be calculated first; then, as... Figure 3 As shown in steps S41 to S42, the processing urgency and processing time percentage of each workpiece type are calculated.
[0055] S41. Based on the target processing time, the delivery date, and the urgency coefficient, the processing urgency level corresponding to each workpiece type is obtained, wherein the urgency coefficient is determined by the delivery date.
[0056] In some implementations, the target processing time, delivery date and urgency coefficient for each workpiece type can be calculated using formula (8) to obtain the processing urgency level for each workpiece type.
[0057] Formula (8) The urgency coefficient is: .
[0058] As an example, suppose the target processing time for workpiece A is 4000 minutes and the delivery time is 1 day; the target processing time for workpiece B is 5000 minutes and the delivery time is 1 day; and the target processing time for workpiece C is 3000 minutes and the delivery time is 2 days.
[0059] For workpiece A, the urgency level A of processing is calculated using formula (8): For workpiece B, the urgency level B of processing is calculated using formula (8): For workpiece C, the urgency level C of processing is calculated using formula (8): Calculations show that the urgency level for processing workpiece A is 4000, for workpiece B it is 5000, and for workpiece C it is 375. It should be understood that a higher urgency value indicates greater urgency. Therefore, the urgency ranking is: Workpiece B > Workpiece A > Workpiece C.
[0060] S42. Based on the total processing time and the target processing time, obtain the processing time percentage corresponding to each workpiece type.
[0061] In some implementations, the total processing time for all workpiece types and the target processing time for each workpiece type can be calculated using formula (9) to obtain the percentage of processing time for each workpiece type.
[0062] Formula (9) As an example, let's continue with the case where the target processing time for workpiece A is 4000 minutes, the target processing time for workpiece B is 5000 minutes, and the target processing time for workpiece C is 3000 minutes. In this case, the corresponding total processing time is 12000 minutes, which is obtained by adding the target processing times for workpieces A, B, and C together.
[0063] For workpiece A, A is calculated using formula (9): For workpiece B, B is calculated using formula (9): For workpiece C, C is calculated using formula (9): Through the above steps, the urgency level and processing time ratio of each workpiece type were calculated, providing a data foundation for subsequent machine allocation and ensuring that workpieces with urgent workpiece types are prioritized during production, thereby improving production efficiency and delivery capability.
[0064] S50. Based on the processing urgency, the processing time percentage, and the target quantity, allocate processing machines to the workpieces corresponding to each workpiece type.
[0065] In some implementations, workpieces can be initially prioritized based on their processing urgency to ensure that the most urgent workpiece types are processed first. Subsequently, processing machines are dynamically allocated based on the processing time percentage of each workpiece type and the number of selected processing machines (i.e., the target number) to optimize production efficiency. This ensures that adjustments are made continuously throughout the processing process based on real-time progress and the target number, guaranteeing that all workpieces are completed with high quality within the specified time.
[0066] In one embodiment, such as Figure 4 As shown, in step S50, which involves allocating processing machines to each workpiece type based on the urgency of processing, the proportion of processing time, and the target quantity, the process includes the following steps: S51. Sort all the workpiece types according to the urgency of processing to determine the processing priority; S52. Based on the processing priority, the target quantity, and the processing time ratio of each processing priority corresponding to the workpiece type, a first allocation is performed to determine the target number of machines allocated to each workpiece type. S53. Based on the target processing time and the target number of machines, obtain the first processing time corresponding to each workpiece type; S54. Based on the first processing time corresponding to each workpiece type and the average processing time of the processing machine, perform the next allocation; The average processing time of the processing machine is determined by the total processing time and the target number of processing machines.
[0067] In some implementations, workpiece types are sorted according to their previously calculated processing urgency to determine their processing priority. For example, in the previous calculations, workpiece A has a processing urgency of 4000, workpiece B has a processing urgency of 5000, and workpiece C has a processing urgency of 375. The sorting result is: workpiece B > workpiece A > workpiece C, that is, the processing priority is workpiece B > workpiece A > workpiece C.
[0068] Next, based on the determined processing priority, the target number of processing machines, and the processing time ratio of each workpiece type, the first allocation is carried out to determine the target number of machines allocated to each workpiece type.
