Flexible job shop scheduling optimization method and system

Abstract

The invention discloses a flexible job shop scheduling optimization method and system. The method comprises the steps of forming an initial scheduling scheme of a flexible job shop operation process; judging whether a periodic scheduling opportunity is reached or not; forming a first optimal rescheduling scheme to perform periodic rescheduling on the operation process of the flexible job shop in response to the arrival of the periodic scheduling opportunity; judging whether a disturbance event occurs or not in response to the situation that the periodic scheduling opportunity is not reached; in response to no disturbance event, returning to the step of forming the initial scheduling scheme; and in response to the occurrence of the disturbance event, forming a first optimal rescheduling scheme, a second optimal rescheduling scheme or a complete rescheduling strategy based on the type of the disturbance event and the severity of disturbance to perform production disturbance adaptive adjustment on the flexible job shop operation process. By using the scheme of the invention, a dynamic closed-loop control system can be constructed based on a periodic scheduling and disturbance event driven dual mechanism, and the dynamic closed-loop control system has anti-interference toughness and production stability guarantee.

Description

Technical Field

[0001] The present application generally relates to the field of personalized customization production technology. More specifically, the present application relates to a flexible job shop scheduling optimization method and system. Background Art

[0002] As the manufacturing industry shifts toward personalized customization, traditional mass production models are no longer able to meet the market's demand for flexibility and responsiveness. Personalized production requires manufacturing systems to dynamically adapt, enabling rapid adjustments to production processes based on customer needs, enabling on-demand manufacturing and reducing resource waste. In this context, digital manufacturing and flexible production line technologies are key enablers. However, complex and volatile resource organization and frequent abnormal events (such as equipment failures and order changes) pose challenges for manufacturing systems, including insufficient real-time responsiveness and inefficient dynamic scheduling.

[0003] In recent years, the cloud-edge collaborative intelligent manufacturing model has provided a new technical path to solving the above problems. Cloud manufacturing achieves efficient resource allocation through centralized management and sharing of manufacturing resources; while edge computing technology significantly reduces data transmission latency by deploying computing power near the data source, supporting real-time monitoring and localized intelligent decision-making. The collaborative application of the two forms a distributed intelligent architecture, which can theoretically improve the elasticity and real-time performance of manufacturing systems. In addition, the introduction of microservices architecture further optimizes system design. By splitting complex businesses into independent service modules (such as order management, equipment monitoring, etc.), it reduces system coupling and improves functional scalability and fault tolerance. For example, independent microservices can be adjusted individually according to production disturbance events, avoiding global system reconstruction.

[0004] However, the existing technology still has significant bottlenecks in practical applications: first, the high coupling between system modules causes the rescheduling mechanism unit and the abnormal event processing logic to be deeply bound to the specific manufacturing environment, which makes it difficult to adapt to the flexible production needs of multiple varieties and small batches; second, the workshop resources are finely granular and the status changes frequently. In addition, the types of abnormal events are complex (such as material shortages, process parameter deviations, etc.). The existing scheduling algorithm unit lacks a classification evaluation and priority response mechanism for disturbance events, resulting in low rescheduling efficiency; third, cloud-edge data collaboration has not yet formed a standardized interface. The heterogeneity of equipment and differences in data protocols have limited the system's interoperability. When a large amount of real-time data is centrally processed in the cloud, it is easy to cause network bandwidth bottlenecks, further weakening the real-time nature of dynamic scheduling.

[0005] In view of this, there is an urgent need to provide a flexible job shop scheduling optimization solution to break through the technical barriers of existing technologies in scalability, real-time performance and exception handling reliability, and provide an efficient dynamic scheduling solution for personalized customized production scenarios. Summary of the Invention

[0006] In order to at least solve one or more of the technical problems mentioned above, the present application proposes a flexible job shop scheduling optimization solution in multiple aspects.

[0007] In a first aspect, the present application provides a flexible job shop scheduling optimization method, including: forming an initial scheduling plan for the flexible job shop operation process based on current production tasks, production goals, process constraints, and the availability of production resources; judging whether the periodic scheduling opportunity has been reached; in response to reaching the periodic scheduling opportunity, forming a first optimal rescheduling plan to periodically rescheduling the flexible job shop operation process; in response to not reaching the periodic scheduling opportunity, judging whether a disturbance event has occurred; in response to no disturbance event occurring, returning to the step of forming the initial scheduling plan for the flexible job shop operation; in response to the occurrence of a disturbance event, forming a first optimal rescheduling plan, a second optimal rescheduling plan, or a complete rescheduling strategy based on the type of disturbance event and the severity of the disturbance to perform production disturbance adaptive adjustment on the flexible job shop operation process.

[0008] In some embodiments, in the process of forming the first optimal rescheduling scheme to periodically rescheduling the operation process of the flexible job workshop, the following steps are performed: calculating the robustness, stability and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively; obtaining the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively based on the robustness, stability and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively; taking the strategy with the lower corresponding comprehensive evaluation value as the first optimal rescheduling scheme; wherein, when the strategy with the lower comprehensive evaluation value is the right-shift rescheduling strategy, the start processing time of the disturbance-affected process is changed to achieve periodic rescheduling of the operation process of the flexible job workshop; when the strategy with the lower comprehensive evaluation value is the partial rescheduling strategy, the disturbance-affected process is rescheduled to achieve periodic rescheduling of the operation process of the flexible job workshop.

[0009] In some embodiments, in the process of calculating the robustness, stability, and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy, the following steps are performed: the robustness corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy is obtained by a robustness calculation formula, wherein the robustness calculation formula is: f1 is robustness, C′ max is the maximum completion time corresponding to the right shift rescheduling strategy or partial rescheduling strategy, C max is the maximum completion time corresponding to the initial scheduling scheme; the stability calculation formula is used to obtain the stability of the right-shift rescheduling strategy and the partial rescheduling strategy, where the stability calculation formula is: f2 is stability, Q ik For process Oik Variation of the processing equipment, R ik The production unit assigned to process O when the initial scheduling plan is adopted, R′ ik The production unit assigned to process O when the right-shift rescheduling strategy or partial rescheduling strategy is adopted, TC ik The production unit assigned to process O when the right-shift rescheduling strategy or partial rescheduling strategy is adopted ik The production unit assigned to process O when the right-shift rescheduling strategy or partial rescheduling strategy is adopted, TC ik Indicates the variation of the completion time of process O, ET ik The variation of the completion time of process O, ET ika The end processing time of process O on production unit R when the initial scheduling plan is adopted ik On production unit R a The end processing time on production unit R, ET ika′ The end processing time of process O on production unit R when the right-shift rescheduling strategy or partial rescheduling strategy is adopted ik On production unit R a′ The end processing time on production unit R, N′ is the number of workpieces participating in the right-shift rescheduling strategy or partial rescheduling strategy, n i ′ is the number of processes of workpiece J i The number of processes of job participating in the right-shift rescheduling strategy or partial rescheduling strategy, O i For workpiece J i The total number of all processes of workpiece J The penalty weight for production unit transfer The penalty weight for the offset of process completion time; The economic efficiencies corresponding to the right-shift rescheduling strategy and partial rescheduling strategy are obtained through the economic calculation formula, where the economic calculation formula is: L is the maximum value of a′, N′ is the number of workpieces participating in the right-shift rescheduling strategy or partial rescheduling strategy, n i ′ is the number of processes of workpiece J i The number of processes of job participating in the right-shift rescheduling strategy or partial rescheduling strategy ET ika′ The end processing time of process O on production unit R when the right-shift rescheduling strategy or partial rescheduling strategy is adopted ik On production unit R a′ The end processing time on production unit R, ST ika′ The end processing time of process O on production unit R when the right-shift rescheduling strategy or partial rescheduling strategy is adopted ik On production unit R a′ The start processing time on production unit R, C′ max The makespan corresponding to the right-shift rescheduling strategy or partial rescheduling strategy

[0010] In some embodiments, in the process of obtaining the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively based on the robustness, stability and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy, the following steps are performed: Normalize the robustness, stability and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively using the normalization formula to obtain the robustness standard value, the stability standard value and the economy standard value. The normalization formula is j = 1, 2, 3, is the standard value of the j-th index, f j is the j-th index, f j,min is the minimum value among all the indices, f j,max is the maximum value among all the indices. The indices include robustness, stability and economy; Calculate the robustness standard value, the stability standard value and the economy standard value using the comprehensive evaluation calculation formula to obtain the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively. The comprehensive evaluation calculation formula is: is the robustness standard value, ω1 is the weight factor of the robustness standard value, is the stability standard value, ω2 is the weight factor of the stability standard value, is the economy standard value, ω3 is the weight factor of the economy standard value.

