A scheduling scheme determination method and device for large-scale discrete manufacturing

Abstract

The application provides a scheduling scheme determination method and device for large-scale discrete manufacturing industry, and the method comprises the following steps: performing preliminary scheduling on a project set to be scheduled based on scheduling mandatory constraints to obtain multiple benchmark feasible solutions of the scheduling scheme; determining scheduling non-mandatory constraints and a scheme optimization objective function based on dynamic scheduling requirements; optimizing the multiple benchmark feasible solutions based on the scheduling non-mandatory constraints to obtain multiple optimized feasible solutions; inputting the multiple optimized feasible solutions into the scheme optimization objective function to obtain multiple function values, and taking the optimized feasible solution corresponding to the function value meeting the requirement of the scheme optimization objective function as a target scheduling scheme. The application divides the scheduling scheme determination process into the solving of multiple benchmark feasible solutions and the determination of a target scheduling scheme adapted to dynamic scheduling requirements, can adaptively obtain different target scheduling schemes according to different dynamic scheduling requirements, and improves the flexibility and robustness of the target scheduling scheme.

Description

Technical Field

[0001] This invention relates to the field of production control technology, specifically to a method and apparatus for determining scheduling schemes in large-scale discrete manufacturing. Background Technology

[0002] Production scheduling refers to breaking down an order into multiple production projects, then comprehensively considering factors such as order delivery dates, task difficulty, characteristics and limitations of different tasks, and arranging the execution time and sequence of each project to ensure smooth production and on-time order delivery. For manufacturing plants, production scheduling is a crucial task.

[0003] Existing scheduling techniques are generally used in companies with stable products. For stable products, the production projects (tasks) and processes are relatively fixed, making scheduling solutions easier to determine. However, for companies in large-scale discrete manufacturing, the production model is mainly multi-variety, small-batch, order-based, and even involves a mix of research and development with mass production. This production model is characterized by variable plans, complex processes, numerous job types, long processing times, and high uncertainty in production conditions. Therefore, scheduling techniques suitable for stable products need to consider numerous constraints and scheduling parameters when applied to large-scale discrete manufacturing scenarios, resulting in long calculation times, low efficiency in determining scheduling solutions, and even the inability to obtain effective scheduling solutions.

[0004] Therefore, there is an urgent need to provide a scheduling scheme determination method and apparatus for large-scale discrete manufacturing, so as to make it applicable to large-scale discrete manufacturing and improve the efficiency and robustness of scheduling scheme determination in large-scale discrete manufacturing scenarios. Summary of the Invention

[0005] In view of this, it is necessary to provide a scheduling scheme determination method and apparatus for large-scale discrete manufacturing, so as to solve the technical problem that the existing technology is not applicable to large-scale discrete manufacturing scenarios, resulting in low efficiency in determining scheduling schemes or even the inability to obtain effective scheduling schemes.

[0006] Firstly, in order to solve the above-mentioned technical problems, the present invention provides a method for determining scheduling schemes for large-scale discrete manufacturing, comprising:

[0007] Based on the scheduling constraint, a preliminary scheduling is performed on the set of projects to be scheduled, and multiple baseline feasible solutions for the scheduling scheme are obtained.

[0008] Determine the non-mandatory scheduling constraints and the objective function for scheme optimization based on dynamic scheduling requirements;

[0009] Based on the aforementioned non-mandatory scheduling constraints, the multiple baseline feasible solutions are optimized to obtain multiple optimized feasible solutions;

[0010] The multiple optimized feasible solutions are input into the scheme optimization objective function to obtain multiple function values. The optimized feasible solution corresponding to the function value that satisfies the requirements of the scheme optimization objective function is taken as the target scheduling scheme.

[0011] In one possible implementation, the mandatory scheduling constraint is a constraint that must be satisfied when scheduling any set of projects, and the non-mandatory scheduling constraint is a constraint that must be satisfied when scheduling at least one set of projects, corresponding to the dynamic scheduling requirement.

[0012] The mandatory scheduling constraints include process dependency constraints, material supply constraints, and bottleneck process priority constraints. When the dynamic scheduling requirement is a short project delivery time, the non-mandatory scheduling constraints include mold / auxiliary tool changeover time constraints, bottleneck resource priority constraints, and project task priority constraints.

