Order production control method and device, electronic equipment and storage medium

Abstract

According to the order production control method and device, the electronic equipment and the storage medium provided by the invention, the order information of the order, the process plan information of the order and the working center information of the working center are acquired, and the working center is used for producing products of the order; decomposing the order into a plurality of processes according to the process plan information, and determining the time required by each process of each order; calculating the earliest starting time of each process of each order according to the order information and the required time; and generating a production scheduling scheme based on the earliest start time and the work center information, and controlling the work center to work based on the production scheduling scheme to produce the order, so that the automation degree of order processing and production scheduling can be improved, and human errors and delay are reduced.

Description

Technical Field

[0001] The present application belongs to the technical field of production scheduling, and in particular, relates to a production control method, device, electronic device and storage medium for an order. Background Art

[0002] The current manufacturing industry is facing complex order processing and production scheduling issues. Traditional production scheduling methods usually rely on manual experience and conduct production scheduling based on orders. However, traditional production scheduling methods are difficult to efficiently handle a large number of orders and changing production demands, are inefficient, and are prone to waste of production resources, production delays, and other problems. Summary of the invention

[0003] The embodiments of the present application provide a production control method, device, electronic device and storage medium for an order, which can improve the degree of automation in order processing and production scheduling and reduce human errors and delays.

[0004] According to a first aspect of the present application, an embodiment of the present application provides a production control method for an order, comprising:

[0005] Acquire order information of an order, process plan information of the order, and work center information of a work center, where the work center is used to produce a product of the order, and the work center information at least includes information related to the production capacity of the work center;

[0006] Decomposing the order into multiple processes according to the process plan information, and determining the time required for each process of each order;

[0007] Calculate the earliest start time of each process of each order according to the order information and the required time;

[0008] Generate the production scheduling plan based on the earliest start time and the work center information;

[0009] The work center is controlled based on the production scheduling plan to produce the order.

[0010] In some embodiments, the work center information includes: idle time of the work center, and generating a scheduling solution based on the earliest start time and the work center information includes:

[0011] Sorting based on the earliest start time to obtain a first sorting result;

[0012] Optimizing the sorting of the first sorting result based on the time required for each process of each order from short to long, to obtain a second sorting result;

[0013] Selecting target processes in sequence from the second sorting results;

[0014] Based on the idle time of the work center corresponding to the target process and the earliest start time of the corresponding target process, the idle time of the work center is allocated to the corresponding target process to generate the production scheduling plan.

[0015] In some embodiments, the method further comprises:

[0016] By using a scheduling optimization algorithm, the production scheduling scheme is optimized to obtain an updated production time for each process;

[0017] A target scheduling solution is generated based on the updated production time.

[0018] In some embodiments, the optimizing the production scheduling scheme by a scheduling optimization algorithm includes:

[0019] Setting the initial temperature, cooling rate and maximum number of iterations, and calculating the total completion time of the production scheduling plan;

[0020] Randomly swapping the production times corresponding to two processes in the production scheduling plan, generating a new production scheduling plan, and calculating the total completion time of the new production scheduling plan;

[0021] Determine whether to accept the new production scheduling plan based on the total completion time of the production scheduling plan and the total completion time of the new production scheduling plan;

[0022] In case of accepting the new production schedule, calculating a new initial temperature based on the initial temperature and the cooling rate;

[0023] Perform iterative calculation based on the new initial temperature and the new production scheduling plan;

[0024] When the number of iterative calculations reaches the maximum number of iterations, or the calculated new initial temperature drops to a set threshold, the updated production time of each process is determined.

[0025] In some embodiments, the method further comprises:

[0026] Obtain the progress information of each process, the status information of each work center and the resource usage in real time;

[0027] The progress information, the status information and the resource usage are input into a production time adjustment model for adjusting the production time of unfinished processes, so as to adjust the production time of unfinished processes in the target scheduling scheme.

