Power flexible manufacturing regulation and control method and device, electronic equipment and storage medium

Abstract

The invention provides an electric power flexible manufacturing regulation and control method and device, electronic equipment and a storage medium. The method comprises the steps of configuring corresponding production scheduling rules and rule constraint conditions based on features of a target production line; generating an initial scheduling scheme based on the production scheduling rule and the rule constraint condition through a production scheduling algorithm, and starting to execute a production scheduling task based on the initial scheduling scheme; and after the disturbance information is detected, adjusting the initial scheduling scheme based on the disturbance information to obtain an adjusted scheduling scheme, and continuing to execute the production scheduling task based on the adjusted scheduling scheme. The invention provides an electric power flexible manufacturing regulation and control scheme, the robustness and applicability of a scheduling method are improved through rule configuration and disturbance processing, and a production scheduling system can be quickly constructed and adjusted according to the characteristics of a production line, so that scheduling scenes with different characteristics are coped, time and labor cost are saved, the efficiency of production scheduling is effectively improved, and the production scheduling efficiency is improved. The problems that an existing electric power manufacturing scene is single, fixed and inflexible are solved.

Description

Technical Field

[0001] The present application relates to the field of electric power intelligent manufacturing technology, and in particular to an electric power flexible manufacturing control method, device, electronic equipment and storage medium. Background Art

[0002] In the field of power manufacturing, flexible manufacturing systems (FMS) are widely used because they can quickly adapt to changes in production demand. With its high degree of automation and flexibility, flexible manufacturing systems can quickly respond to market changes and meet personalized and diversified production needs.

[0003] However, with the increasing complexity of the production environment, the existing flexible manufacturing system has some defects: First, the existing flexible manufacturing system often seems to be unable to cope with the changing scheduling scenarios. Since each scenario has its own unique scheduling characteristics, the reusability of the scheduling system between different scenarios is greatly reduced. This limitation seriously restricts production efficiency and the adaptability of the system. Secondly, the current practice is to customize the development of scheduling methods and systems for each specific scenario. Although this method is effective in specific situations, it inevitably brings huge development workload and time cost. With the increasing market demand for rapid response, this practice has gradually become inappropriate. In addition, the scheduling methods of existing systems often lack sufficient flexibility and adaptability. When faced with emergencies or disturbances in the production process, it is difficult for existing systems to quickly adjust scheduling strategies to adapt to new production needs. This not only affects production efficiency, but also increases the operational risks of enterprises.

[0004] The preceding description is intended to provide general background information and does not necessarily constitute prior art. Summary of the invention

[0005] In response to the above technical problems, the present application provides a method, device, electronic device and storage medium for flexible power manufacturing control, which solve the problems of single, fixed and inflexible existing power manufacturing scenarios and effectively improve the efficiency and applicability of production scheduling.

[0006] In order to solve the above technical problems, the present application provides a method for controlling electric power flexible manufacturing, comprising the following steps:

[0007] Configure the corresponding production scheduling rules and rule constraints based on the characteristics of the target production line;

[0008] Generate an initial scheduling plan based on the scheduling rules and the rule constraints through a scheduling algorithm, and start executing the scheduling task based on the initial scheduling plan;

[0009] After the disturbance information is detected, the initial scheduling plan is adjusted based on the disturbance information to obtain an adjusted scheduling plan, so as to continue to execute the production scheduling task based on the adjusted scheduling plan.

[0010] Furthermore, in some embodiments of the present application, the production scheduling rules and rule constraints corresponding to the characteristic configuration of the target production line include:

[0011] If it is detected that the characteristics of the target production line meet the discrete task, various attributes that determine the priority are configured, and the task priority under the corresponding attribute is configured;

[0012] If it is detected that the characteristics of the target production line meet the requirements of a continuous task, a weighted value is calculated based on the weight values ​​of each attribute, and the task priority is determined based on the weighted value.

[0013] Furthermore, in some embodiments of the present application, the production scheduling rules and rule constraints corresponding to the characteristic configuration of the target production line further include:

[0014] Define each attribute and its corresponding weight value that determines the priority according to the production scheduling rules;

[0015] The weight value of each attribute is normalized.

[0016] Furthermore, in some embodiments of the present application, the generating of an initial scheduling scheme based on the scheduling rule and the rule constraint by the scheduling algorithm includes:

[0017] Converting the production scheduling rules and the rule constraints into input parameters of the production scheduling algorithm;

[0018] Calculating the task priority by the scheduling algorithm based on the scheduling rules and the weight values ​​of the attributes;

[0019] The production scheduling algorithm generates an initial scheduling plan corresponding to the production scheduling task based on the task priority and the rule constraints.

[0020] Further, in some embodiments of the present application, after detecting the disturbance information, adjusting the initial scheduling scheme based on the disturbance information to obtain the adjusted scheduling scheme includes:

[0021] After detecting a disturbance in the flexible manufacturing system, generating disturbance information;

[0022] Analyze the disturbance information to determine the disturbance type corresponding to the disturbance information;

[0023] The initial scheduling scheme is adjusted based on the disturbance type to obtain an adjusted scheduling scheme.