[0013] In one possible implementation, the project set includes multiple projects, and each project includes multiple processes; when the dynamic scheduling requirement is a short project delivery time, the objective function for optimizing the solution is determined based on the dynamic scheduling requirement, including:

[0014] Identify multiple process chains in the project and determine the process chain duration of each process chain, and take the process chain duration with the longest duration as the critical chain duration;

[0015] The time difference between the start and end times of the project is taken as the project cycle, and the time difference between the start time of the project and the start time of the first process in the project is taken as the project delivery value.

[0016] The critical chain impact factor is determined based on the critical chain duration and the project cycle, and the project delivery time impact factor is determined based on the project cycle and the project delivery time value.

[0017] The sum of the critical chain impact factor and the project delivery date impact factor is used as the objective function for optimizing the scheme.

[0018] In one possible implementation, the objective function of the scheme is:

[0019]

[0020]

[0021] In the formula, Optimize the objective function for the solutions to the project set; For the first x The objective function for optimizing the scheme of each project; Key chain impact factor; Factors affecting project delivery time;m This represents the total number of items in the project collection. For the first x The critical chain duration of each project; For the first x Project cycle of each project; For the first x The project delivery value of each project; This is the critical chain length weighting coefficient; Weighting coefficient for project delivery options.

[0022] In one possible implementation, determining the process chain duration of each process chain includes:

[0023] Obtain multiple processes in the process chain;

[0024] Determine the planned duration of each of the aforementioned processes and the time interval between adjacent processes;

[0025] The process chain duration is the sum of the planned duration of the multiple processes and the duration between the processes.

[0026] In one possible implementation, determining the planned duration of each of the said processes includes:

[0027] Obtain the initial planned duration of the process, as well as the process type, number of production runs, and frequency of overdue occurrences for the process;

[0028] The duration correction factor for the process is determined based on the process type, the number of production runs, and the frequency of overdue occurrences.

[0029] The planned duration of the process is adjusted using the duration adjustment factor to obtain the planned duration of the process.

[0030] In one possible implementation, determining the plurality of process chains includes:

[0031] Obtain multiple initial process chains and determine the key process chain among the multiple initial process chains, wherein the key process chain is the initial process chain with the longest process chain duration;

[0032] Determine whether the intervals between processes in the critical process chain can be shortened;

[0033] If so, then shorten the interval between processes; if not, then split the key process chain based on production resources to obtain multiple split chains.

[0034] The plurality of split chains and the plurality of initial process chains other than the critical process chain are referred to as the plurality of process chains.

[0035] In one possible implementation, after optimizing the plurality of baseline feasible solutions based on the non-mandatory scheduling constraints to obtain a plurality of optimized feasible solutions, the method further includes:

[0036] Obtain the occupancy status of production resources, and adjust the multiple optimized feasible solutions based on the occupancy status.

[0037] In one possible implementation, the method further includes:

[0038] With the target scheduling scheme as the center, and the preset parameter range as the trial range, multiple trial solutions are determined;

[0039] The multiple trial solutions are input into the scheme optimization objective function to obtain multiple trial values. The trial solution corresponding to the trial value that satisfies the requirements of the scheme optimization objective function is taken as the optimized scheduling scheme.

[0040] Secondly, the present invention also provides a scheduling scheme determination device for large-scale discrete manufacturing, comprising:

[0041] The initial scheduling unit is used to perform preliminary scheduling on the set of items to be scheduled based on scheduling constraints, and to obtain multiple baseline feasible solutions for the scheduling scheme.

[0042] The scheduling objective determination unit is used to determine the non-mandatory scheduling constraints and the objective function for scheme optimization based on dynamic scheduling requirements.

[0043] The baseline feasible solution optimization unit is used to optimize the multiple baseline feasible solutions based on the scheduling non-mandatory constraints to obtain multiple optimized feasible solutions;

[0044] The target scheduling scheme determination unit is used to input the multiple optimized feasible solutions into the scheme optimization objective function, obtain multiple function values ​​accordingly, and take the optimized feasible solution corresponding to the function value that satisfies the requirements of the scheme optimization objective function as the target scheduling scheme.