[0011] In some embodiments, in the process of adaptively adjusting the production disturbance of the flexible job shop operation process by forming the first optimal rescheduling plan, the second optimal rescheduling plan or the complete rescheduling strategy based on the type of disturbance event and the severity of the disturbance, the following steps are performed: Determine whether the type of disturbance event is an explicit disturbance or an implicit disturbance; In response to the type of disturbance event being an explicit disturbance, form the second optimal rescheduling plan to adaptively adjust the production disturbance of the flexible job shop operation process; In response to the type of disturbance event being an implicit disturbance, determine whether the impact degree of the comprehensive working hour deviation is greater than the impact degree threshold of the comprehensive working hour deviation; In response to the impact degree of the comprehensive working hour deviation being greater than the impact degree threshold of the comprehensive working hour deviation, use the complete rescheduling strategy to adaptively adjust the production disturbance of the flexible job shop operation process; In response to the impact degree of the comprehensive working hour deviation not being greater than the impact degree threshold of the comprehensive working hour deviation, form the first optimal rescheduling plan to adaptively adjust the production disturbance of the flexible job shop operation process.

[0012] In some embodiments, in the process of forming the second optimal rescheduling plan to adaptively adjust the production disturbance of the flexible job shop operation process, the following steps are executed: Calculate the robustness, stability, and economy corresponding to the partial rescheduling strategy and the complete rescheduling strategy respectively; Obtain the comprehensive evaluation values corresponding to the partial rescheduling strategy and the complete rescheduling strategy respectively based on the robustness, stability, and economy corresponding to the partial rescheduling strategy and the complete rescheduling strategy respectively; Use the strategy with the lower corresponding comprehensive evaluation value as the second optimal rescheduling plan; wherein, when the strategy with the lower comprehensive evaluation value is the partial rescheduling strategy, the production disturbance of the flexible job shop operation process is adaptively adjusted by rescheduling the disturbed impact operations; when the strategy with the lower comprehensive evaluation value is the complete rescheduling strategy, the production disturbance of the flexible job shop operation process is adaptively adjusted by rescheduling the unfinished operations.

[0013] In some embodiments, the comprehensive impact degree of working hour deviation is obtained through the comprehensive impact degree calculation formula of working hour deviation, wherein, the comprehensive impact degree calculation formula of working hour deviation is: I is the comprehensive impact degree of working hour deviation, B a (O) t represents the set of all operations affected by the disturbance event at time t, I ika is the comprehensive impact degree of working hour deviation corresponding to operation O i,k PE ika operation O i,k at the actual completion time on production unit R a E ika is the expected completion time of operation O i,k on production unit R a T ika is the standard operation time required when production unit R a completes the processing task of operation O i,k λ ik ∈(0,1] is the importance coefficient of operation O i,k The importance coefficient of operation O.

[0014] In some embodiments, in the process of judging whether a disturbance event occurs, the following steps are executed: Obtain the expected production state of the flexible job shop according to the initial scheduling plan; Obtain the actual production state corresponding to the flexible job shop; Judge whether there is a difference between the actual production state and the expected production state; In response to the existence of a difference between the actual production state and the expected production state, judge that a disturbance event occurs; In response to the non-existence of a difference between the actual production state and the expected production state, judge that no disturbance event occurs.

[0015] In a second aspect, the present application provides a set of flexible job shop scheduling optimization systems, which perform flexible job shop scheduling optimization by using the flexible job shop scheduling optimization method described in any embodiment of the first aspect. The system includes: a cloud server center for realizing resource management, adaptive dynamic scheduling, real-time monitoring and feedback, data analysis, management of platform resources, and establishing dual-channel redundant communication with the edge server center in a flexible job shop; an edge server center for realizing device access, data preprocessing, edge computing, local fault-tolerant scheduling, and coordinating resource status with the cloud server center in a flexible job shop; a flexible job shop for synchronizing data with the cloud server center through the edge server center and executing dynamic scheduling tasks; wherein, the cloud service platform includes a flexible job shop adaptive dynamic scheduling module, and the flexible job shop adaptive dynamic scheduling module is used to perform periodic rescheduling on the operation process of the flexible job shop or perform adaptive adjustment of production disturbances on the operation process of the flexible job shop.

[0016] In some embodiments, the workshop production system adaptive dynamic scheduling module includes an initial scheduling plan formation unit, a first judgment unit, a periodic rescheduling unit, a second judgment unit, an iterative unit, and a production disturbance adaptive adjustment unit; the initial scheduling plan formation unit is used to form an initial scheduling plan for the operation process of the flexible job shop based on the current production task, production target, process constraints, and available production resources; the first judgment unit is used to judge whether the periodic scheduling opportunity has arrived; in response to the arrival of the periodic scheduling opportunity, the periodic rescheduling unit is used to form a first optimal rescheduling plan to perform periodic rescheduling on the operation process of the flexible job shop; in response to the non-arrival of the periodic scheduling opportunity, the second judgment unit is used to judge whether a disturbance event has occurred; in response to the non-occurrence of a disturbance event, the iterative unit is used to return to the step of forming the initial scheduling plan for the operation of the flexible job shop; in response to the occurrence of a disturbance event, the adaptive dynamic scheduling unit is used to form a first optimal rescheduling plan, a second optimal rescheduling plan, or a complete rescheduling strategy based on the type of the disturbance event and the severity of the disturbance to perform adaptive adjustment of production disturbances on the operation process of the flexible job shop.

[0017] Through the flexible job shop scheduling optimization solution provided above, in the embodiments of the present application, by performing periodic rescheduling on the operation process of the flexible job shop when the cycle scheduling opportunity is reached and performing production disturbance adaptive adjustment on the operation process of the flexible job shop when a disturbance event occurs, a dynamic closed-loop control system can be constructed based on the dual mechanisms of periodic scheduling and disturbance event drive. Periodic rescheduling can prevent the cumulative deviation of slow drift, smooth short-term fluctuations, and avoid the line oscillation caused by frequent adjustments. The disturbance trigger mechanism can quickly respond to sudden abnormal events and maintain the stability of the production rhythm, meeting the strict requirements of continuous production in high-precision manufacturing scenarios. This enables the system to have anti-interference resilience and ensure production stability. At the same time, based on the hierarchical response strategy for disturbance type and severity, it not only avoids the waste of computing resources caused by over-scheduling but also can initiate full rescheduling when necessary, achieving a balance between computing efficiency and scheduling quality.

[0018] Further, in some embodiments, during the process of forming the first optimal rescheduling plan for periodic rescheduling, by evaluating the robustness, stability, and economy of right-shift rescheduling and partial rescheduling strategies, the trade-off of multi-dimensional optimization is achieved, avoiding the bias of a single index, thereby selecting the optimal adjustment plan and avoiding the limitations of a single strategy.