[0024] Further, in some embodiments of the present application, adjusting the initial scheduling scheme based on the disturbance type to obtain an adjusted scheduling scheme includes:

[0025] If the disturbance type is determined to be a device failure disturbance, the faulty device is locked, and an alternative device with the same processing capacity as the faulty device is searched, the process task of the faulty device is transferred to the alternative device, and an adjusted scheduling plan is generated;

[0026] If the disturbance type is determined to be an order change disturbance, the changed order is added to the production sequence to be scheduled based on its priority, or the changed order is deleted from the production sequence to be scheduled, the production sequence to be scheduled is readjusted, and an adjusted scheduling plan is generated.

[0027] Further, in some embodiments of the present application, adjusting the initial scheduling scheme based on the disturbance type to obtain an adjusted scheduling scheme includes:

[0028] If the disturbance type is determined to be a progress abnormality disturbance, the corresponding deviation value is calculated based on the actual execution time and the planned time of the production scheduling task;

[0029] When it is determined that the deviation value is greater than a preset threshold, the initial scheduling plan is adjusted based on the arrival time or processing time change of the production resources to obtain an adjusted scheduling plan.

[0030] Accordingly, the present application also provides an electric power flexible manufacturing control device, comprising:

[0031] A rule configuration module is used to configure corresponding production scheduling rules and rule constraints based on the characteristics of the target production line;

[0032] A production scheduling module, used to generate an initial scheduling plan based on the production scheduling rules and the rule constraints through a production scheduling algorithm, and start executing the production scheduling task based on the initial scheduling plan;

[0033] The disturbance processing module is used to adjust the initial scheduling plan based on the disturbance information after detecting the disturbance information, so as to obtain an adjusted scheduling plan, so as to continue to execute the production scheduling task based on the adjusted scheduling plan.

[0034] The present application also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of the electric power flexible manufacturing control method as described above when executing the program.

[0035] The present application also provides a storage medium storing a computer program that can be loaded by a processor and execute the above-mentioned electric power flexible manufacturing control method.

[0036] Implementing the embodiments of the present application has the following beneficial effects:

[0037] As described above, the present application provides a method, device, electronic device and storage medium for controlling flexible manufacturing of electric power, which includes: configuring the corresponding production scheduling rules and rule constraints based on the characteristics of the target production line; generating an initial scheduling plan based on the production scheduling rules and rule constraints through the production scheduling algorithm, and starting to execute the production scheduling task based on the initial scheduling plan; after detecting the disturbance information, adjusting the initial scheduling plan based on the disturbance information to obtain the adjusted scheduling plan, so as to continue to execute the production scheduling task based on the adjusted scheduling plan. The present application provides a flexible manufacturing control scheme of electric power, which can quickly adapt to different production scenarios and demand changes through rule configurable technology, and can ensure timely response and adjustment in the face of uncertainty in the production process through disturbance analysis and processing technology, reducing the risk of production interruption, and reducing the time and cost of human intervention through automated production scheduling and disturbance response mechanism, and improving the efficiency and accuracy of production scheduling. It can be seen that the present application only needs to configure the corresponding parameters according to the characteristics of the production line to cope with scheduling scenarios with different characteristics, and analyze and process the disturbance of the flexible manufacturing system at the same time, so that the scheduling method is more robust. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor.

[0039] Figure 1 It is a flow chart of the electric power flexible manufacturing control method provided in the embodiment of the present application;

[0040] Figure 2 It is a flowchart of a specific implementation method of the electric power flexible manufacturing control method provided in the embodiment of the present application;

[0041] Figure 3 It is a structural schematic diagram of the electric power flexible manufacturing control device provided in an embodiment of the present application;

[0042] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0043] The realization of the purpose, functional features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. The above-mentioned drawings have shown clear embodiments of this application, which will be described in more detail later. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0044] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0045] It should be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0046] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0048] Flexible manufacturing systems are widely used in the production of aviation parts. However, since they have different scheduling characteristics in different scheduling scenarios, the scheduling system of flexible manufacturing systems is difficult to reuse between different scheduling scenarios. In actual production, the current common practice of scheduling system developers is to study scheduling methods and develop scheduling systems in a targeted manner according to the characteristics of different scenarios, but the workload is huge. If a production scheduling system can be quickly built for complex scheduling scenarios, a lot of time and labor costs can be saved. However, most of the current research on the scheduling problem of flexible manufacturing systems is aimed at a specific scenario.

[0049] In response to the reusability problem of the scheduling system between different scenarios, the embodiments of the present application provide an electric power flexible manufacturing control method, device, electronic device and storage medium, and propose a rule-configurable adaptive scheduling scheme. Decision makers only need to configure the corresponding parameters according to the characteristics of the production line to cope with scheduling scenarios with different characteristics. At the same time, it analyzes and processes the disturbances of the flexible manufacturing system, making the scheduling method more robust.

[0050] See also Figure 1 , Figure 1 : is a flow chart of the electric power flexible manufacturing control method provided in the embodiment of the present application. The electric power flexible manufacturing control method provided in this embodiment may specifically include the following steps:

[0051] S1. Configure the corresponding production scheduling rules and rule constraints based on the characteristics of the target production line;

[0052] Specifically, for step S1, first analyze the characteristics of the target production line, including its process flow, equipment capabilities, task types and other characteristic information, and configure corresponding production scheduling rules and rule constraints based on the production line characteristics, which may include but are not limited to task priority, resource allocation and time window, etc.