[0028] In some embodiments, the method further comprises:

[0029] Get the current process queue, current resource usage and the current status of each work center;

[0030] Based on the process queue, the current resource usage and the current state, the production bottleneck prediction model for predicting the production bottleneck is input to determine the production bottleneck information of each work center;

[0031] Based on the production bottleneck information of each work center, the production tasks of the work center are allocated and / or the production resource allocation is adjusted.

[0032] In some embodiments, the method further comprises:

[0033] Obtain raw material information and work status information of each work center;

[0034] Determine whether there is an abnormality based on the work status information of each work center, and determine whether there is a shortage of raw materials based on the raw material information;

[0035] In the case of abnormality of the work center and / or shortage of raw materials, at least one of the following operations is performed: generating an alternative production scheduling plan, and outputting notification information.

[0036] According to a second aspect of the present application, an embodiment of the present application provides an order production control device, including:

[0037] A first acquisition module is used to acquire order information of an order, process plan information of the order, and work center information of a work center, where the work center is used to produce the product of the order, and the work center information at least includes information related to the production capacity of the work center;

[0038] A first determination module, used to decompose the order into multiple processes according to the process plan information, and determine the time required for each process of each order;

[0039] A second determination module, configured to calculate the earliest start time of each process of each order according to the order information and the required time;

[0040] A generating module, configured to generate the production scheduling plan based on the earliest start time and the work center information;

[0041] A control module is used to control the work center based on the production scheduling plan to produce the order.

[0042] According to the third aspect of the present application, an embodiment of the present application 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 implements any of the methods described above when executing the computer program.

[0043] According to the fourth aspect of the present application, an embodiment of the present application provides an order production control system, characterized in that it includes: a work center and the electronic device mentioned above, and the work center is communicatively connected with the electronic device.

[0044] According to a fifth aspect of the present application, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the above is implemented.

[0045] According to the sixth aspect of the present application, an embodiment of the present application provides a computer program product, which, when executed on a terminal device, enables the electronic device to execute any of the methods described above.

[0046] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0047] The production control method for an order provided in an embodiment of the present application obtains order information of an order, process plan information of the order and work center information of a work center, wherein the work center is used to produce the product of the order; the order is decomposed into multiple processes according to the process plan information, and the required time for each process of each order is determined; the earliest start time of each process of each order is calculated according to the order information and the required time; a production scheduling plan is generated based on the earliest start time and the work center information, and the work of the work center is controlled based on the production scheduling plan to produce the order. In this way, the degree of automation of order processing and production scheduling can be improved, and human errors and delays can be reduced.

[0048] It can be understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 A schematic diagram of the implementation flow of a production control method for an order provided for the implementation of this application;

[0051] Figure 2 A flowchart of another order production control method provided in an embodiment of the present application;

[0052] Figure 3 A schematic diagram of the structure of a production control device for an order provided in an embodiment of the present application;

[0053] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0055] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0056] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0057] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0058] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appearing in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways.

[0059] Based on the technical problems of the related technology, the embodiment of the present application provides an order production control method that can be applied to electronic devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPC), netbooks, personal digital assistants (PDA), etc. The embodiment of the present application does not impose any restrictions on the specific types of electronic devices.

[0060] The functions implemented by the order production control method provided in the embodiment of the present application can be implemented by calling program codes by the processor of the electronic device, wherein the program codes can be stored in a computer storage medium.

[0061] The embodiment of the present application provides a production control method for an order, which realizes comprehensive optimization of production scheduling by integrating order information, process plan information of an order, and work center information of a work center. The electronic device automatically obtains and processes the order information, thereby improving the automation of order processing and production scheduling and reducing human errors and delays.

[0062] Figure 1 A schematic diagram of the implementation flow of a production control method for an order provided for the implementation of this application, such as Figure 1 As shown, the production control methods for orders include:

[0063] Step S101, acquiring order information of an order, process plan information of an order and work center information of a work center, where the work center is used to produce the product of the order, and the work center information at least includes information related to the production capacity of the work center.

[0064] According to the embodiment of the present application, production capacity includes the capacity of production equipment, available time, and other factors related to production capacity.