[0045] The beneficial effects of this invention are as follows: The scheduling scheme determination method for large-scale discrete manufacturing provided by this invention first performs an initial scheduling based on the scheduling mandatory constraints of the project set to be scheduled, obtaining multiple baseline feasible solutions for the scheduling scheme, realizing the same solution for all project sets. Then, based on the scheduling non-mandatory constraints determined by dynamic scheduling requirements, the multiple baseline feasible solutions are optimized to obtain multiple optimized feasible solutions. This realizes the optimization of the baseline feasible solutions according to dynamic scheduling requirements, improves the matching degree between the optimized feasible solutions and the actual scheduling requirements, and thus increases the probability of obtaining a scheduling scheme, that is, improves the robustness of the scheduling scheme determination method. Furthermore, after obtaining multiple optimized feasible solutions, this invention also determines the target scheduling scheme among the multiple optimized feasible solutions by using the scheme optimization objective function determined based on the dynamic scheduling requirements, ensuring the matching degree between the target scheduling scheme and the dynamic scheduling requirements, that is, improving the accuracy of the target scheduling scheme.

[0046] Furthermore, this invention divides the complex solution process in large-scale discrete manufacturing scenarios into solving multiple baseline feasible solutions applicable to all project sets and target scheduling schemes applicable to the characteristic requirement of dynamic scheduling. This achieves the division of complex solution problems, thereby improving the efficiency of determining target scheduling schemes and obtaining different target scheduling schemes according to different adaptability requirements of dynamic scheduling, thus improving the flexibility and robustness of target scheduling schemes. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0048] Figure 1 A schematic flowchart of an embodiment of the scheduling scheme determination method for large-scale discrete manufacturing provided by the present invention;

[0049] Figure 2 A schematic diagram of an embodiment of the process dependency constraint provided by the present invention;

[0050] Figure 3 For the present invention Figure 1 A schematic diagram of an embodiment of determining the objective function for scheme optimization in step S102;

[0051] Figure 4 For the present invention Figure 3 A flowchart illustrating an embodiment of determining the process chain duration in step S301;

[0052] Figure 5 For the present invention Figure 4 A flowchart illustrating an embodiment of determining the planned duration of the process in step S402;

[0053] Figure 6 For the present invention Figure 3 A flowchart illustrating an embodiment of determining multiple process chains in step S301;

[0054] Figure 7 A schematic diagram of an embodiment of the present invention for splitting the process chain;

[0055] Figure 8 This is a schematic diagram of an embodiment of the scheduling scheme determination device for large-scale discrete manufacturing provided by the present invention. Detailed Implementation

[0056] 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 a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0057] It should be understood that the illustrative drawings are not drawn to scale. The flowcharts used in this invention illustrate operations implemented according to some embodiments of the invention. It should be understood that the operations in the flowcharts may be implemented out of order, and steps without logical contextual relationships may be reversed or performed simultaneously. Furthermore, those skilled in the art, guided by the content of this invention, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor systems and / or microcontroller systems.

[0058] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0059] This invention provides a method and apparatus for determining scheduling schemes in large-scale discrete manufacturing, which will be described below.

[0060] Figure 1A schematic flowchart of an embodiment of the scheduling scheme determination method for large-scale discrete manufacturing provided by the present invention is shown below. Figure 1 As shown, the scheduling scheme determination method for large-scale discrete manufacturing includes:

[0061] S101. Based on the scheduling constraint, perform preliminary scheduling of the set of projects to be scheduled to obtain multiple baseline feasible solutions for the scheduling scheme.

[0062] Step S101 can be performed based on commonly used scheduling tools, namely: the scheduling tool receives scheduling constraints and a set of items to be scheduled in order to obtain multiple baseline feasible solutions.

[0063] Scheduling tools include, but are not limited to, Microsoft Project, Primavera P6, Jira, ClickUp, etc.

[0064] It should be noted that: scheduling mandatory constraints refer to constraints that must be satisfied when scheduling any set of items, that is: universal constraints.

[0065] S102. Determine the non-mandatory scheduling constraints and the objective function for scheme optimization based on dynamic scheduling requirements.

[0066] Dynamic scheduling requirements refer to dynamically adjustable requirements set for different sets of projects, such as the shortest project delivery time or the highest utilization rate of production resources.

[0067] It should be noted that non-mandatory scheduling constraints refer to constraints corresponding to a set of projects; that is, they only apply to one or a few sets of projects and are not required to be satisfied by all sets of projects. For example, when the dynamic scheduling requirement is the shortest delivery time, non-mandatory scheduling constraints to shorten the delivery time need to be set adaptively based on this requirement.

[0068] Furthermore, the objective function for scheme optimization refers to a function whose objective is to meet the dynamic scheduling requirements. For example, when the dynamic scheduling requirement is the shortest delivery time, the objective function for scheme optimization is the project delivery time; when the dynamic scheduling requirement is the highest resource utilization rate, the objective function for scheme optimization is the utilization rate of production resources.