[0019] Furthermore, in some embodiments, during the process of performing production disturbance adaptive adjustment, by distinguishing between explicit disturbances and implicit disturbances, different scheduling strategies can be matched according to different disturbance characteristics, avoiding resource waste or insufficient effects caused by adopting a single response mode. By introducing the threshold of the comprehensive deviation influence degree of working hours as the decision boundary for handling implicit disturbances, the quantitative evaluation of the influence of implicit disturbances is realized, preventing over-scheduling triggered by minor deviations and avoiding the out-of-control of cumulative deviations. By forming a two-level decision-making structure for disturbance type judgment and influence degree evaluation to form a redundant verification mechanism, it can not only prevent single judgment errors but also adapt to complex disturbance superposition scenarios.

[0020] Still further, in some embodiments, during the process of determining whether a disturbance event occurs, the expected production state is clarified through the initial scheduling plan, providing an objective basis for subsequent comparison and ensuring that the judgment process is well-founded. By continuously obtaining the actual production state data and dynamically tracking the operation of the workshop, a transparent monitoring of the production process is formed. By comparing the differences between the expected and actual states, the abnormal points can be quickly located, making the occurrence of disturbance events rely on objective data rather than empirical judgment, reducing human bias, and improving the scientificity and clarity of decision-making. Description of the Drawings

[0021] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present application will become readily understandable. In the drawings, several embodiments of the present application are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0022] Figure 1 An exemplary flowchart of the flexible job shop scheduling optimization method according to an embodiment of the present application is shown;

[0023] Figure 2 An exemplary flowchart of forming the first optimal rescheduling plan according to an embodiment of the present application is shown;

[0024] Figure 3 An exemplary flowchart of determining whether a disturbance event occurs according to an embodiment of the present application is shown;

[0025] Figure 4 An exemplary flowchart of adaptively adjusting production disturbances to the operation process of the flexible job shop according to an embodiment of the present application is shown;

[0026] Figure 5 An exemplary flowchart of forming the second optimal rescheduling plan according to an embodiment of the present application is shown;

[0027] Figure 6 An exemplary structural block diagram of the flexible job shop scheduling optimization system according to an embodiment of the present application is shown;

[0028] Figure 7 A specific composition architecture diagram of the cloud server center, edge server center, and flexible job shop according to an embodiment of the present application is shown;

[0029] Figure 8 A specific composition architecture diagram of the cloud platform according to an embodiment of the present application is shown;

[0030] Figure 9 An exemplary structural block diagram of the workshop production system adaptive dynamic scheduling module according to an embodiment of the present application is shown. Detailed implementation manners

[0031] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0032] It should be understood that the terms "comprising" and "including" as used in the specification and claims of this application indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0033] It should also be understood that the terms used in the specification of this application are merely for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification and claims of this application, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms. It should be further understood that the term "and / or" as used in the specification and claims of this application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0034] Figure 1 An exemplary flowchart of the flexible job shop scheduling optimization method 100 according to an embodiment of this application is shown.

[0035] As Figure 1 shown, in step S110, an initial scheduling plan for the operation process of the flexible job shop is formed based on the current production tasks, production goals, process constraints, and the availability of production resources.

[0036] In an embodiment of this application, production scheduling and the actual production process are organically integrated through shop floor production monitoring to ensure the overall consistency between the production site and the scheduling plan. The initial optimized scheduling plan includes expected information such as the processing order and time of processes, and the matching results of production units and processing tasks. Based on the real-time monitoring system of the operation state of the flexible job shop, the above-mentioned expected information establishes a direct mapping relationship with the production process at the manufacturing site, realizing production guidance and status monitoring of the work-in-process and manufacturing resources at the flexible job shop site.

[0037] In an embodiment of this application, in the initial scheduling plan of the flexible job shop, the work content and processing sequence of each production unit are optimized and generated according to the scheduling objectives. Each process included in each workpiece is also restricted by the specified process route.

[0038] After step S110 is executed, in step S120, it is judged whether the cycle scheduling opportunity has arrived.

[0039] In an embodiment of the present application, during the process of determining whether the periodic scheduling opportunity has arrived, first, obtain the last scheduling time, the preset period, and the current time. Then, determine whether the time interval between the current time and the last scheduling time reaches the preset period. In response to the time interval between the current time and the last scheduling time reaching the preset period, it is determined that the periodic scheduling opportunity has arrived. In response to the time interval between the current time and the last scheduling time not reaching the preset period, it is determined that the periodic scheduling opportunity has not arrived.

[0040] In an embodiment of the present application, the preset period is set according to actual needs and historical experience, and the present application does not limit this here.

[0041] In response to reaching the periodic scheduling opportunity, in step S130, form the first optimal rescheduling plan to perform periodic rescheduling on the operation process of the flexible job shop.

[0042] In an embodiment of the present application, the specific process involved in forming the first optimal rescheduling plan can refer to Figure 2 .

[0043] Figure 2 The exemplary flowchart of forming the first optimal rescheduling plan in the embodiment of the present application is shown.

[0044] As Figure 2 shown, in step S210, calculate the robustness, stability, and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively. In step S220, obtain the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively based on the robustness, stability, and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy. In step S230, use the strategy with the lower corresponding comprehensive evaluation value as the first optimal rescheduling plan.

[0045] Since when calculating the comprehensive evaluation values of each rescheduling plan, robustness and stability are important indicators to measure the quality of a dynamic scheduling plan. In a dynamic scheduling plan, the characteristic that the production performance index (such as the makespan) does not deteriorate is called robustness. The characteristic of not deviating from the initial scheduling plan is called stability. After a perturbation occurs and rescheduling is performed, if the gap between the rescheduling plan and the initial scheduling plan is large in terms of operation processing sequence, production unit allocation, etc., it may significantly increase the production cost, including additional material handling expenses, etc., and may cause delays in the project or delivery time. Therefore, when judging which rescheduling plan to adopt, not only the robustness of the scheduling plan performance needs to be considered, but also the change range between the new and old scheduling plans needs to be considered. In addition, from the economic perspective, the utilization rate of production units in the rescheduling plan needs to be considered. Therefore, the effectiveness of the rescheduling plan is evaluated with three indicators: robustness, stability, and economy.

[0046] In an embodiment of the present application, in the process of calculating the robustness corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively, the robustness corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy is obtained through the robustness calculation formula. By an important index characterizing the efficiency of the robust rescheduling scheme, the relative deviation between the actual result of the rescheduling and the expected result of the initial scheduling scheme is used for measurement.

[0047] Specifically, the robustness calculation formula is: f1 is the robustness, C max is the makespan corresponding to the right-shift rescheduling strategy or the partial rescheduling strategy, and C max is the makespan corresponding to the initial scheduling scheme.

[0048] In an embodiment of the present application, in the process of calculating the stability corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively, the stability corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy is obtained through the stability calculation formula. The stability of the rescheduling scheme is measured by the degree of difference between the rescheduling scheme and the initial scheduling scheme, including the difference in processing equipment and the difference in makespan. At the rescheduling moment, some processes may have been processed, and the stability of these processes may not need to be considered.

[0049] Specifically, the stability calculation formula is: f2 is the stability, Q ik is the change amount of the processing equipment for operation O ik R is the production unit to which operation O ik is assigned when the initial scheduling scheme is adopted, R′ ik is the production unit to which operation O ik is assigned when the right-shift rescheduling strategy or the partial rescheduling strategy is adopted, TC ik ik represents the change amount of the makespan of operation O ik ET ika is the end processing time of operation O ik on production unit R a when the initial scheduling scheme is adopted, ET ika′ is the end processing time of operation O ik on production unit R a′ when the right-shift rescheduling strategy or the partial rescheduling strategy is adopted, N′ is the number of workpieces participating in the right-shift rescheduling strategy or the partial rescheduling strategy, n i ′ is the number of operations of workpiece J i participating in the right-shift rescheduling strategy or the partial rescheduling strategy, O i i is the number of all operations of workpiece J i ​is the penalty weight for production unit transfer, is the penalty weight for the deviation of the operation completion time.