[0065] In the embodiment of the present application, the electronic device can obtain the order information of the order, the process plan information of the order, and the work center information of the work center in a variety of ways. As an example, the order is a current order to be produced, and the electronic device can communicate with the order management system to extract information directly related to the current order to be produced from the order management system.

[0066] In the embodiment of the present application, the order information includes the order number, order quantity, delivery time, customer priority, etc. The process plan information is a series of processing steps and process requirements required to complete the order product, for example, including the production process and steps for producing each product. The work center is a combination for producing the ordered product. The work center information includes the capacity, staffing, available time, maintenance plan, etc. of the production equipment of each work center.

[0067] In the embodiment of the present application, by collecting detailed order information, process plan information and work center information, basic data support can be provided for subsequent production scheduling, task allocation and resource management, thereby ensuring the feasibility and efficiency of production scheduling.

[0068] Step S102, decomposing the order into multiple processes according to the process plan information, and determining the time required for each process of each order.

[0069] In an embodiment of the present application, an order product includes multiple processes, and the electronic device can decompose the order into multiple specific processes based on the process list in the process plan information. Each process represents an independent processing or processing step, which is combined in a specific order to finally complete the production of the order product. As an example, the production process of a product may include multiple steps, such as cutting, assembly, inspection, etc. The electronic device can decompose the order into cutting, assembly, inspection, assembly, etc. based on the process list in the process plan information.

[0070] In an embodiment of the present application, the time required for each process is the required production time for each process. Among them, the required time can be determined based on historical data, equipment performance, personnel skill level, and process requirements, and the operator can enter the required time in the display interface of the electronic device, so that the electronic device can determine the required time for each process of each order. For the duration of the required time, as some examples, for common processes, the required time is standard time or standard working hours, for example, 3h, 6h, 9h, as some other examples, for new or special processes, the required time needs to be actually evaluated to determine the required time. Specifically, the required time can be determined by trial production, simulated operation, or expert evaluation.

[0071] Step S103, calculating the earliest start time of each process of each order according to the order information and the required time.

[0072] In an embodiment of the present application, the earliest start time of each process is reversely calculated based on the required time for each process of each order, as well as factors such as order priority and delivery time involved in the order information.

[0073] In an embodiment of the present application, the earliest start time of each process of the order can be reversely calculated starting from the delivery time of the order. For example, first, the start time of the production plan can be reversely calculated based on the delivery time of the order as the time of the front-end process, and the earliest completion time of the front-end process is added to the required time of the current process to obtain a candidate value for the earliest start time of the current process, where the current process is the next process of the front-end process. By analogy, the earliest start time of all subsequent processes can be obtained. For another example, the earliest start time of the terminal process can be obtained based on the delivery time of the order minus the required time of the terminal process, and then the earliest start time of the terminal process is added to the required time of the previous process to obtain a candidate value for the earliest start time of the previous process, and by analogy, the earliest start time of all processes can be obtained.

[0074] As an example, an order includes the first process, the second process, and the third process in sequence. First, the earliest start time of the first process can be determined according to the start time of the production plan, and the earliest completion time of the first process can be obtained by adding the required time of the first process. The earliest completion time of the first process can be added to the required time of the second process to obtain the candidate value of the earliest start time of the second process. Similarly, the earliest start time of the subsequent third process can be obtained.

[0075] It should be noted that when the earliest start time of a process is adjusted, the earliest start time of the following processes should also be adjusted, so that the accuracy of the generated scheduling plan can be guaranteed.

[0076] Step S104: generating the production scheduling plan based on the earliest start time and the work center information.

[0077] In an embodiment of the present application, first, the electronic device needs to collect the earliest start time (EST) of all relevant tasks, work center information (including the production capacity, available time, resource constraints, etc. of the equipment of the work center), and the dependencies between tasks. Secondly, determine the execution priority of the task according to the urgency, importance, or dependency of the task on other tasks. For example, based on the earliest start time and priority, sort the tasks to form a preliminary task execution sequence. Then, evaluate the capacity and available time of the work center to determine the type and number of tasks that each work center can handle. Assign tasks to appropriate work centers based on the requirements of the tasks and the capacity of the work center. Assign specific start and end times to each task on the work center to ensure that the task starts as soon as possible after the earliest start time and meets the resource constraints of the work center.