[0069] Assuming the target number is 8 processing machines, the processing time of workpiece B accounts for 0.42, the processing time of workpiece A accounts for 0.33, and the processing time of workpiece C accounts for 0.25.
[0070] According to the allocation rules, the target number of machines allocated to workpiece B = target quantity × processing time percentage = 8 × 0.42 ≈ 0.36 (rounded up to 4 machines, allocated to processing machines 1, 2, 3, and 4). The target number of machines assigned to workpiece A = 8 × 0.33 ≈ 2.64 (rounded up to 3 machines, assigned to processing machines 5, 6, and 7). The target number of machines assigned to workpiece C = 8 × 0.25 ≈ 2 (due to the limitation on the target number of processing machines, we take 1 machine). After the first allocation is completed, the first processing time for each workpiece type will be calculated based on the target processing time and the target number of machines for each workpiece type.
[0071] Assuming the target processing time for workpiece A is 4000 minutes and the target number of machines is 3, the first processing time for workpiece A is approximately 4000 / 3 ≈ 1333.33 minutes. Similarly, the target processing time for workpiece B is 5000 minutes and the target number of machines is 4, so the first processing time for workpiece B is 1250 minutes. The target processing time for workpiece C is 3000 minutes and the target number of machines is 1, so the first processing time for workpiece C is 3000 minutes.
[0072] Next, based on the initial processing time for each workpiece type, a first production plan is generated. This plan is then sent to the selected target processing machine, and confirmation of order acceptance is received from the machine, commencing the first processing run. Then, based on the initial processing time for each workpiece type and the average processing time of the processing machine, the next allocation is performed until all workpieces in the production order are processed. The average processing time of the processing machine is determined by the total processing time for all workpiece types and the target number of processing machines. For example, if the total processing time is 12,000 minutes and the target number is 8 machines, then the average processing time of the processing machine = total processing time / target number = 12,000 / 8 = 1,500 minutes.
[0073] This dynamic allocation method enables the rational scheduling of processing machines based on real-time processing conditions and urgency, thereby achieving optimal resource allocation, improving production efficiency, and ensuring that all workpieces are processed on time.
[0074] Furthermore, such as Figure 5As shown, in step S54, which is the process of allocating the next processing time based on the first processing time corresponding to each workpiece type and the average processing time of the processing machine, the following steps are included: S541. Select the minimum value from the first processing time corresponding to each workpiece type and the average processing time of the processing machine as the minimum processing time.
[0075] In step S541, a minimum processing time is determined based on the first processing time of each workpiece type and the average processing time of the current processing machines. This minimum processing time indicates that, in the current processing state, all workpieces corresponding to that workpiece type have been processed or the time limit of any processing machine has been reached. For example, for workpiece B, its target processing time is 5000, and it is allocated to 4 processing machines, each with a processing time of 1250 minutes. In this case, when the minimum processing time is 1250 minutes, it indicates that all workpieces corresponding to workpiece type B have been processed.
[0076] S542. When the minimum processing time is the first processing time corresponding to any of the workpiece types, the first remaining number of workpieces corresponding to each workpiece type is calculated.
[0077] In step S541, if the determined minimum processing time is the same as the first processing time for any workpiece type, proceed to step S542. In this step, the first remaining workpiece number corresponding to all current workpiece types is calculated. The first remaining workpiece number refers to the number of workpieces of all workpiece types that have not yet been completed after the first allocation cycle. At this time, processing machines can be reallocated based on the remaining workpieces corresponding to each workpiece type.
[0078] S543. Based on the first remaining number of workpieces, recalculate the percentage of the first remaining processing time corresponding to the remaining workpiece type.
[0079] In step S543, the first remaining processing time percentage is calculated by the number of remaining workpieces corresponding to the unfinished workpiece type and the total number of remaining workpieces of the current unfinished workpiece type, and is used to measure the number of processing machines that the workpieces corresponding to the unfinished workpiece type should obtain in the subsequent allocation.