[0069] S103. Optimize multiple baseline feasible solutions based on scheduling non-mandatory constraints to obtain multiple optimized feasible solutions.

[0070] One approach to optimizing multiple baseline feasible solutions based on non-mandatory scheduling constraints is as follows: screen multiple baseline feasible solutions to determine the optimized feasible solutions that satisfy the non-mandatory scheduling constraints; when no optimized feasible solutions satisfy the non-mandatory scheduling constraints exist, re-schedule each baseline feasible solution based on the non-mandatory scheduling constraints to obtain multiple optimized feasible solutions.

[0071] S104. Input multiple optimized feasible solutions into the scheme optimization objective function to obtain multiple function values, and take the optimized feasible solution corresponding to the function value that satisfies the requirements of the scheme optimization objective function as the target scheduling scheme.

[0072] It should be understood that the scheduling scheme determination method for large-scale discrete manufacturing in the embodiments of the present invention can be implemented in any device based on the determination of a scheduling scheme for large-scale discrete manufacturing, such as a scheduling scheme generation device. Specifically, the scheduling scheme determination method for large-scale discrete manufacturing is stored in the aforementioned device as a pre-programmed program. When the device is started, the program is invoked, and the scheduling scheme determination method for large-scale discrete manufacturing is implemented.

[0073] Compared with existing technologies, the scheduling scheme determination method for large-scale discrete manufacturing provided by this invention first performs an initial scheduling based on scheduling mandatory constraints on the set of projects to be scheduled, obtaining multiple baseline feasible solutions for the scheduling scheme. This achieves the same solution for all project sets. Then, based on scheduling non-mandatory constraints determined by dynamic scheduling requirements, the multiple baseline feasible solutions are optimized to obtain multiple optimized feasible solutions. This achieves optimization of the baseline feasible solutions according to dynamic scheduling requirements, improving the matching degree between the optimized feasible solutions and the actual scheduling requirements, thereby increasing the probability of obtaining a scheduling scheme, i.e., improving the robustness of the scheduling scheme determination method. Furthermore, after obtaining multiple optimized feasible solutions, this invention also determines the target scheduling scheme among the multiple optimized feasible solutions through the scheme optimization objective function determined based on the dynamic scheduling requirements, ensuring the matching degree between the target scheduling scheme and the dynamic scheduling requirements, i.e., improving the accuracy of the target scheduling scheme.

[0074] Furthermore, this embodiment of the invention divides the complex solution process in the context of large-scale discrete manufacturing into solving multiple baseline feasible solutions applicable to all project sets and target scheduling schemes applicable to the characteristic requirement of dynamic scheduling. This achieves the division of complex solution problems, thereby improving the efficiency of determining target scheduling schemes and obtaining different target scheduling schemes according to different adaptability requirements of dynamic scheduling, thus improving the flexibility and robustness of target scheduling schemes.

[0075] In a specific embodiment of the present invention, the scheduling constraints include process dependency constraints, material supply constraints, and bottleneck process priority constraints.

[0076] Among them, process dependency constraints refer to the sequential dependencies between multiple processes in each project, such as... Figure 2As shown, project A includes four processes: A1, A2, A3, and A4. Process A2 can only be performed after process A1 is completed, and process A4 can only be performed after processes A2 and A3 are completed. The order of dependencies between A1, A2, A3, and A4 is the process dependency constraint.

[0077] Material supply constraints refer to the materials required for each process to be executed; that is, the corresponding process can only be executed after the materials are in place.

[0078] Bottleneck process priority constraint means that the bottleneck process is executed first, that is, time and resources are allocated to the bottleneck process first.

[0079] Among them, the bottleneck process refers to the process that has the greatest impact on dynamic scheduling requirements.

[0080] As can be seen from the foregoing description, scheduling non-mandatory constraints are closely related to dynamic scheduling requirements. In a specific embodiment of the present invention, the dynamic scheduling requirement is a short project delivery period, so the scheduling non-mandatory constraints include mold / auxiliary tool switching time constraints, bottleneck resource priority constraints, and project task priority constraints.

[0081] The mold / auxiliary tool changeover time constraint refers to minimizing the changeover time of molds / auxiliary tools. For example, when changing between A and B type projects, additional installation and disassembly time needs to be calculated. When scheduling, priority should be given to assigning A and B type projects to two machines. If there are not enough machines, all A type projects should be completed first, followed by B type projects.