[0053] S2. Generate an initial scheduling plan based on the scheduling rules and rule constraints through the scheduling algorithm, and start executing the scheduling task based on the initial scheduling plan;

[0054] Specifically, for step S2, a production scheduling algorithm is used to generate an initial scheduling plan based on configured rules and constraints, and the production scheduling task is started according to the generated initial scheduling plan while monitoring the production process.

[0055] S3. After detecting the disturbance information, the initial scheduling plan is adjusted based on the disturbance information to obtain an adjusted scheduling plan, so as to continue to perform the production scheduling task based on the adjusted scheduling plan;

[0056] Specifically, for step S3, during the production process, disturbance information that may affect the scheduling plan, such as equipment failure, order change, etc., is detected in real time, and the scheduling plan is adjusted according to the disturbance information, so as to continue to execute the production scheduling task according to the adjusted scheduling plan until new disturbance information appears, and then continue to adjust the scheduling plan according to the disturbance information until the production scheduling task is completed.

[0057] It can be seen that the power flexible manufacturing control method provided in this embodiment can quickly adapt to different production scenarios and demand changes by adjusting the configuration rules according to the production line, thereby reducing development and maintenance costs; disturbance analysis and processing technology ensures that when faced with uncertainties in the production process, the system can respond and adjust in a timely manner to reduce the risk of production interruptions; reasonable scheduling rules and algorithms can improve resource utilization, reduce waiting time and processing costs; through automated scheduling and disturbance response mechanisms, human intervention is reduced, and the efficiency and accuracy of production scheduling are improved; it provides decision makers with flexible rule selection and configuration capabilities, and supports data and rule-based decision-making processes.

[0058] Furthermore, in some embodiments, step S1 "configuring corresponding production scheduling rules and rule constraints based on the characteristics of the target production line" may specifically include:

[0059] S11. If it is detected that the characteristics of the target production line meet the discrete task, configure the attributes that determine the priority, and configure the task priority under the corresponding attributes;

[0060] S12. If it is detected that the characteristics of the target production line meet the requirements of a continuous task, a weighted value is calculated based on the weight values ​​of each attribute, and the task priority is determined based on the weighted value.

[0061] Specifically, for the rule configuration of step S1, this embodiment mainly includes discrete task priority configuration and continuous task priority configuration; wherein, if it is detected that the characteristics of the target production line meet the discrete task, the various attributes that determine the priority are configured, and the task priority under the corresponding attribute is configured. The decision maker can configure the various attribute values ​​that determine the priority and directly specify the task priority under the corresponding attribute. For example, based on the remaining delivery time, urgency rate, importance and processing time, the decision maker can directly give a corresponding priority value according to the value of each attribute. If it is detected that the characteristics of the target production line meet the continuous task, the weighted value is calculated based on the weight value of each attribute, and the task priority is determined based on the weighted value. A weighted value is calculated by weighing the weights of attributes such as processing time, remaining delivery time, urgency rate, importance, etc., and the weighted value is divided by "1" as the priority of the task. The decision maker chooses to add the attributes involved in the decision and gives the weight values ​​of these attributes. The larger the weight value, the more attention the attribute is paid. The decision maker can flexibly configure the production scheduling rules and weight values ​​according to the specific characteristics and needs of the production line, so as to achieve more accurate scheduling.

[0062] By accurately configuring task priorities, this embodiment enables the system to arrange production tasks more reasonably and improve production efficiency; flexible rule configuration and weight value adjustment enable the system to adapt to the characteristics and needs of different production lines, enhancing the adaptability and flexibility of the system; reasonable weight value calculation and normalization processing ensure the rational allocation of resources among different tasks and avoid waste of resources; it provides decision makers with flexible rule selection and configuration capabilities, supports the decision-making process based on data and rules, and improves the scientific nature and effectiveness of decisions; through reasonable priority configuration, the system can better respond to changes in the production process, reduce the risk of production interruptions, and improve production continuity and stability.

[0063] Furthermore, in some embodiments, step S1 "configuring corresponding production scheduling rules and rule constraints based on the characteristics of the target production line" may further include:

[0064] Define each attribute and its corresponding weight value that determines the priority according to the production scheduling rules;

[0065] The weight value of each attribute is normalized.

[0066] Specifically, for step S1, in order to unify the dimensions so that the contribution score of each attribute to the priority falls roughly within the same magnitude range and the contribution of a certain attribute is not ignored due to a large magnitude difference, the values ​​of each attribute need to be normalized. The details are as follows:

[0067] The value of processing time score S1: S1 = (TT min ) / (Tmax -T min ), where S1 is the value of the processing time score; T is the task processing time; T min is the minimum processing time of the task to be scheduled; T max The maximum processing time of the task to be scheduled.

[0068] The value of the remaining delivery time score S2: S2 = (T1-T2) / T max , where S2 is the value of the remaining delivery time score; T1 is the longest delivery period; T2 is the remaining delivery time of the task; T max The longest delivery time among the tasks to be scheduled.