[0078] Step S105, controlling the work center to produce the order based on the production scheduling plan.

[0079] In the embodiment of the present application, after the production scheduling plan is determined, the tasks can be assigned to the appropriate work centers, so as to control the work centers and realize the production of orders.

[0080] The production control method for an order provided in an embodiment of the present application obtains order information of the order, process plan information of the order and work center information of the work center, where the work center is used to produce the product of the order; decomposes the order into multiple processes according to the process plan information, and determines the required time for each process of each order; calculates the earliest start time of each process of each order according to the order information and the required time; generates a production scheduling plan based on the earliest start time and the work center information, and controls the work of the work center based on the production scheduling plan to produce the order, thereby improving the degree of automation of order processing and production scheduling and reducing human errors and delays.

[0081] According to this application, the work center information specifically includes the idle time of the work center, and it is necessary to check whether the resources (such as equipment and manpower) of the work center are available at the earliest start time. If the resources of the work center are occupied by other processes, the earliest start time needs to be postponed to the next time point when the resources are available. In this way, the order between processes can be met and the availability of resources can be combined.

[0082] In some embodiments, the work center information includes the idle time of the work center. In step S104, a scheduling scheme is generated based on the earliest start time and the work center information, including:

[0083] Step S1041, sorting based on the earliest start time to obtain a first sorting result.

[0084] In this step, all processes are sorted from earliest to latest according to their earliest start time to obtain a preliminary sorting list, i.e. the first sorting result. In this way, it is possible to determine which processes should be prioritized for scheduling to ensure that production activities can start as early as possible and proceed smoothly.

[0085] Specifically, from the previous steps (such as step S103), we have obtained the earliest start time (EST) of each process of each order. Create a list (or a similar data structure) to store all processes and their corresponding earliest start times. Each process can be represented as an object or tuple containing information such as process ID, order, required time, and earliest start time. Use a sorting algorithm (such as quick sort, merge sort, heap sort, etc.) to sort the processes in the list. The basis for sorting is the earliest start time (EST) of the process. When sorting, ensure that the process with the earliest start time is at the front of the list, and the process with the latest start time is at the back of the list. After the sorting is completed, the first sorting result can be obtained.

[0086] Step S1042, optimizing the sorting in the first sorting result based on the time required for each process of each order from short to long, to obtain a second sorting result.

[0087] In this step, based on the first sorting result, for processes with the same or similar earliest start time, a second sorting is performed from short to long according to the time required for each process (i.e., production time) (i.e., the second sorting result). In this way, shorter processes will be arranged first, thereby optimizing the production process, reducing waiting time, and improving efficiency.

[0088] Specifically, first, the processes can be grouped according to the order ID, but this step is optional because the main focus is on the required time and the earliest start time of the processes, not which order they belong to. However, knowing the order to which the processes belong may be useful for subsequent resource allocation and conflict resolution. When performing sorting based on required time, the relative order between processes with the same EST in the first sorting result needs to be kept unchanged (i.e., stability is maintained). This usually means that we need to use a stable sorting algorithm or take additional measures during the sorting process to ensure this. Traverse the list of processes in the first sorting result. For processes with the same EST, sort them according to their required time (duration). The process with a shorter required time should be ranked first. If both the EST and the required time of two processes are the same, their relative order in the first sorting result can be maintained, or further sorted according to other criteria (such as process ID, order priority, etc.). After the above sorting process, we get a new list of processes, in which the processes are first sorted by EST, and for processes with the same EST, they are sorted by required time. This list is the second sorting result.

[0089] Step S1043, selecting target processes in sequence from the second sorting results.

[0090] In this step, the process list of the second sorting result is traversed in the sorted order. During the traversal process, each selected process is regarded as the current target process. For each target process, the system will perform a series of operations, such as allocating resources, setting start and end times, and updating production progress.