[0050] In the embodiments of the present application, in the process of calculating the economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively, the economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy is obtained through the economy calculation formula. The utilization rate of the production unit is used to evaluate the economy of the rescheduling plan. The utilization rate of the production unit represents the percentage of the working time of the production unit in the total processing time. The higher the utilization rate, the less the machine idle time and the personnel idle time, the higher the resource utilization rate of the enterprise, and the more reasonable the rescheduling plan.

[0051] Specifically, the economy calculation formula is: L is the maximum value of a′, N′ is the number of workpieces participating in the right-shift rescheduling strategy or the partial rescheduling strategy, and n i ′ is the number of operations of workpiece J i participating in the right-shift rescheduling strategy or the partial rescheduling strategy, ET ika′ is the end processing time of operation O when adopting the right-shift rescheduling strategy or the partial rescheduling strategy on production unit R ik in production unit R a′ ST is the start processing time of operation O when adopting the right-shift rescheduling strategy or the partial rescheduling strategy on production unit R ika′ is the start processing time of operation O when adopting the right-shift rescheduling strategy or the partial rescheduling strategy on production unit R ik in production unit R a′ C′ max is the makespan corresponding to the right-shift rescheduling strategy or the partial rescheduling strategy.

[0052] In the embodiments of the present application, in the process of obtaining the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively based on the robustness, stability and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively, first, the normalization formula is used to normalize the robustness, stability and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively to obtain the robustness standard value, the stability standard value and the economy standard value. Then, the comprehensive evaluation calculation formula is used to calculate the robustness standard value, the stability standard value and the economy standard value to obtain the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively.

[0053] By normalizing the robustness, stability and economy, the dimensional difference between the three indicators of robustness, stability and economy can be eliminated.

[0054] Specifically, the normalization formula is j = 1, 2, 3, is the standard value of the j-th indicator, fj is the j-th index, f j,min is the minimum value among all indices, f j,max is the maximum value among all indices, and the indices include robustness, stability, and economy.

[0055] The comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively represent the excellence degree of the rescheduling plan. The smaller the comprehensive evaluation value, the more excellent the rescheduling plan.

[0056] Specifically, the comprehensive evaluation calculation formula is: is the robustness standard value, ω1 is the weight factor of the robustness standard value, is the stability standard value, ω2 is the weight factor of the stability standard value, is the economy standard value, ω3 is the weight factor of the economy standard value.

[0057] In the embodiments of the present application, when the strategy with a lower comprehensive evaluation value is the right-shift rescheduling strategy, the start processing time of the processes affected by the perturbation is changed to achieve periodic rescheduling of the operation process of the flexible job shop.

[0058] In the embodiments of the present application, when the strategy with a lower comprehensive evaluation value is the partial rescheduling strategy, the processes affected by the perturbation are rescheduled to achieve periodic rescheduling of the operation process of the flexible job shop.

[0059] In response to not reaching the periodic scheduling opportunity, in step S140, it is judged whether a perturbation event occurs.

[0060] In the embodiments of the present application, the specific process involved in judging whether a perturbation event occurs can be referred to Figure 3 .

[0061] Figure 3 shows an exemplary flowchart for judging whether a perturbation event occurs in the embodiments of the present application.

[0062] As Figure 3 shown, in step S310, the expected production status of the flexible job shop is obtained according to the initial scheduling plan. In step S320, the actual production status corresponding to the flexible job shop is obtained. In step S330, it is judged whether there is a difference between the actual production status and the expected production status. In response to there being a difference between the actual production status and the expected production status, in step S340, it is judged that a perturbation event occurs. In response to there being no difference between the actual production status and the expected production status, in step S350, it is judged that no perturbation event occurs.

[0063] In an embodiment of the present application, in the manufacturing of an Internet of Things-driven flexible job shop perception environment, through corresponding monitoring technologies, managers can obtain key data during the operation of the flexible job shop in real time and timely grasp the actual production status.

[0064] By determining whether there is a difference between the actual production status and the expected production status to determine whether a disturbance event occurs, the abnormal point can be quickly located, making whether the disturbance event occurs depend on objective data rather than empirical judgment, reducing human bias, and improving the scientific nature of decision-making.

[0065] In response to the non-occurrence of a disturbance event, return to the step of forming the initial scheduling plan for the operation of the flexible job shop, that is, return to step S110.

[0066] In an embodiment of the present application, when a disturbance event does not occur, that is, when rescheduling is not required, return to step S110 to start a new round of judgment again.

[0067] In response to the occurrence of a disturbance event, in step S150, based on the type of the disturbance event and the severity of the disturbance, form the first optimal rescheduling plan, the second optimal rescheduling plan, or a complete rescheduling strategy to adaptively adjust the production disturbance of the operation process of the flexible job shop.

[0068] In an embodiment of the present application, the specific steps involved in step S150 can be referred to Figure 4 .

[0069] Figure 4 Shows an exemplary flowchart of adaptively adjusting the production disturbance of the operation process of the flexible job shop in an embodiment of the present application.

[0070] As Figure 4 shown, in step S410, determine whether the type of the disturbance event is an obvious disturbance or a hidden disturbance. In response to the type of the disturbance event being an obvious disturbance, in step S420, form the second optimal rescheduling plan to adaptively adjust the production disturbance of the operation process of the flexible job shop. In response to the type of the disturbance event being a hidden disturbance, in step S430, determine whether the impact degree of the comprehensive deviation of working hours is greater than the threshold of the impact degree of the comprehensive deviation of working hours. In response to the impact degree of the comprehensive deviation of working hours being greater than the threshold of the impact degree of the comprehensive deviation of working hours, in step S440, adopt a complete rescheduling strategy to adaptively adjust the production disturbance of the operation process of the flexible job shop. In response to the impact degree of the comprehensive deviation of working hours not being greater than the threshold of the impact degree of the comprehensive deviation of working hours, in step S450, form the first optimal rescheduling plan to adaptively adjust the production disturbance of the operation process of the flexible job shop.

[0071] In the embodiments of the present application, when a disturbance event occurs, by processing the information in devices such as RFID and PLC, the active perception and recognition of abnormal events in the workshop are realized to obtain the type of the disturbance event.

[0072] In the embodiments of the present application, production disturbances are prevalent in the production process of flexible job shops. According to their obviousness, perceptibility, and detectability, the disturbance events can be divided into explicit disturbances and implicit disturbances. Specifically, explicit disturbances include accidental events such as emergency order insertion, sudden material supply interruption, process design plan change, and equipment damage. After each explicit disturbance event occurs, it can be immediately recognized and usually triggers an obvious system response or change. In contrast, implicit disturbances often occur in real time during the production process, with a high occurrence frequency, but the impact of each occurrence is relatively small. It may need to be identified through indirect methods or long-term observation, and the impact may lead to serious consequences only after long-term accumulation, such as potential defects in mechanical design, equipment performance degradation, and fluctuations in workers' processing time.

[0073] Since the occurrence frequency of explicit disturbances is low, once they occur, they will cause serious interference to the production process. A complete rescheduling strategy must be immediately executed to cope with the disturbances in order to quickly restore the normal production state and minimize the impact on production efficiency and product quality. Therefore, a complete rescheduling strategy is adopted to adaptively adjust the production disturbance of the flexible job shop operation process by rescheduling the unfinished processes, or a partial rescheduling strategy is adopted to adaptively adjust the production disturbance of the flexible job shop operation process by rescheduling the processes affected by the disturbance.