[0080] As an example, when workpiece B has been completed, the remaining number of workpieces corresponding to workpiece A is 63, and the remaining number of workpieces corresponding to workpiece C is 292. Then, the remaining target processing time for workpiece A is 63 × 4 = 252 minutes, and the remaining target processing time for workpiece C is 292 × 6 = 1752 minutes. At this time, the proportion of the first remaining processing time for workpiece A is 252 / (252 + 1752) ≈ 0.13, and the proportion of the first remaining processing time for workpiece C is 1752 / (252 + 1752) ≈ 0.87.
[0081] S544. Based on the processing priority, the percentage of the first remaining processing time, and the target quantity, perform the next allocation.
[0082] In step S544, this allocation process will continue to allocate based on the processing priority calculated above, combined with the first remaining processing time percentage and target quantity for each workpiece type calculated at the current time.
[0083] As an example, taking the calculation in step S543, where the percentage of the first remaining processing time for workpiece A is 0.13 and the percentage of the first remaining processing time for workpiece C is 0.87, the number of processing machines assigned to workpiece A next time is 0.13 × 8 = 1.04 (rounded up to 2, assigned to processing machines 5 and 6), and the number of processing machines assigned to workpiece C next time is 8 - 2 = 6 (assigned to processing machines 1, 2, 3, 4, 7, and 8).
[0084] S545. When the minimum processing time is equal to the average processing time, the allocation ends.
[0085] In step S545, if the determined minimum processing time is the average processing time of the current processing machine, it is determined whether all workpieces corresponding to each workpiece type have been processed. If all workpieces have been processed, the allocation ends. If there are unfinished workpiece types, the second remaining number of workpieces corresponding to the unfinished workpiece types is obtained and evenly allocated to the target number of processing machines. This ensures that all workpiece tasks in the production processing order information can be completed efficiently, and also ensures that the running time of the processing machines is roughly the same, reducing factory maintenance costs.
[0086] The above steps S541 to S545 combine the first processing time corresponding to each workpiece type with the average processing time of the processing machine, and adopt a dynamic allocation method. This allows for the reasonable allocation of resources across tasks of various workpiece types, optimization of production plans, and ensures that the running time of the processing machine is roughly the same, thereby reducing factory maintenance costs.
[0087] The following is a complete example of the embodiment described in step S50 above: Suppose there are three types of workpieces, A, B, and C, which require 4000 minutes, 5000 minutes, and 3000 minutes to complete their respective processing. The target number of processing machines allocated are 3, 4, and 1, respectively.
[0088] Therefore, the processing time required for each type of workpiece is calculated, that is, the processing time for the first processing.
[0089] At this point, the first processing time for workpiece A is 1333.33 minutes; The first processing time for workpiece B is 1250 minutes; The first processing time for workpiece C is 3000 minutes.
[0090] In this case, the average processing time of the processing machine is 1500 minutes. Therefore, the minimum processing time is the minimum of the first processing time corresponding to each workpiece type and the average processing time of the machine, which is 1250 minutes in this embodiment.
[0091] After 1250 minutes, the processing results for each workpiece type were calculated. Workpiece A's processing quantity was 1250 minutes divided by 4 and then multiplied by 23, resulting in 937 pieces, with 63 pieces remaining. Workpiece B completed processing all 1000 pieces and met the delivery deadline (i.e., 1250 divided by 60 multiplied by 40 = 0.86 days, less than 1 day). Workpiece C completed 208 pieces, with 292 pieces remaining. Subsequently, the processing time percentage for the remaining workpiece types was recalculated to ensure more accurate allocation in subsequent steps. Based on this, the second processing time for workpiece A was calculated as 63 multiplied by 4, or 252 minutes, while the second processing time for workpiece C was calculated as 292 multiplied by 6, or 1752 minutes.
[0092] Based on this, the number of machines required to process workpiece A is calculated as 252 minutes divided by 252 plus 1752 multiplied by 8, resulting in approximately 2. This number is assigned to machines 5 and 6. The number of machines required to process workpiece C is 8 minus 2, resulting in 6 machines, which are assigned to machines 1, 2, 3, 4, 7, and 8.