[0082] It should be noted that project categorization is not based on the project's inherent category, but rather on whether a change of mold / auxiliary tools is required. For example, if two projects have different inherent categories but are applicable to the same set of molds / auxiliary tools, these two projects are considered the same type of project. In other words, projects are categorized based on whether they are applicable to the same set of molds / auxiliary tools.

[0083] Bottleneck resource priority constraint refers to ensuring continuous production of bottleneck resources, that is, maximizing the utilization rate of bottleneck resources in order to shorten the project cycle.

[0084] Bottleneck resources refer to the production resources that have the greatest impact on project delivery time. These production resources include, but are not limited to, personnel, equipment, and tooling.

[0085] Project task priority constraints refer to allocating production resources to each project according to its task priority, so as to ensure that each project is completed in the order of its priority.

[0086] In some embodiments of the present invention, the project set includes multiple projects, and each project includes multiple processes. When the dynamic scheduling requirement is a short project delivery time, such as... Figure 3As shown, the objective function for determining the scheme optimization based on dynamic scheduling requirements in step S102 includes:

[0087] S301. Identify multiple process chains in the project and determine the process chain duration of each process chain. The process chain duration with the longest duration shall be taken as the critical chain duration.

[0088] Among them, the process chain refers to the sequential chain formed by connecting various processes in the process of project execution according to logic, technology or resource dependencies.

[0089] Specifically, such as Figure 2 As shown, Project A includes two process chains, namely A1-A2-A4 and A3-A4.

[0090] S302. The time difference between the start and end times of the project shall be used as the project cycle, and the time difference between the start time of the project and the start time of the first process in the project shall be used as the project delivery value.

[0091] S303. Determine the critical chain impact factor based on the critical chain duration and project cycle, and determine the project delivery impact factor based on the project cycle and project delivery value.

[0092] S304. Use the sum of the critical chain impact factor and the project delivery date impact factor as the objective function for scheme optimization.

[0093] In determining the objective function for optimizing the solution, this invention incorporates the critical chain duration as an influencing factor. Considering that the critical chain duration directly represents the time required to complete the project, this improves the accuracy of the objective function. Furthermore, when determining the project delivery date, this invention considers not only the project cycle but also the project delivery date value derived from the project start time and the start time of the first process within the project. That is, it takes into account the preparation and buffer time between the process start time and the project start time, further ensuring the accuracy of the objective function and thus improving the accuracy and reliability of the determined target scheduling scheme.

[0094] In a specific embodiment of the present invention, the objective function for scheme optimization is:

[0095]

[0096]

[0097] In the formula, Optimize the objective function for the solutions to the project set; For the first x The objective function for optimizing the scheme of each project; Key chain impact factor; Factors affecting project delivery time;m This represents the total number of items in the project collection. For the first x The critical chain duration of each project; For the first x Project cycle of each project; For the first x The project delivery value of each project; This is the critical chain length weighting coefficient; Weighting coefficient for project delivery options.

[0098] Because accurately determining the process chain duration is crucial for accurately determining the target scheduling scheme, existing technologies only consider the execution time of each process. However, in real-world scenarios, in addition to the actual execution time of each process, it also includes personnel movement time between processes, material preparation time, etc. To improve the accuracy of the process chain duration, in some embodiments of this invention, such as... Figure 4 As shown, determining the process chain duration of each process chain in step S301 includes:

[0099] S401, Obtain multiple processes in the process chain.

[0100] Among them, many processes can be directly determined based on the baseline feasible solution, which is the preliminary scheduling scheme. The preliminary scheduling scheme includes the execution processes of each project. By sorting out the processes, the process chain can be obtained, and then multiple processes in the process chain can be obtained.

[0101] S402. Determine the planned duration of each process and the time between adjacent processes.

[0102] The planned duration of a process can be the average working time during the historical execution of the process, or it can be the calculated working time based on mature standard working time and algorithms.

[0103] Inter-process time refers to the additional time required between two adjacent processes.

[0104] Specifically, the time between processes includes buffer time, waiting time, and transfer time.

[0105] S403. The sum of the planned duration of multiple processes and the duration between processes is taken as the process chain duration.

[0106] Specifically, process chain duration for:

[0107]

[0108] In the formula, The duration of the first process; For the first z The process time of each step For the first z The time interval between each process and its preceding process; o This represents the total number of processes.