[0074] In the embodiments of the present application, by comprehensively evaluating the partial rescheduling strategy and the complete rescheduling strategy, the better evaluated rescheduling strategy is used as the second-optimal rescheduling plan. The specific process involved in forming the second-optimal rescheduling plan can be referred to Figure 5 。

[0075] Figure 5 An exemplary flowchart showing the formation of the second-optimal rescheduling plan in the embodiments of the present application is shown.

[0076] As Figure 5 shown, in step S510, the robustness, stability, and economy corresponding to the partial rescheduling strategy and the complete rescheduling strategy are calculated respectively. In step S520, based on the robustness, stability, and economy corresponding to the partial rescheduling strategy and the complete rescheduling strategy, the comprehensive evaluation values corresponding to the partial rescheduling strategy and the complete rescheduling strategy are obtained respectively. In step S530, the strategy with the lower corresponding comprehensive evaluation value is used as the second-optimal rescheduling plan.

[0077] In the embodiments of the present application, the specific process involved in step S510 can refer to the specific processes related to the robustness, stability, and economy corresponding to the right shift rescheduling strategy and the partial rescheduling strategy described above, which will not be elaborated here.

[0078] In the embodiments of the present application, the specific process involved in step S520 can refer to the specific processes of obtaining the comprehensive evaluation values corresponding to the right shift rescheduling strategy and the partial rescheduling strategy respectively based on the robustness, stability, and economy corresponding to the right shift rescheduling strategy and the partial rescheduling strategy described above, which will not be elaborated here.

[0079] Since implicit disturbances occur frequently, if adjustments are made once an event disturbance or system deviation occurs, rescheduling will be frequently triggered. Frequent adjustments usually mean continuous changes in production plans, resource allocation, personnel arrangements, etc., and a stable production rhythm cannot be formed. This increases decision-making pressure and costs while affecting the continuity and stability of workshop operations, and instead reduces production efficiency. Therefore, when dealing with implicit disturbances, it is required to systematically evaluate the impact degree of the comprehensive labor hour deviation and select appropriate countermeasures according to the evaluation results.

[0080] Suppose a disturbance event ξ1 occurs at time t, which affects the completion time of operation O i,k When calculating the impact degree of the completion time deviation on the operation itself, it is necessary to consider the problem that there are differences in the operation durations of different operations. That is, under the same time deviation, the operation with a shorter self-operation duration is more affected than the operation with a longer self-operation duration. At the same time, when the operation where the disturbance occurs is a critical operation or has higher requirements for processing quality, the tolerance of this operation to operation deviation will be relatively low. Therefore, the comprehensive labor hour deviation impact degree I ika is established to quantify the degree of impact of the completion time deviation on the operation itself.

[0081] Since the operation of each individual operation alone cannot reflect the impact degree of the deviation on the entire flexible job shop, it is necessary to further calculate the total impact degree of the operation deviation on the entire shop. In the initial scheduling plan of the flexible job shop, the work content and processing sequence of each production unit are optimized and generated according to the scheduling objectives. Each operation included in each workpiece is also restricted by the specified process route. Except for the operations at the end of the production line, when the processing time of each operation in the production scheduling plan changes, it will affect the normal execution of the subsequent operations and ultimately have a chain reaction on the overall production process. The subsequent operations include the subsequent operations of the production unit and the subsequent operations of the workpiece. It is quantified by the comprehensive labor hour deviation impact degree I of all affected operations.

[0082] In the embodiments of the present application, the comprehensive deviation impact degree of working hours is obtained through the comprehensive deviation impact degree calculation formula of working hours. Among them, the comprehensive deviation impact degree calculation formula of working hours is: I = ∑ Ba(O)t I ika , where I is the comprehensive deviation impact degree of working hours, B a (O) t represents the set of all processes affected by the disturbance event at time t. I ika is the comprehensive deviation impact degree of working hours corresponding to process O i,k , PE ika is the actual completion time of process O i,k on production unit R a , E ika is the expected completion time of process O i,k on production unit R a , T ika is the standard operation time required when production unit R a completes the processing task of process O i,k , λ ik ∈(0,1] is the importance coefficient of process O i,k .

[0083] In the embodiments of the present application, the specific process of forming the first optimal rescheduling plan can be referred to the foregoing, and will not be elaborated here.

[0084] Through the above process of adaptively adjusting the production disturbance of the flexible job shop operation process, when there are large-scale and drastic changes in the production environment or production operation state that cannot be ignored, through the adaptive dynamic scheduling mechanism, the flexible job shop can sense the abnormal changes beyond the threshold range of the predetermined monitoring parameters, adopt appropriate rescheduling plans to cope with the disturbances, so that the system can still operate according to specific production goals, thereby maintaining stability and efficiency in a changing environment and realizing adaptive dynamic scheduling. This adaptive process can not only cope with temporary changes, but also improve the overall performance and anti-disturbance ability of the system through continuous optimization. This way enables the system to automatically adjust and optimize its own operation under complex and unpredictable conditions, thereby improving long-term stability and flexibility.

[0085] In summary, through the flexible job shop scheduling optimization solution provided above, the embodiments of the present application can construct a dynamic closed-loop control system based on a dual mechanism of periodic scheduling and disturbance event-driven. By performing periodic rescheduling on the operation process of the flexible job shop when the cycle scheduling opportunity is reached, and performing production disturbance adaptive adjustment on the operation process of the flexible job shop when a disturbance event occurs. Periodic rescheduling can prevent the cumulative deviation of slow drift, smooth short-term fluctuations, and avoid the line oscillation caused by frequent adjustments. The disturbance trigger mechanism can quickly respond to sudden abnormal events and maintain the stability of the production rhythm, meeting the strict requirements of continuous production in high-precision manufacturing scenarios, which makes the system have anti-interference resilience and production stability guarantee. At the same time, based on the hierarchical response strategy of disturbance type and severity, it not only avoids the waste of computing resources caused by over-scheduling, but also can start full rescheduling when necessary, achieving a balance between computing efficiency and scheduling quality.

[0086] Further, in some embodiments, during the process of forming the first optimal rescheduling scheme for periodic rescheduling, by evaluating the robustness, stability, and economy of right-shift rescheduling and partial rescheduling strategies, the trade-off of multi-dimensional optimization is realized, avoiding the bias of a single index, so as to select the optimal adjustment scheme and avoid the limitations of a single strategy.

[0087] Furthermore, in some embodiments, during the process of performing production disturbance adaptive adjustment, by distinguishing between explicit disturbances and implicit disturbances, different scheduling strategies can be matched according to different disturbance characteristics, avoiding resource waste or insufficient effects caused by using a single response mode. By introducing the comprehensive deviation influence degree threshold of working hours as the decision boundary for handling implicit disturbances, the quantitative evaluation of the influence of implicit disturbances is realized, preventing over-scheduling triggered by minor deviations and avoiding the out-of-control of cumulative deviations at the same time. By forming a two-level decision structure of disturbance type judgment and influence degree evaluation to form a redundant verification mechanism, it can not only prevent a single judgment error, but also adapt to complex disturbance superposition scenarios.

[0088] Still further, in some embodiments, during the process of determining whether a disturbance event occurs, the expected production state is clarified through the initial scheduling scheme, providing an objective basis for subsequent comparison and ensuring that the judgment process is well-founded. By continuously obtaining the actual production state data and dynamically tracking the operation of the workshop, a transparent monitoring of the production process is formed. By comparing the differences between the expected and actual states, the abnormal points can be quickly located, making the occurrence of disturbance events depend on objective data rather than empirical judgment, reducing human bias and improving the scientificity of decision-making.