[0093] Next, the second time allocation calculation will begin. For workpiece A, the second processing time will be 252 minutes divided by 2, resulting in 126 minutes; for workpiece C, it will be 1752 minutes divided by 6, resulting in 292 minutes. The average processing time of the processing machine also needs to be calculated. Considering the already processed time of 1250 minutes, the average processing time becomes 250 minutes. Therefore, the minimum processing time for the second time is 126 minutes. After 126 minutes, the processing status of each workpiece type will be reassessed. The processing quantity for workpiece A is 126 minutes divided by 4 and multiplied by 2, resulting in 63 pieces, which are completed. Workpiece C has completed 126 pieces of processing, and the remaining number of workpieces is 292 minus 126, resulting in 166 pieces.
[0094] In this stage, all processing machines are used for processing workpiece C. The remaining 166 workpieces of workpiece C will be calculated by multiplying 166 by 6 and dividing by 8, resulting in 124.5 minutes. Ultimately, the total processing time of the processing machines will accumulate to 1500.5 minutes.
[0095] It should be noted that the above is merely an example and does not constitute a limitation of the present invention.
[0096] In summary, one embodiment of the present invention selects a target number of processing machines by acquiring production order information and processing machine information. This process allows resource allocation to better align with actual production needs, avoiding idle or overused processing machines. Next, it is determined whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type, ensuring timely production. When completion is possible, allocation is based on the urgency of the workpiece type, the proportion of processing time, and the target number of processing machines, maximizing the optimization of the processing flow. For workpiece types with high urgency, sufficient processing machine resources are prioritized, increasing their processing speed and reducing production delays caused by excessive waiting time, thereby improving overall production efficiency and ensuring high-quality and timely completion of production tasks.
[0097] Secondly, such as Figure 6 As shown, the present invention also discloses a smart terminal, the internal structure of which can be illustrated as follows: Figure 6As shown, the intelligent terminal includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the intelligent terminal is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the workpiece type-based allocation method provided in the above embodiment.
[0098] In one embodiment, a smart terminal is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps: Obtain production order information and processing machine information; Based on the production order information and the processing machine information, select a target number of processing machines for processing; Determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type; If it can be completed, then calculate the processing urgency and processing time percentage of each workpiece type in the production processing order information; Based on the urgency of processing, the percentage of processing time, and the target quantity, processing machines are allocated to the workpieces corresponding to each workpiece type.
[0099] Thirdly, embodiments of this application disclose a computer-readable storage medium that, when executed by a processor in a smart terminal, enables the smart terminal to perform various steps of any embodiment of an assignment method based on workpiece type disclosed in this invention. The computer-readable storage medium may be non-volatile or volatile.
[0100] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: Obtain production order information and processing machine information; Based on the production order information and the processing machine information, select a target number of processing machines for processing; Determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type; If it can be completed, then calculate the processing urgency and processing time percentage of each workpiece type in the production processing order information; Based on the urgency of processing, the percentage of processing time, and the target quantity, processing machines are allocated to the workpieces corresponding to each workpiece type.
[0101] Fourthly, the present invention discloses a computer program product, including a computer program that, when executed by a processor, implements the workpiece type-based allocation method disclosed in any of the above embodiments.
[0102] In one embodiment, a computer program product is provided, which, when executing a computer program, performs the following steps: Obtain production order information and processing machine information; Based on the production order information and the processing machine information, select a target number of processing machines for processing; Determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type; If it can be completed, then calculate the processing urgency and processing time percentage of each workpiece type in the production processing order information; Based on the urgency of processing, the percentage of processing time, and the target quantity, processing machines are allocated to the workpieces corresponding to each workpiece type.
[0103] Fifthly, such as Figure 7 As shown, a workpiece processing production line is provided, which includes the intelligent terminal described in the second aspect above and multiple processing machines arranged on the workpiece production line. The intelligent terminal performs the following steps: Obtain production order information and processing machine information; Based on the production order information and the processing machine information, select a target number of processing machines for processing; Determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type; If it can be completed, then calculate the processing urgency and processing time percentage of each workpiece type in the production processing order information; Based on the urgency of processing, the percentage of processing time, and the target quantity, processing machines are allocated to the workpieces corresponding to each workpiece type.