[0069] The value of the urgency score S3: S3 = (AA max -A min ) / (A max -A min ), where S3 is the value of the urgency score; A is the urgency of the task; A max A is the maximum urgency rate of the tasks to be scheduled; min It is the minimum urgency rate among the tasks to be scheduled.

[0070] The value of the importance score S4: S4 = (S max -S) / (S max -S min ), where S4 is the value of the importance score; S max is the maximum value score of the task; S is the value score of the task; S min The minimum score for the task. Regarding the importance, the value of "very important" is "1", the value of "very important" is "2", the value of "average" is "3", and the value of "unimportant" is "4".

[0071]

[0072] The value range of each attribute weight is specified as an integer from 0 to 100, and each weight value is normalized during calculation. The priority calculation formula is:

[0073] Where: A i is the score of each attribute value; ω i is the weight value corresponding to each attribute.

[0074] This embodiment defines each attribute and its corresponding weight value that determines the priority according to the production scheduling rules. These weight values ​​are the key factors in determining the priority of the task; the weight value of each attribute is normalized to ensure that the weight value is within a reasonable range and to avoid ignoring the contribution of a certain attribute. Normalization is an important step to ensure the fairness and effectiveness of the weight value.

[0075] This embodiment ensures the rational allocation of resources among different tasks through reasonable weight value calculation and normalization processing, avoids resource waste, and improves resource utilization efficiency; the normalization processing of weight values ​​and the application of priority calculation formulas enable the system to operate more stably when facing uncertainties in the production process, and reduce scheduling errors caused by improper weight settings.

[0076] In a specific embodiment, using these two rule configuration methods, decision makers can obtain existing priority rules through appropriate configuration, or they can customize special rules belonging to a certain scenario. When configuring rules, the discrete configuration method only needs to configure the corresponding task priorities of each delivery period to complete the configuration. When configuring rules, the continuous configuration method needs to configure the weight of the delivery period attribute and set other weight values ​​to 0. As long as the parameters of the discrete task priority configuration method are set properly, the fitting effect of each priority rule will be better. In theory, most of the existing priority rules can be fitted through the discrete priority configuration method. The advantage of the continuous configuration method is that the configuration is simple, and you only need to add relevant attributes and configure the corresponding weight values.

[0077] In addition, the electric power flexible manufacturing control method provided in this embodiment can also encapsulate the PT rules, EDD rules, Johnson rules, CDS rules, Palmer rules, LNS rules and FIFO rules into a priority rule system. Decision makers can select applicable rules in the system for production scheduling and even compile priority rules, which greatly improves the applicability of priority rules.

[0078] Further, in some embodiments, step S2 "generating an initial scheduling plan based on the production scheduling rule and the rule constraint condition by using the production scheduling algorithm" may specifically include:

[0079] S21. Converting the production scheduling rules and rule constraints into input parameters of the production scheduling algorithm;

[0080] S22. Calculate the task priority by using the scheduling algorithm based on the scheduling rules and attribute weight values;

[0081] S23. Generate an initial scheduling plan corresponding to the production scheduling task based on the task priority and rule constraints through the production scheduling algorithm.

[0082] Specifically, for the formulation of the scheduling plan in step S2, the scheduling rules and rule constraints are abstracted as input parameters of the scheduling algorithm to ensure that the algorithm can schedule tasks according to these conditions; the scheduling algorithm is used to calculate the task priority according to the scheduling rules and attribute weight values, which involves scoring the attributes of each task and determining the execution order of the tasks based on these scores; based on the task priority and rule constraints, the scheduling algorithm generates an initial scheduling plan corresponding to the scheduling task. This plan is the starting point of production scheduling and provides guidance for subsequent production activities, so that the scheduling task can be executed according to the initial scheduling plan.

[0083] Among them, the scheduling algorithm can use optimization techniques such as heuristics, meta-heuristics or hybrid algorithms to improve the efficiency and quality of the scheduling plan. The scheduling algorithm can consider multiple goals at the same time, such as minimizing production costs, maximizing equipment utilization, shortening production cycles, etc. The algorithm can integrate real-time data, such as production line status, inventory levels, order requirements, etc., to dynamically adjust the scheduling plan. In a specific embodiment, machine learning or deep learning technology can also be applied to enable the scheduling algorithm to learn from historical data and optimize the scheduling strategy.

[0084] This embodiment uses an automated production scheduling algorithm to quickly generate an initial scheduling plan that meets production needs and constraints, thereby improving the efficiency of the scheduling process; the production scheduling algorithm comprehensively considers multiple factors, and the generated scheduling plan can more effectively utilize resources and reduce waiting and idle time; the algorithm can adapt to changes in the production process, such as order changes, equipment failures, etc., and quickly adjust the scheduling plan to cope with these changes; through precise task priority calculation and scheduling plan generation, the utilization rate of equipment and materials is improved and waste is reduced; the algorithm supports complex multi-objective optimization, helping decision makers find the best balance between multiple goals; integrating real-time data and artificial intelligence technology enables the system to better predict and adapt to uncertainties in the production process and improve the robustness of the system.