[0109] Because research and mass production are mixed in large-scale discrete manufacturing, their technological maturity levels are not the same. This difference in technological maturity leads to different process planning times. However, existing technologies do not take into account the impact of different technological maturity levels when determining process planning times, resulting in inaccurate process planning times and consequently inaccurate target scheduling schemes.

[0110] To solve the above-mentioned technical problems, in some embodiments of the present invention, such as Figure 5 As shown, determining the planned process time for each process in step S402 includes:

[0111] S501. Obtain the initial planned duration of the process, as well as the process type, number of production runs, and frequency of overdue occurrences;

[0112] The initial planned duration can be the average working hours during the historical execution of the process.

[0113] Process type refers to different processes under the same operation. For example, if the operation is removal, the process type can be different types such as turning or milling.

[0114] The production count refers to the number of times this process has been performed in history.

[0115] The frequency of overdue occurrences refers to the frequency of overdue occurrences of this process in its historical execution.

[0116] S502. Determine the duration correction factor for the process based on the process type, number of production runs, and frequency of overdue occurrences.

[0117] It should be understood that the more production cycles a process undergoes, the lower the frequency of delays, and the higher the process maturity, the easier it is to execute according to the initial planned time. In other words, different production cycles and frequencies of delays affect the execution time of a process. Furthermore, different process types will also result in different process durations.

[0118] Therefore, by obtaining the process type, production frequency, and overdue frequency of each process, the embodiments of the present invention can achieve a comprehensive evaluation and correction of the initial planned duration.

[0119] S503. Adjust the planned duration of the process using the duration correction factor to obtain the planned duration of the process.

[0120] Specifically, the product of the duration correction factor and the planned duration of the process can be used as the planned duration of the process.

[0121] In determining the planned duration of a process, this invention considers influencing factors including process type and technological maturity to improve the accuracy of the planned duration, thereby improving the accuracy of the determined target scheduling scheme.

[0122] In practical applications, the length of the critical chain can characterize the overall project time, and the critical chain refers to the longest process chain. To further shorten project delivery time, in some embodiments of this invention, such as... Figure 6 As shown, determining multiple process chains in step S301 includes:

[0123] S601. Obtain multiple initial process chains and determine the critical process chain among the multiple initial process chains. The critical process chain is the initial process chain with the longest process chain duration.

[0124] S602. Determine whether the interval between processes in the critical process chain can be shortened;

[0125] One way to determine whether the interval can be shortened is: if there are deletable waiting times or other processes in the interval between processes, the interval can be shortened; otherwise, it cannot be shortened.

[0126] S603. If yes, shorten the interval between processes; if no, split the key process chain based on production resources to obtain multiple split chains.

[0127] S604. Multiple split chains and multiple initial process chains other than the critical process chain are treated as multiple process chains.

[0128] The embodiments of the present invention shorten the duration of the process chain by shortening the interval between processes and by splitting the key process chain, thereby shortening the project delivery time and further increasing the probability of meeting the dynamic scheduling requirements.

[0129] In a specific embodiment of the present invention, the chain splitting method is as follows: Figure 7 As shown, to ensure that the prerequisite tasks B1 and B2 of B4 can be completed in a timely manner, B2 is split and assigned to resources 2 and 2' for production. That is, the process of B2 is split into B2 and B2', and the process of B2-B4 is further split into B2-B4 and B2'-B4, thus shortening the time of the process chain.

[0130] In practical applications, there may be situations where resources are occupied by the previous project set when scheduling the current project set. To adapt to this application scenario, in some embodiments of the present invention, after step S103, the following is also included:

[0131] Obtain the occupancy status of production resources, and adjust multiple optimal feasible solutions based on the occupancy status.

[0132] The embodiments of the present invention obtain the occupancy status of production resources and adjust and optimize feasible solutions based on the occupancy status, which can ensure the matching degree between the optimized feasible solutions and the actual scenario and improve the effectiveness of the determined target scheduling scheme.

[0133] Specifically, such as Figure 7 As shown, it can be seen that resources 2, 2', and 3 are already occupied. Therefore, when scheduling, the occupancy status needs to be considered. For example, the third process of project A, namely A3, requires the participation of resource 3. Since resource 3 is occupied, A3 can only be placed after the occupied time.

[0134] Furthermore, by Figure 7 It can also be seen that the embodiments of the present invention schedule multiple projects in the project set as a whole, rather than bringing forward the delivery date of a single project. For example, although the delivery date of project A is earlier, resource 2 still completes B2 first, effectively shortening the delivery date of project B. This effectively utilizes production resources while taking into account the overall delivery date of multiple projects.