[0089] The embodiment of the present application also provides a flexible job shop scheduling optimization system, which can adopt the foregoing flexible job shop scheduling optimization method 100 for flexible job shop scheduling optimization, or can adopt other methods for flexible job shop scheduling optimization, and the present application does not limit this here.

[0090] Figure 6 The exemplary structural block diagram of the flexible job shop scheduling optimization system according to the embodiment of the present application is shown.

[0091] As Figure 6 shown, the system 600 includes a cloud server center 610, an edge server center 620, and a flexible job shop 630.

[0092] Specifically, the cloud server center 610 is used to implement resource management, adaptive dynamic scheduling, real-time monitoring and feedback, data analysis, platform resource management of the flexible job shop, and establish dual-channel redundant communication with the edge server center.

[0093] Specifically, the edge server center 620 is used to implement device access, data preprocessing, edge computing, local fault-tolerant scheduling of the flexible job shop, and cooperate with the cloud server center to manage resource status.

[0094] Specifically, the flexible job shop 630 is used to synchronize data with the cloud server center through the edge server center and execute dynamic scheduling tasks.

[0095] In the embodiment of the present application, for the specific composition of the cloud server center, the edge server center, and the flexible job shop, reference can be made to Figure 7 .

[0096] Figure 7 The specific composition architecture diagrams of the cloud server center, the edge server center, and the flexible job shop according to the embodiment of the present application are shown.

[0097] As Figure 7As shown in the figure, the cloud server center includes a cloud platform, an API Server, and a CloudCore. Among them, the API Server, as the core component for managing the resources of the entire cluster, is responsible for maintaining and managing various Kubernetes resource objects and storing the status information of all resource objects in the cluster. The CloudCore cloud core module is responsible for the synchronization and maintenance with edge nodes, and it synchronizes information with the Kubernetes cluster through the List-Watch mechanism. The built-in CloudHub module in CloudCore and the EdgeHub module built into the edge side adopt a dual-channel redundant transmission mechanism. The main channel establishes a persistent connection based on the MQTT protocol to achieve command-response interaction between the cloud and edge nodes. The backup channel supports message transmission through the QUIC protocol to improve the reliability and availability of the industrial network system. Through structured message encapsulation, it synchronizes the basic metadata of Kubernetes, such as Pods, ConfigMaps, etc. In addition, CloudCore also includes an EdgeControler module and a DeviceController module, which are respectively used to manage the metadata of Kubernetes and the CRD resources related to devices.

[0098] In the embodiment of the present application, for the specific composition of the cloud platform, reference can be made to Figure 8 .

[0099] Figure 8 The figure shows the specific composition architecture diagram of the cloud platform in the embodiment of the present application.

[0100] As Figure 8 shown in the figure, the cloud platform mainly consists of a registration center, a configuration center, a service gateway, service circuit breaker, a database, a resource management module, an adaptive dynamic scheduling module for the workshop production system, a real-time monitoring and feedback module, a data analysis module, a system management module, etc.

[0101] Specifically, the registration center provides service discovery and registration services. The registration center is responsible for recording the locations (such as IP addresses and port numbers) of each microservice, enabling other microservices to easily find and communicate with it. When a new microservice starts, it registers its information with the service discovery component, and when other microservices need to call it, they can query its location information through the service discovery component. The technology stack used by this component is Spring Cloud Alibaba Nacos.

[0102] Specifically, the configuration center provides a configuration management service, which is responsible for managing the configuration information of microservices, including database connection parameters, log levels, business rules, etc. When the configuration needs to be modified, instead of modifying each microservice one by one, it can be uniformly modified through the configuration management service. This can ensure the consistency of the configuration and facilitate configuration switching in different environments. The technology stack used by this component is also Spring Cloud Alibaba Nacos.

[0103] Specifically, as the entry of the microservice system, the service gateway is responsible for receiving external requests and routing them to the corresponding microservices. It can perform unified authentication, authorization, traffic limiting, caching, etc. on requests, protect the security of internal microservices, and improve the performance and stability of the system. The technology stack used by this component is Spring Cloud Gateway.

[0104] Specifically, service fusing aims to protect the high availability, stability, and elasticity of services. When a certain microservice in the fan-out link is unavailable or the response time is too long, service degradation will occur, and then the call to the microservice of that node will be fused, quickly returning error response information. When it is detected that the call response of the microservice of that node is normal, the call link will be restored. The technology stack used by this component is Spring Cloud Alibaba Sentinel.

[0105] Specifically, as the core component for storing data, each microservice usually has its own independent database (which can be a relational database or a non-relational database) for storing business data related to that service. In this scheduling system, the relational database MySQL and the non-relational database Redis are used.

[0106] Specifically, the resource management microservice includes a resource management module, an adaptive dynamic scheduling module for the workshop production system, a real-time monitoring and feedback module, a data analysis module, a system management module, etc.

[0107] Specifically, the resource management module includes a machine management unit, a workpiece management unit, a process management unit, a working procedure management unit, a worker management unit, a task management unit, and a remaining unit (not shown in Figure 8 ), etc. The task management unit is used to define the flexible job shop scheduling task information, and the task information includes product types and quantities, etc. The remaining unit defines the key resource element information involved in the flexible job shop scheduling task, which is the main information source and information carrier during the execution of the scheduling task.

[0108] Specifically, the adaptive dynamic scheduling module of the workshop production system includes a scheduling algorithm unit, a rescheduling mechanism unit, a scheduling display unit, etc. This microservice is the core of the flexible job shop dynamic scheduling. For edge manufacturing resources with limited computing resources or computationally intensive optimization tasks, the computing tasks can be offloaded to the cloud platform service through the HTTP protocol interface provided by the cloud platform service for operation. After the task calculation is completed, the task result can be returned to the flexible job shop resources. The scheduling algorithm unit is mainly implemented based on the hybrid genetic-simulated annealing algorithm. For a given optimization calculation task, through general steps including population creation, iterative evolution, individual optimization, and chromosome decoding, it integrates simulated annealing for scheduling optimization. The rescheduling mechanism unit designs a rescheduling drive mechanism considering the impact of dynamic disturbance events on the scheduling scheme, and at the same time uses the algorithm in the scheduling algorithm unit to solve the optimal rescheduling scheme. The scheduling display unit provides a visual interaction interface for the final scheduling scheme.

[0109] Specifically, the real-time monitoring and feedback module includes a disturbance trigger unit, a data collection unit, a real-time kanban unit, etc. The disturbance trigger unit is responsible for triggering the rescheduling mechanism unit of the dynamic scheduling microservice for dynamic scheduling after receiving the disturbance abnormal information from the edge device. The data collection unit is responsible for collecting the disturbance abnormal information and using the data analysis microservice maintenance management module to track and maintain the equipment. The real-time kanban module provides a real-time workshop status kanban to realize the visual management of the workshop.

[0110] The data analysis module includes a performance analysis unit, an intelligent optimization unit, a maintenance management unit, etc. The performance analysis unit is responsible for forming an analysis report by comparing with the past manufacturing process. The intelligent optimization unit tunes the parameters of the algorithm in the scheduling algorithm unit based on reinforcement learning. The maintenance management unit tracks and guides the equipment to ensure its availability.

[0111] Specifically, the system management module includes a user management unit, a permission management, and a unit data management unit, etc. The user management unit and the permission management unit are the infrastructures of the cloud service platform, and manage the user permissions and resource access through the role-based access control model. The data management unit is responsible for managing and controlling the documents and data related to the production unit and the system.

[0112] In the embodiment of the present application, for the specific composition of the adaptive dynamic scheduling module of the workshop production system, reference can be made to Figure 9 .

[0113] Figure 9 Fig. shows an exemplary structural block diagram of the adaptive dynamic scheduling module of the workshop production system according to the embodiment of the present application.