[0085] Further, in some embodiments, step S3 “after detecting the disturbance information, adjusting the initial scheduling scheme based on the disturbance information to obtain an adjusted scheduling scheme” may specifically include:

[0086] S31. After detecting a disturbance in the flexible manufacturing system, generating disturbance information;

[0087] S32. Analyze the disturbance information to determine the disturbance type corresponding to the disturbance information;

[0088] S33. Adjust the initial scheduling plan based on the disturbance type to obtain an adjusted scheduling plan.

[0089] Specifically, for step S3, the system monitors and detects disturbance information that may affect the initial scheduling plan in real time, such as equipment failure, order change, progress delay, etc. When a disturbance occurs in the flexible manufacturing system, the scheduling system will determine the type of disturbance based on the on-site situation fed back by the programmable logic controller, and trigger the corresponding processing strategy based on different fault information, regenerate a scheduling plan that conforms to the current situation, and send it to the action planning layer for execution. When generating a new scheduling plan, it is necessary to follow the principle of changing the original production plan as little as possible to minimize the impact of the disturbance on the scheduling plan. By conducting an in-depth analysis of the detected disturbance information, the type, scope of influence and severity of the disturbance are determined. According to the analysis results of the disturbance information, the type of disturbance is determined, such as equipment failure disturbance, order change disturbance, progress abnormality disturbance, etc. Based on the type of disturbance, the initial scheduling plan is adjusted accordingly to adapt to changes in the production environment and ensure the continuity and efficiency of production.

[0090] Among them, in the specific implementation process, machine learning or pattern recognition technology can be used to automatically identify and classify disturbance information to improve response speed and accuracy. Develop a dynamic scheduling algorithm that can quickly respond to disturbances and adjust the scheduling plan in real time to minimize the impact of disturbances on production. Before adjusting the scheduling plan, use computer simulation technology to predict the impact of different adjustment strategies on production and select the optimal plan. It can also provide a user-friendly human-computer interaction interface so that operators can quickly understand disturbance information and adjustments to the scheduling plan, and perform necessary manual intervention. Integrate a predictive maintenance system to identify potential equipment failures in advance and reduce the occurrence of equipment failure-type disturbances.

[0091] This embodiment improves the adaptability of the production process to changes by quickly responding to disturbance information and adjusting the scheduling plan; timely adjusting the scheduling plan reduces production interruptions and delays caused by disturbances and improves production stability; reallocates resources according to the type of disturbance, optimizes resource utilization efficiency and reduces resource waste; the application of dynamic scheduling algorithms and multi-scenario simulation technology improves the quality of scheduling plans and ensures efficient production operation; integrates predictive maintenance and intelligent disturbance identification technology to enhance the system's ability to predict and respond to potential problems and improve the robustness of the system; human-computer interaction optimization and automated adjustment reduce the workload of operators and improve operational efficiency and response speed; by continuously monitoring disturbances and adjusting scheduling plans, the system can continuously learn and improve to support continuous optimization of the production process.

[0092] Further, in some embodiments, step S33 of “adjusting the initial scheduling scheme based on the disturbance type to obtain an adjusted scheduling scheme” may specifically include:

[0093] If the disturbance type is determined to be equipment failure, the faulty equipment will be locked, and alternative equipment with the same processing power as the faulty equipment will be queried. The process tasks of the faulty equipment will be transferred to the alternative equipment, and an adjusted scheduling plan will be generated.

[0094] If the disturbance type is determined to be an order change disturbance, the changed order is added to the production sequence to be scheduled based on its priority, or the changed order is deleted from the production sequence to be scheduled, the production sequence to be scheduled is readjusted, and an adjusted scheduling plan is generated.

[0095] Further, in some embodiments, step S33 of “adjusting the initial scheduling scheme based on the disturbance type to obtain an adjusted scheduling scheme” may specifically include:

[0096] If the disturbance type is determined to be a schedule abnormality disturbance, the corresponding deviation value is calculated based on the actual execution time and planned time of the production scheduling task;

[0097] When it is determined that the deviation value is greater than a preset threshold, the initial scheduling plan is adjusted based on the arrival time of the production resources or the change in the processing time to obtain an adjusted scheduling plan.

[0098] Specifically, by summarizing and classifying the common disturbances in flexible manufacturing systems, it can be seen that common disturbances mainly include equipment failure disturbances, abnormal progress disturbances, and order change disturbances. The process of disturbance processing is that when the scheduling system receives the feedback disturbance information, it will give priority to judging the type of disturbance. If the disturbance is an equipment failure disturbance or an order change disturbance, it will directly trigger the system to reschedule. If the disturbance is an abnormal progress disturbance, the rescheduling discrimination value of the disturbance will be calculated according to the rescheduling strategy. If the discrimination value does not exceed the set threshold, it is considered that the impact of the disturbance is small and no rescheduling is required. If the discrimination value exceeds the set threshold, it is considered that the impact of the disturbance is large and rescheduling is necessary. After rescheduling, the new scheduling plan obtained is sent to the action execution layer for execution, and this cycle is repeated until the plan is executed.