[0135] In practical applications, the optimal solution sometimes appears around the target scheduling scheme; that is, the target scheduling scheme is not the optimal solution, but rather a solution around it. To further improve the accuracy of the scheduling scheme, in some embodiments of the present invention, after step S104, the scheduling scheme determination method for large-scale discrete manufacturing further includes:

[0136] With the target scheduling scheme as the center, and the preset parameter range as the trial range, multiple trial solutions are determined;

[0137] Multiple trial solutions are input into the scheme optimization objective function, resulting in multiple trial values. The trial solution corresponding to the trial value that satisfies the requirements of the scheme optimization objective function is taken as the optimized scheduling scheme.

[0138] Among them, multiple trial solutions include target scheduling schemes, and the preset parameter ranges include the maximum parameter range and step size.

[0139] For example, when the target scheduling scheme is a heating temperature of 200℃, a maximum parameter range of 10℃, and a step size of 5℃, the trial solutions are 195℃, 200℃, 205℃, and 210℃.

[0140] It should be understood that the preset parameter range can be set or adjusted according to the actual application scenario, and no specific limitation is made here.

[0141] In this embodiment of the invention, after determining the target scheduling scheme, multiple trial solutions are determined with the target scheduling scheme as the center and a preset parameter range as the trial range. The optimal solution among the multiple trial solutions is then determined, which makes the final optimized scheduling scheme more in line with the requirements of the scheme optimization objective function, and further improves the accuracy of the optimized scheduling scheme.

[0142] To better implement the scheduling scheme determination method for large-scale discrete manufacturing in the embodiments of the present invention, the embodiments of the present invention also provide a scheduling scheme determination device for large-scale discrete manufacturing, based on the scheduling scheme determination method for large-scale discrete manufacturing. Figure 8 As shown, the scheduling scheme determination device 800 for large-scale discrete manufacturing includes:

[0143] The initial scheduling unit 801 is used to perform preliminary scheduling of the set of items to be scheduled based on scheduling mandatory constraints, and to obtain multiple baseline feasible solutions for the scheduling scheme.

[0144] The scheduling objective determination unit 802 is used to determine the non-mandatory scheduling constraints and the objective function for scheme optimization based on dynamic scheduling requirements;

[0145] The baseline feasible solution optimization unit 803 is used to optimize multiple baseline feasible solutions based on scheduling non-mandatory constraints to obtain multiple optimized feasible solutions;

[0146] The target scheduling scheme determination unit 804 is used to input multiple optimized feasible solutions into the scheme optimization objective function, obtain multiple function values, and take the optimized feasible solution corresponding to the function value that satisfies the requirements of the scheme optimization objective function as the target scheduling scheme.

[0147] The scheduling scheme determination device 800 for large-scale discrete manufacturing provided in the above embodiments can realize the technical solutions described in the above embodiments of the scheduling scheme determination method for large-scale discrete manufacturing. The specific implementation principles of each module or unit can be found in the corresponding content in the above embodiments of the scheduling scheme determination method for large-scale discrete manufacturing, and will not be repeated here.