[0104] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A workpiece type-based allocation method, characterized in that, include: Obtain production order information and processing machine information; Based on the production order information and the processing machine information, select a target number of processing machines for processing; Determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type; If it can be completed, then calculate the processing urgency and processing time percentage of each workpiece type in the production processing order information; Based on the urgency of processing, the percentage of processing time, and the target quantity, processing machines are allocated to the workpieces corresponding to each workpiece type.
2. The workpiece type-based allocation method as described in claim 1, characterized in that, The production processing order information includes work order information and single-trip processing time. The work order information includes the number of boards processed and the delivery date. The determination of whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production order information for each workpiece type includes: Based on the number of processing plates and the single-pass processing time, the target processing time corresponding to each workpiece type is obtained; Based on the target processing time and the delivery date, the average daily processing time corresponding to each workpiece type is obtained; The total processing time is obtained by summing the target processing times for all workpiece types. The average daily processing time for all workpiece types is summarized to obtain the total average daily processing time. Based on the total processing time and the total average daily processing time, determine whether the selected target number of processing machines can complete the processing of all workpieces within the delivery period specified in the production processing order information for each workpiece type.
3. The workpiece type-based allocation method as described in claim 2, characterized in that, The processing machine information includes tool retrieval time and tool placement time, and the single-trip processing time is determined in the following way: Based on the work order information, the drilling height and number of holes in each workpiece type are calculated using the machining program; Based on the tool retrieval time, the tool release time, the drilling height, the number of holes in the single plate, and the processing path time, the single-pass processing time corresponding to each workpiece type is obtained; The machining path duration represents the time required for the machining tool to move from the starting point to the target machining point.
4. The workpiece type-based allocation method as described in claim 2, characterized in that, The calculation of the processing urgency and processing time percentage for each workpiece type in the production processing order information includes: Based on the target processing time, the delivery date, and the urgency coefficient, the processing urgency level corresponding to each workpiece type is obtained, wherein the urgency coefficient is determined by the delivery date; Based on the total processing time and the target processing time, the percentage of processing time corresponding to each workpiece type is obtained.
5. The workpiece type-based allocation method as described in claim 2, characterized in that, The step of allocating processing machines to workpieces corresponding to each workpiece type based on the urgency of processing, the proportion of processing time, and the target quantity includes: Based on the urgency of the processing, all workpiece types are sorted to determine processing priority; Based on the processing priority, the target quantity, and the processing time ratio of each workpiece type corresponding to the processing priority, a first allocation is performed to determine the target number of machines allocated to each workpiece type. Based on the target processing time and the target number of machines, the first processing time corresponding to each workpiece type is obtained; The next allocation is made based on the first processing time corresponding to each workpiece type and the average processing time of the processing machine. The average processing time of the processing machine is determined by the total processing time and the target number of processing machines.
6. The workpiece type-based allocation method as described in claim 5, characterized in that, The next allocation based on the first processing time corresponding to each workpiece type and the average processing time of the processing machine includes: The minimum value is selected from the first processing time corresponding to each workpiece type and the average processing time of the processing machine as the minimum processing time; When the minimum processing time is the first processing time corresponding to any of the workpiece types, the first remaining number of workpieces corresponding to each workpiece type is calculated; Based on the first remaining number of workpieces, recalculate the percentage of the first remaining processing time corresponding to the remaining workpiece type; The next allocation will be made based on the processing priority, the percentage of the first remaining processing time, and the target quantity; The allocation ends when the minimum processing time equals the average processing time.
7. A smart terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the workpiece type-based allocation method as described in any one of claims 1 to 6.
8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the workpiece type-based allocation method as described in any one of claims 1 to 6.
9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the workpiece type-based allocation method according to any one of claims 1 to 6.
10. A workpiece processing production line, characterized in that, The workpiece processing production line includes the intelligent terminal as described in claim 7 and a plurality of processing machines arranged on the workpiece production line, wherein the intelligent terminal implements the workpiece type-based allocation method as described in any one of claims 1 to 6.