[0099] The following will analyze and handle the above three different types of disturbances. The first is the analysis and handling of equipment failure disturbances. Equipment failure anomalies include equipment failure, scheduled equipment maintenance, etc. Long-term shortages of certain equipment-related resources, such as tools and personnel, can also cause equipment failure disturbances. This type of disturbance is specifically manifested as the equipment being unavailable for a period of time. The difference is that scheduled equipment maintenance can generally predict the time when the disturbance will be restored, while equipment failure generally cannot determine the time when the disturbance will be restored. When handling disturbances, the processing procedures of these two situations are basically the same, except that the time of unlocking the equipment is different. When equipment on the production line fails, the process tasks originally scheduled on the faulty equipment cannot be executed. Therefore, when equipment failure occurs, the process tasks originally scheduled on the faulty equipment need to be processed. When an equipment failure occurs in the system, the scheduling system will lock the faulty equipment so that it no longer participates in the subsequent process task scheduling, and query the equipment with the same processing capacity as the faulty equipment, transfer the process tasks originally scheduled on the faulty equipment to the alternative equipment, and generate a new scheduling plan for delivery to the action planning layer for execution. After the equipment failure is eliminated, the lock state of the faulty equipment is released, and a new production scheduling plan is generated.

[0100] Then comes the analysis and processing of abnormal progress disturbances. There are many disturbances that cause abnormal processing progress, and the most common ones are resource shortages and changes in processing time. The start time of a process task cannot be earlier than the latest arrival time of the required resources, so resource shortages often cause the process task to fail to start at the planned time, resulting in abnormal progress. In addition, changes in processing time can cause the process task plan to fail to end at the planned time, which can also cause abnormal processing progress. The actual start time of the process task is constrained by the resource preparation time. Assuming that the processing of a process task requires three resources: personnel, tools, and materials, if the tooling is in place at time t1, the personnel are in place at time t2, and the tools are in place at time t3, then the earliest start time of the process task cannot be earlier than t3. When the system encounters a resource shortage disturbance that causes the process task to fail to start at the planned time, the scheduling system will calculate the new scheduling discrimination value based on the deviation between the actual execution and the plan. The deviation value is the difference between the actual start (end) time of the process task and the planned start (end) time. When this value exceeds the set threshold, it means that the deviation is large and rescheduling is required. At this time, the specific time when each resource is in place is obtained based on the feedback from the resource management system, and the current process tasks are rescheduled to obtain a new production schedule that meets the resource arrival time constraints. The impact of processing time changes on progress is mainly reflected in the end time of the process task. If the processing time becomes longer or shorter, it will cause the end time of the process task to lag or advance. Among them: the early end time of the process task will lead to a decrease in equipment utilization, but it will have little impact on the overall production schedule; the delay in the process task time will affect the start time of the next process task. If the delay time is long, it will have a greater impact on the production schedule and must be rescheduled.

[0101] Finally, the order change disturbance analysis and processing, order change disturbances include insertion orders, urgent orders and cancellation orders. When the system receives a new order, it assigns priority to the new task according to the priority rules configured by the system, and adds the process tasks in the new order to the sequence to be scheduled. The scheduling system will reschedule all the currently unprocessed process tasks to obtain a new scheduling plan. Urgent orders are a special case of insertion orders, which require the inserted orders to be completed as soon as possible. Therefore, when rescheduling, the scheduling system needs to ensure that the process tasks of urgent orders are given priority. The scheduling system sorts all process tasks based on priority rules. In order to ensure the processing of urgent orders, they should be given a higher priority. In fact, after receiving an order, the scheduling system will call the priority rules configured by the user to assign priority to the process tasks in the order. The process of canceling an order is relatively simple. When an order that has been scheduled but not executed is canceled, it is necessary to delete all the process tasks under the order in the task sequence to be scheduled, and then reschedule the remaining orders that meet the scheduling conditions.

[0102] This embodiment improves the efficiency and accuracy of production scheduling through an automated and intelligent scheduling method; the system and device can flexibly adapt to different production needs and changes, improving the adaptability of production scheduling; realizes real-time monitoring and response to production progress and disturbance information, reducing production interruptions and delays; improves resource utilization efficiency and reduces resource waste by optimizing resource allocation and scheduling plan adjustment; timely adjustment of scheduling plans reduces production losses caused by abnormal progress and disturbances, and ensures the smooth implementation of production plans; the system and device are highly robust, can predict and adapt to various changes in the production process, and ensure the continuity and stability of production; the design of the system and device supports continuous monitoring, analysis and optimization, and promotes continuous improvement and optimization of the production process.