[0148] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0149] The above provides a detailed description of a scheduling scheme determination method and apparatus for large-scale discrete manufacturing provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for determining scheduling schemes in large-scale discrete manufacturing, characterized in that, include: Based on the scheduling constraint, a preliminary scheduling is performed on the set of projects to be scheduled, and multiple baseline feasible solutions for the scheduling scheme are obtained. Determine the non-mandatory scheduling constraints and the objective function for scheme optimization based on dynamic scheduling requirements; Based on the aforementioned non-mandatory scheduling constraints, the multiple baseline feasible solutions are optimized to obtain multiple optimized feasible solutions; The multiple optimized feasible solutions are input into the scheme optimization objective function to obtain multiple function values, and the optimized feasible solution corresponding to the function value that satisfies the requirements of the scheme optimization objective function is taken as the target scheduling scheme. The mandatory scheduling constraints are constraints that must be satisfied when scheduling any set of projects, while the non-mandatory scheduling constraints are constraints that must be satisfied when scheduling at least one set of projects, corresponding to the requirements of dynamic scheduling. The mandatory scheduling constraints include process dependency constraints, material supply constraints, and bottleneck process priority constraints. When the dynamic scheduling requirement is a short project delivery time, the non-mandatory scheduling constraints include mold / auxiliary tool changeover time constraints, bottleneck resource priority constraints, and project task priority constraints. The project set includes multiple projects, and each project includes multiple processes; when the dynamic scheduling requirement is a short project delivery time, the objective function for optimizing the solution is determined based on the dynamic scheduling requirement, including: Identify multiple process chains in the project and determine the process chain duration of each process chain, and take the process chain duration with the longest duration as the critical chain duration; The time difference between the start and end times of the project is taken as the project cycle, and the time difference between the start time of the project and the start time of the first process in the project is taken as the project delivery value. The critical chain impact factor is determined based on the critical chain duration and the project cycle, and the project delivery time impact factor is determined based on the project cycle and the project delivery time value. The sum of the critical chain impact factor and the project delivery date impact factor is used as the objective function for optimizing the scheme; The objective function for optimizing the proposed scheme is: In the formula, Optimize the objective function for the solutions to the project set; For the first x The objective function for optimizing the scheme of each project; Key chain impact factor; Factors affecting project delivery time; m This represents the total number of items in the project collection. For the first x The critical chain duration of each project; For the first x Project cycle for each project; For the first x The project delivery value of each project; This is the critical chain length weighting coefficient; Weighting coefficient for project delivery options.

2. The scheduling scheme determination method for large-scale discrete manufacturing according to claim 1, characterized in that, Determining the process chain duration for each of the aforementioned process chains includes: Obtain multiple processes in the process chain; Determine the planned duration of each of the aforementioned processes and the duration between adjacent processes; The process chain duration is the sum of the planned duration of the multiple processes and the duration between the processes.

3. The scheduling scheme determination method for large-scale discrete manufacturing according to claim 2, characterized in that, Determine the planned duration of each of the aforementioned processes, including: Obtain the initial planned duration of the process, as well as the process type, number of production runs, and frequency of overdue occurrences for the process; The duration correction factor for the process is determined based on the process type, the number of production runs, and the frequency of overdue occurrences. The planned duration of the process is adjusted using the duration adjustment factor to obtain the planned duration of the process.

4. The scheduling scheme determination method for large-scale discrete manufacturing according to claim 1, characterized in that, Determining the plurality of process chains includes: Obtain multiple initial process chains and determine the key process chain among the multiple initial process chains, wherein the key process chain is the initial process chain with the longest process chain duration; Determine whether the intervals between processes in the critical process chain can be shortened; If so, then shorten the interval between processes; if not, then split the key process chain based on production resources to obtain multiple split chains. The plurality of split chains and the plurality of initial process chains other than the critical process chain are referred to as the plurality of process chains.

5. The scheduling scheme determination method for large-scale discrete manufacturing according to claim 1, characterized in that, After optimizing the multiple baseline feasible solutions based on the non-mandatory scheduling constraints to obtain multiple optimized feasible solutions, the method further includes: Obtain the occupancy status of production resources, and adjust the multiple optimized feasible solutions based on the occupancy status.

6. The scheduling scheme determination method for large-scale discrete manufacturing according to claim 1, characterized in that, The method further includes: With the target scheduling scheme as the center, and the preset parameter range as the trial range, multiple trial solutions are determined; The multiple trial solutions are input into the scheme optimization objective function to obtain multiple trial values. The trial solution corresponding to the trial value that satisfies the requirements of the scheme optimization objective function is taken as the optimized scheduling scheme.

7. A scheduling scheme determination device for large-scale discrete manufacturing, characterized in that, The apparatus applicable to the method for determining production schemes for large-scale discrete manufacturing as described in any one of claims 1-6, the apparatus comprising: The initial scheduling unit is used to perform preliminary scheduling on the set of items to be scheduled based on scheduling constraints, and to obtain multiple baseline feasible solutions for the scheduling scheme. The scheduling objective determination unit is used to determine the non-mandatory scheduling constraints and the objective function for scheme optimization based on dynamic scheduling requirements. The baseline feasible solution optimization unit is used to optimize the multiple baseline feasible solutions based on the scheduling non-mandatory constraints to obtain multiple optimized feasible solutions; The target scheduling scheme determination unit is used to input the multiple optimized feasible solutions into the scheme optimization objective function, obtain multiple function values ​​accordingly, and take the optimized feasible solution corresponding to the function value that satisfies the requirements of the scheme optimization objective function as the target scheduling scheme.

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