[0114] As Figure 9As shown in the figure, the adaptive dynamic scheduling module 900 of the workshop production system includes an initial scheduling plan formation unit 910, a first judgment unit 920, a periodic rescheduling unit 930, a second judgment unit 940, an iteration unit 950, and a production disturbance adaptive adjustment unit 960.

[0115] Specifically, the initial scheduling plan formation unit 910 is used to form an initial scheduling plan for the operation process of the flexible job shop based on the current production tasks, production goals, process constraints, and the availability of production resources.

[0116] Specifically, the first judgment unit 920 is used to judge whether the periodic scheduling time has arrived.

[0117] Specifically, in response to the arrival of the periodic scheduling time, the periodic rescheduling unit 930 is used to form a first optimal rescheduling plan to perform periodic rescheduling on the operation process of the flexible job shop.

[0118] Specifically, in response to the non-arrival of the periodic scheduling time, the second judgment unit 940 is used to judge whether a disturbance event has occurred.

[0119] Specifically, in response to the non-occurrence of a disturbance event, the iteration unit 950 is used to return to the step of forming the initial scheduling plan for the operation of the flexible job shop.

[0120] Specifically, in response to the occurrence of a disturbance event, the adaptive dynamic scheduling unit 960 is used to form a first optimal rescheduling plan, a second optimal rescheduling plan, or a complete rescheduling strategy based on the type of the disturbance event and the severity of the disturbance to perform production disturbance adaptive adjustment on the operation process of the flexible job shop.

[0121] When the system 600 performs flexible job shop scheduling optimization by using the aforementioned flexible job shop scheduling optimization method 100, the initial scheduling plan formation unit 910 executes the aforementioned step S110, the first judgment unit 920 executes the aforementioned step S120, the periodic rescheduling unit 930 executes the aforementioned step S130, the second judgment unit 940 executes the aforementioned step S140, the iteration unit 950 executes to return to step S110, and the production disturbance adaptive adjustment unit 960 executes the aforementioned step S150. The specific execution process can be referred to the previous text and will not be elaborated here.

[0122] In the embodiments of the present application, the edge server center, as an intermediate medium for the workshop resources to access the cloud server center, has a certain edge intelligence and is mainly composed of an EdgeCore and an MQTT server.

[0123] Specifically, the EdgeCore edge core module connects various edge devices, realizes the access management of workshop devices, converts their data into a format processable by the system, and can also preprocess the collected data, such as filtering and aggregation operations. It can also store important data locally, reducing the burden on the cloud and ensuring data security. At the same time, it supports the execution of edge computing tasks and can process data nearby at the edge according to rules to achieve real-time response. In addition, Edgecore is responsible for communicating and coordinating with the K8S APIServer in the cloud to ensure smooth information interaction between the edge and the cloud. Inside, it also better realizes functions and ensures system security through protocol adaptation and conversion, support for containerized operation, and having security mechanisms and authentication and authorization, etc.

[0124] Specifically, the MQTT server is a core component of the Internet of Things and messaging system. It mainly acts as a messaging hub, receives messages from numerous publishers (such as various sensors and intelligent devices), and forwards them to subscribers of corresponding topics. It also has protocol conversion and message routing functions, can process messages of different protocols and accurately route them. At the same time, it can store messages for offline message processing to ensure that data is not lost even when the device is offline. When dealing with a large number of message requests, the MQTT server can achieve load balancing and traffic control to ensure the efficient and stable operation of the system. In addition, it also provides security management, including user authentication, authorization, and message encryption, to ensure system security and prevent illegal access and information leakage.

[0125] Specifically, to cope with network fluctuations in a complex workshop environment, a three-level fault tolerance mechanism is designed: ACK confirmation and exponential backoff retransmission strategy are adopted for cloud-edge communication to ensure the reachability of instructions; the cloud monitors through heartbeat packets to maintain the connection activity of edge nodes; a local meta-database is established at the edge to support maintaining the basic scheduling function based on cached data during network interruption, and state consistency is achieved through the differential data synchronization mechanism after the network is restored.

[0126] In the embodiment of the present application, the flexible job shop includes manufacturing resources, auxiliary resources, and a flexible intelligent production line. Among them, the manufacturing resources include various device terminals supporting different protocols, such as dual-arm robots, PLC three-axis robots, CNC six-axis robots, etc., and various sensors supporting them. Since the data transmission protocols and formats of different robots and sensors are not the same, KubeEdge adopts the design of Mapper, which can convert the protocols of these devices into the MQTT protocol to achieve the synchronization and management of edge applications and device data in the cloud. Auxiliary resources are indispensable tools for manufacturing resources to execute tasks, such as fixtures, grippers, etc. The flexible intelligent production line is the carrier of resources and can be divided into various auxiliary devices, personnel resources, processing devices, manufacturing units, and intelligent production lines, etc. according to different granularities.

[0127] Although several embodiments of the present application have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many changes, alterations, and alternative forms may be contemplated by those skilled in the art without departing from the spirit and scope of the present application. It should be understood that various alternatives to the embodiments of the present application described herein may be employed in practicing the present application. The appended claims are intended to define the scope of the present application and thus cover equivalents or alternatives within the scope of these claims.

Claims

1. A flexible job shop scheduling optimization method, characterized in that, include: Form an initial scheduling plan for the flexible job shop operation process based on current production tasks, production goals, process constraints, and production resource availability; Determine whether the periodic scheduling opportunity has arrived; In response to reaching a periodic scheduling opportunity, forming a first optimal rescheduling plan to periodically reschedule the flexible job shop operation process; In response to the periodic scheduling opportunity not being reached, determining whether a disturbance event occurs; In response to no disturbance event occurring, returning to the step of forming an initial scheduling plan for the flexible job shop operation; In response to a disturbance event, a first optimal rescheduling plan, a second optimal rescheduling plan or a complete rescheduling strategy is formed based on the type of the disturbance event and the severity of the disturbance to perform production disturbance adaptive adjustment on the flexible job shop operation process.

2. The flexible job shop scheduling optimization method according to claim 1, wherein, In the process of forming the first optimal rescheduling plan to periodically rescheduling the flexible job shop operation process, the following steps are performed: Calculate the robustness, stability, and economy of the right-shift rescheduling strategy and the partial rescheduling strategy respectively; Obtaining comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy based on their respective robustness, stability, and economy; The strategy with the lower corresponding comprehensive evaluation value is taken as the first optimal rescheduling solution; Among them, when the strategy with the lower comprehensive evaluation value is the right-shift rescheduling strategy, the start processing time of the disturbance-affected process is changed to achieve periodic rescheduling of the flexible job shop operation process; When the strategy with the lower comprehensive evaluation value is the partial rescheduling strategy, the operation process of the flexible job shop is periodically rescheduled by rescheduling the disturbance-affected processes.