[0103] This embodiment also provides a specific implementation method of the electric power flexible manufacturing control method, such as Figure 2As shown in the figure, first, the corresponding rules are configured according to the characteristics of the production line. According to these characteristics, the corresponding production scheduling rules and constraints are configured to provide a basis for the subsequent production scheduling algorithm. Then, the configured rules and constraints are used to generate the initial scheduling plan through the production scheduling algorithm. According to the generated initial scheduling plan, the production scheduling task is started, and the production process is monitored at the same time to ensure that the task is carried out according to the plan. Then, during the execution process, the system needs to continuously detect whether there are disturbances, such as equipment failure, order changes, and progress delays. These disturbances may affect the effectiveness of the scheduling plan. If a disturbance is detected, the system will enter the disturbance analysis and processing stage. The system will analyze the type and impact of the disturbance and determine the adjustment measures to be taken. This may include reallocating resources, adjusting task priorities, etc. According to the results of the disturbance analysis, the type of disturbance (such as equipment failure, order changes, abnormal progress, etc.) is determined, and the corresponding processing strategy is determined. According to the disturbance type and processing strategy, the initial scheduling plan is adjusted, and an updated scheduling plan is generated. The scheduling task is re-executed until the production scheduling task is completed. If there is no disturbance, the current scheduling plan continues to be executed until the production scheduling task is completed.

[0104] In summary, the electric power flexible manufacturing control method provided in this embodiment can quickly adapt to different production scenarios and demand changes through rule-configurable technology, and can ensure timely response and adjustment in the face of uncertainty in the production process through disturbance analysis and processing technology, thereby reducing the risk of production interruption. Through automated production scheduling and disturbance response mechanisms, the time and cost of human intervention are reduced, and the efficiency and accuracy of production scheduling are improved. It can be seen that this embodiment only needs to configure the corresponding parameters according to the characteristics of the production line to cope with scheduling scenarios with different characteristics, while analyzing and processing the disturbances of the flexible manufacturing system, making the scheduling method more robust.

[0105] In order to facilitate better implementation of the electric power flexible manufacturing control method of the embodiment of the present application, the embodiment of the present application also provides an electric power flexible manufacturing control device. The meanings of the terms are the same as those in the above-mentioned electric power flexible manufacturing control method, and the specific implementation details can refer to the description in the method embodiment.

[0106] See also Figure 3 , Figure 3 A schematic diagram of the structure of the electric power flexible manufacturing control device provided in an embodiment of the present application, wherein the electric power flexible manufacturing control device may specifically include a rule configuration module 201, a production scheduling module 202 and a disturbance processing module 203, which may be specifically as follows:

[0107] A rule configuration module 201, configured to configure corresponding production scheduling rules and rule constraints based on the characteristics of the target production line;

[0108] The production scheduling module 202 is used to generate an initial scheduling plan based on the production scheduling rules and rule constraints through the production scheduling algorithm, and start executing the production scheduling task based on the initial scheduling plan;

[0109] The disturbance processing module 203 is used to adjust the initial scheduling plan based on the disturbance information after the disturbance information is detected to obtain an adjusted scheduling plan, so as to continue to execute the production scheduling task based on the adjusted scheduling plan.

[0110] The electric power flexible manufacturing control device provided in this embodiment, through the rule configuration module 201, configures the corresponding production scheduling rules and rule constraints based on the characteristics of the target production line; through the production scheduling module 202, an initial scheduling plan is generated based on the production scheduling rules and rule constraints through the production scheduling algorithm, and the production scheduling task is started based on the initial scheduling plan; after the disturbance information is detected, the initial scheduling plan is adjusted based on the disturbance information through the disturbance processing module 203 to obtain the adjusted scheduling plan, so as to continue to execute the production scheduling task based on the adjusted scheduling plan. The electric power flexible manufacturing control device provided in this embodiment improves the robustness and applicability of the scheduling method through rule configuration and disturbance processing, and can quickly build and adjust the scheduling system according to the characteristics of the production line, so as to cope with scheduling scenarios with different characteristics, save time and labor costs, effectively improve the efficiency of production scheduling, and solve the problems of single, fixed and inflexible existing power manufacturing scenarios.

[0111] In addition, the present application also provides an electronic device, such as Figure 4 , which shows a schematic diagram of the structure of an electronic device involved in an embodiment of the present application. Specifically, the electronic device may include a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, a power supply 303, an input unit 304 and other components. Those skilled in the art can understand that Figure 4 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0112] The processor 301 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0113] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and power flexible manufacturing control methods by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0114] The electronic device also includes a power supply 303 for supplying power to each component. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 303 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0115] The electronic device may further include an input unit 304, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0116] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302, thereby realizing various functions, as follows:

[0117] Configure the corresponding production scheduling rules and rule constraints based on the characteristics of the target production line; generate an initial scheduling plan based on the production scheduling rules and rule constraints through the production scheduling algorithm, and start executing the production scheduling task based on the initial scheduling plan; after detecting the disturbance information, adjust the initial scheduling plan based on the disturbance information to obtain an adjusted scheduling plan, so as to continue executing the production scheduling task based on the adjusted scheduling plan.

[0118] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0119] The embodiments of the present application can quickly adapt to different production scenarios and demand changes through rule-configurable technology, and can ensure timely response and adjustment in the face of uncertainties in the production process through disturbance analysis and processing technology, thereby reducing the risk of production interruptions. Through automated production scheduling and disturbance response mechanisms, the time and cost of human intervention are reduced, thereby improving the efficiency and accuracy of production scheduling.

[0120] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0121] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any one of the electric power flexible manufacturing control methods provided in the embodiment of the present application. For example, the instructions can execute the following steps:

[0122] Configure the corresponding production scheduling rules and rule constraints based on the characteristics of the target production line; generate an initial scheduling plan based on the production scheduling rules and rule constraints through the production scheduling algorithm, and start executing the production scheduling task based on the initial scheduling plan; after detecting the disturbance information, adjust the initial scheduling plan based on the disturbance information to obtain an adjusted scheduling plan, so as to continue executing the production scheduling task based on the adjusted scheduling plan.

[0123] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0124] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. Since the instructions stored in the storage medium can execute the steps in any one of the electric power flexible manufacturing control methods provided in the embodiments of the present application, the beneficial effects that can be achieved by any one of the electric power flexible manufacturing control methods provided in the embodiments of the present application can be achieved. For details, please refer to the previous embodiments and will not be repeated here.

[0125] The above is a detailed introduction to an electric flexible manufacturing control method, device, electronic device and storage medium provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for controlling flexible manufacturing of electric power, It is characterized in that The steps include: Configure the corresponding production scheduling rules and rule constraints based on the characteristics of the target production line; Generate an initial scheduling plan based on the scheduling rules and the rule constraints through a scheduling algorithm, and start executing the scheduling task based on the initial scheduling plan; After the disturbance information is detected, the initial scheduling plan is adjusted based on the disturbance information to obtain an adjusted scheduling plan, so as to continue to execute the production scheduling task based on the adjusted scheduling plan.

2. The electric power flexible manufacturing control method according to claim 1, It is characterized in that The production scheduling rules and rule constraints corresponding to the characteristic configuration of the target production line include: If it is detected that the characteristics of the target production line meet the discrete task, various attributes that determine the priority are configured, and the task priority under the corresponding attribute is configured; If it is detected that the characteristics of the target production line meet the requirements of a continuous task, a weighted value is calculated based on the weight values ​​of each attribute, and the task priority is determined based on the weighted value.

3. The electric power flexible manufacturing control method according to claim 2, It is characterized in that The production scheduling rules and rule constraints corresponding to the characteristic configuration of the target production line also include: Define each attribute and its corresponding weight value that determines the priority according to the production scheduling rules; The weight value of each attribute is normalized.

4. The electric power flexible manufacturing control method according to claim 3, It is characterized in that The generating an initial scheduling scheme based on the scheduling rules and the rule constraints by the scheduling algorithm includes: Converting the production scheduling rules and the rule constraints into input parameters of the production scheduling algorithm; Calculating the task priority by the scheduling algorithm based on the scheduling rules and the weight values ​​of the attributes; The production scheduling algorithm generates an initial scheduling plan corresponding to the production scheduling task based on the task priority and the rule constraints.

5. The electric power flexible manufacturing control method according to claim 1, It is characterized in that After the disturbance information is detected, adjusting the initial scheduling scheme based on the disturbance information to obtain an adjusted scheduling scheme includes: After detecting a disturbance in the flexible manufacturing system, generating disturbance information; Analyze the disturbance information to determine the disturbance type corresponding to the disturbance information; The initial scheduling scheme is adjusted based on the disturbance type to obtain an adjusted scheduling scheme.

6. The electric power flexible manufacturing control method according to claim 5, It is characterized in that The adjusting the initial scheduling scheme based on the disturbance type to obtain an adjusted scheduling scheme includes: If the disturbance type is determined to be an equipment failure disturbance, the faulty equipment is locked, and alternative equipment with the same processing capacity as the faulty equipment is searched, the process tasks of the faulty equipment are transferred to the alternative equipment, and an adjusted scheduling plan is generated; If the disturbance type is determined to be an order change disturbance, the changed order is added to the production sequence to be scheduled based on its priority, or the changed order is deleted from the production sequence to be scheduled, the production sequence to be scheduled is readjusted, and an adjusted scheduling plan is generated.

7. The electric power flexible manufacturing control method according to claim 5, It is characterized in that The adjusting the initial scheduling scheme based on the disturbance type to obtain an adjusted scheduling scheme includes: If the disturbance type is determined to be a progress abnormality disturbance, the corresponding deviation value is calculated based on the actual execution time and the planned time of the production scheduling task; When it is determined that the deviation value is greater than a preset threshold, the initial scheduling plan is adjusted based on the arrival time or processing time change of the production resources to obtain an adjusted scheduling plan.

8. A flexible power manufacturing control device, It is characterized in that include: A rule configuration module is used to configure corresponding production scheduling rules and rule constraints based on the characteristics of the target production line; A production scheduling module, used to generate an initial scheduling plan based on the production scheduling rules and the rule constraints through a production scheduling algorithm, and start executing the production scheduling task based on the initial scheduling plan; The disturbance processing module is used to adjust the initial scheduling plan based on the disturbance information after detecting the disturbance information, so as to obtain an adjusted scheduling plan, so as to continue to execute the production scheduling task based on the adjusted scheduling plan.

9. An electronic device, It is characterized in that include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program according to the steps of the electric power flexible manufacturing control method as described in any one of claims 1 to 7.

10. A storage medium, It is characterized in that A computer program is stored which can be loaded by a processor and execute the electric power flexible manufacturing control method as described in any one of claims 1 to 7.

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