3. The flexible job shop scheduling optimization method according to claim 2, wherein In the process of calculating the robustness, stability, and economy of the right-shift rescheduling strategy and the partial rescheduling strategy, the following steps are performed: The robustness corresponding to the right shift rescheduling strategy and the partial rescheduling strategy is obtained through the robustness calculation formula, where the robustness calculation formula is as follows: f1 is the robustness, and C′ max is the makespan corresponding to the right shift rescheduling strategy or the partial rescheduling strategy, and C max is the makespan corresponding to the initial scheduling scheme; The stability corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy is obtained through the stability calculation formula, where the stability calculation formula is: f2 is the stability, Q ik is the change in the processing equipment for process O ik R ik is the production unit assigned to process O when the initial scheduling plan is adopted ik R′ ik is the production unit assigned to process O when the right-shift rescheduling strategy or the partial rescheduling strategy is adopted ik TC ik represents the change in the completion time of process O ik ET ika is the end processing time of process O on production unit R when the initial scheduling plan is adopted ik ET a is the end processing time of process O on production unit R when the right-shift rescheduling strategy or the partial rescheduling strategy is adopted ika′ ik R a′ i N′ is the number of workpieces participating in the right-shift rescheduling strategy or the partial rescheduling strategy, n i ′ is the number of processes of workpiece J i that participate in the right-shift rescheduling strategy or the partial rescheduling strategy, O i is the total number of processes of workpiece J i ρ1 is the penalty weight for production unit transfer, and ρ2 is the penalty weight for process completion time deviation; The economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy is obtained through the economy calculation formula. The economy calculation formula is as follows: L is the maximum value of a′, N′ is the number of workpieces participating in the right-shift rescheduling strategy or the partial rescheduling strategy, and n i ′ is the number of processes of workpiece J i participating in the right-shift rescheduling strategy or the partial rescheduling strategy, ET ika′ is the finishing time of process O ik on production unit R a′ when the right-shift rescheduling strategy or the partial rescheduling strategy is adopted, and ST ika′ is the starting time of process O ik on production unit R a′ when the right-shift rescheduling strategy or the partial rescheduling strategy is adopted, and C′ max is the makespan corresponding to the right-shift rescheduling strategy or the partial rescheduling strategy.

4. The flexible job shop scheduling optimization method according to claim 2, characterized in that In the process of obtaining the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy based on the robustness, stability, and economy corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy, the following steps are performed: The robustness, stability, and economy corresponding to the right shift rescheduling strategy and the partial rescheduling strategy are normalized respectively using the normalization formula to obtain the robustness standard value, the stability standard value, and the economy standard value. The normalization formula is is the standard value of the j-th index, f j is the j-th index, f j,min is the minimum value among all the indices, f j,max is the maximum value among all the indices. The indices include robustness, stability, and economy; The comprehensive evaluation calculation formula is used to calculate the robustness standard value, stability standard value, and economy standard value to obtain the comprehensive evaluation values corresponding to the right-shift rescheduling strategy and the partial rescheduling strategy respectively. Among them, the comprehensive evaluation calculation formula is as follows: is the robustness standard value, and ω1 is the weight factor of the robustness standard value. is the stability standard value, and ω2 is the weight factor of the stability standard value. is the economy standard value, and ω3 is the weight factor of the economy standard value.

5. The flexible job shop scheduling optimization method according to claim 1, wherein In the process of forming a first optimal rescheduling plan, a second optimal rescheduling plan, or a complete rescheduling strategy based on the type of disturbance event and the severity of the disturbance to adaptively adjust the production disturbance to the flexible job shop operation process, the following steps are performed: Determine whether the disturbance event is an explicit disturbance or an implicit disturbance; In response to the disturbance event being an explicit disturbance, forming a second optimal rescheduling plan to adaptively adjust the production disturbance to the operation process of the flexible job shop; In response to the type of the disturbance event being an implicit disturbance, determining whether the comprehensive deviation impact of working hours is greater than a comprehensive deviation impact threshold of working hours; In response to the fact that the comprehensive deviation impact of working hours is greater than the comprehensive deviation impact threshold of working hours, a complete rescheduling strategy is adopted to adaptively adjust the production disturbance of the flexible job shop operation process; In response to the fact that the comprehensive deviation impact of working hours is not greater than the comprehensive deviation impact threshold of working hours, a first optimal rescheduling plan is formed to perform production disturbance adaptive adjustment on the operation process of the flexible job shop.

6. The flexible job shop scheduling optimization method according to claim 5, wherein In the process of forming the second optimal rescheduling plan to adaptively adjust the production disturbance of the flexible job shop operation process, the following steps are performed: Calculate the robustness, stability, and economy of the partial and full rescheduling strategies respectively; Obtaining comprehensive evaluation values corresponding to the partial rescheduling strategy and the full rescheduling strategy based on their respective robustness, stability, and economy; The strategy with the lower corresponding comprehensive evaluation value is taken as the second best rescheduling solution; Among them, when the strategy with the lower comprehensive evaluation value is the partial rescheduling strategy, the production disturbance-affected processes are rescheduled to achieve adaptive adjustment of the flexible job shop operation process to the production disturbance; When the strategy with the lower comprehensive evaluation value is the complete rescheduling strategy, the unfinished processes are rescheduled to achieve adaptive adjustment of the production disturbance to the operation process of the flexible job shop.

7. The flexible job shop scheduling optimization method according to claim 5, wherein The impact degree of the comprehensive working hour deviation is obtained through the calculation formula of the impact degree of the comprehensive working hour deviation. Among them, the calculation formula of the impact degree of the comprehensive working hour deviation is as follows: I is the impact degree of the comprehensive working hour deviation, B a (O) t represents the set of all processes affected by the disturbance event at time t, I ika is the impact degree of the comprehensive working hour deviation corresponding to process O, PE i,k Process O ika in production unit R i,k The actual completion time, E a is the expected completion time of process O ika in production unit R i,k The standard operation time required when production unit R a completes the processing task of process O, T ika is the standard operation time required when production unit R a completes the processing task of process O i,k , λ ik ∈(0,1] is the importance coefficient of process O i,k .

8. The flexible job shop scheduling optimization method according to claim 1, wherein In the process of determining whether a disturbance event has occurred, perform the following steps: Obtain the expected production status of the flexible job shop based on the initial scheduling plan; Obtain the actual production status corresponding to the flexible job shop; Determine whether there is a discrepancy between the actual production status and the expected production status; In response to a difference between an actual production state and an expected production state, determining that a disturbance event occurs; In response to no difference between the actual production state and the expected production state, it is determined that no disturbance event has occurred.

9. A flexible job shop scheduling optimization system, characterized in that, The flexible job shop scheduling optimization method according to any one of claims 1 to 8 is used to perform flexible job shop scheduling optimization, wherein the system comprises: The cloud server center is used to implement resource management, adaptive dynamic scheduling, real-time monitoring and feedback, data analysis, platform resource management, and dual-channel redundant communication with the edge server center for flexible job shops; The edge server center is used to implement equipment access, data preprocessing, edge computing, local fault-tolerant scheduling, and coordinated resource status with the cloud server center in the flexible workshop; Flexible job shop, used to synchronize data between edge server center and cloud server center and perform dynamic scheduling tasks; The cloud service platform includes a flexible job shop adaptive dynamic scheduling module, which is used to periodically reschedule the flexible job shop operation process or perform production disturbance adaptive adjustment on the flexible job shop operation process.

10. The flexible job shop scheduling optimization system according to claim 9, characterized in that, The workshop production system adaptive dynamic scheduling module includes an initial scheduling scheme forming unit, a first judgment unit, a periodic rescheduling unit, a second judgment unit, an iteration unit and a production disturbance adaptive adjustment unit; The initial scheduling plan forming unit is used to form an initial scheduling plan for the flexible job shop operation process based on current production tasks, production goals, process constraints, and production resource availability; The first judgment unit is used to judge whether the periodic scheduling opportunity has arrived; In response to reaching a periodic scheduling opportunity, the periodic rescheduling unit is used to form a first optimal rescheduling scheme to periodically rescheduling the flexible job shop operation process; In response to the periodic scheduling opportunity not being reached, using the second judgment unit to judge whether a disturbance event occurs; In response to the non-occurrence of a disturbance event, return to the step of forming the initial scheduling plan for the operation of the flexible job shop by using the iterative unit; In response to the occurrence of a disturbance event, use the adaptive dynamic scheduling unit to adaptively adjust the production disturbance of the operation process of the flexible job shop by forming the first optimal rescheduling plan, the second optimal rescheduling plan or the complete rescheduling strategy based on the type of the disturbance event and the severity of the disturbance.

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