[0091] Step S1044, based on the idle time of the work center corresponding to the target process and the earliest start time of the corresponding target process, the idle time of the work center is allocated to the corresponding target process to generate the production scheduling plan.

[0092] In this step, after the target process (ie, the process to be selected from the second sorting result) has been determined, factors such as the idle time of the work center and the earliest start time (EST) of the target process also need to be considered.

[0093] Specifically, for each target process, the idle time of the corresponding work center (such as a machine tool, production line, etc.) needs to be determined. This usually involves querying the work center's schedule to find out which time periods are not occupied by other processes. Consider the earliest start time (EST) of the target process: The target process has an earliest start time, which is the earliest time that the process can start executing without violating any preconditions or resource constraints. When allocating the idle time of the work center, it is necessary to ensure that the allocated time is not earlier than this EST. Based on the idle time of the work center and the EST of the target process, an appropriate start time is assigned to the target process. This start time should be a point in the idle time of the work center and no earlier than the EST. If the work center has multiple consecutive idle time periods to choose from, other factors (such as resource utilization, dependencies between processes, etc.) may need to be considered to determine the best start time. Once the start time is assigned to the target process, the production schedule needs to be updated. This includes recording the start time, end time (calculated based on the start time and required time), and required resources of the process in the schedule. For each target process in the second sorting result, the above process is repeated until all processes are assigned specific execution times.

[0094] In these embodiments, through the above steps, an optimized scheduling scheme can be generated that takes into account both the earliest start time and the time required for the process and the idle time of the work center. Such a scheme helps to reduce waiting time, improve resource utilization, and ensure that orders can be delivered on time.

[0095] According to the present application, during the production control process of an order, the execution time of the process is adjusted to better meet production goals, such as minimizing the production cycle, maximizing resource utilization, or balancing workload.

[0096] In some embodiments, the order production control method further includes:

[0097] Step S106, optimizing the scheduling plan through a scheduling optimization algorithm to obtain an updated production time for each process.

[0098] In this step, the scheduling scheme is optimized to obtain the updated production time for each process, aiming to improve production efficiency, reduce resource conflicts and ensure on-time delivery of orders.

[0099] In this step, the electronic device can optimize the scheduling plan through an optimization algorithm to obtain an updated production time for each process. As an example, the optimization algorithm can be a genetic algorithm (GA), simulated annealing (SA), an ant colony algorithm (ACO), a local search algorithm (such as a greedy algorithm, a neighborhood search), or a machine learning algorithm.

[0100] In this step, after the optimization process is completed, each process will obtain an updated production time. The updated production time is the production time of each process output according to the above optimization algorithm.

[0101] Step S107, generating a target scheduling plan based on the updated production time.

[0102] In this step, the electronic device can generate a target schedule based on the updated production time. The target schedule is the final output of production scheduling, which guides the actual production process. The target schedule includes the execution order, start time, end time and required resources of each process. In addition, it may also include some additional information, such as the dependency between processes, resource allocation, and monitoring points of production progress.

[0103] In these embodiments, the production time of the process steps is adjusted to better meet production goals, such as minimizing the production cycle, maximizing resource utilization, or balancing workload, so as to further optimize and determine the final scheduling solution.

[0104] In some embodiments, in step S106, optimizing the scheduling scheme includes:

[0105] Step S1061, set the initial temperature, cooling rate and maximum number of iterations, and calculate the total completion time of the production scheduling plan.

[0106] In this step, the optimization process described is similar to the application of the simulated annealing algorithm (SA). The simulated annealing algorithm is a general probabilistic optimization algorithm used to find an approximate global optimal solution to a problem within a given large search space. The following is a detailed explanation of each sub-step:

[0107] In this step, the initial temperature is set, which determines the search range at the beginning of the algorithm. A higher temperature allows the algorithm to accept a worse solution, thereby increasing the possibility of jumping out of the local optimal solution. The cooling rate determines the speed at which the temperature decreases with the number of iterations, which affects the convergence speed and search accuracy of the algorithm. Maximum number of iterations: This is one of the conditions for the algorithm to stop iterating, ensuring that the algorithm ends in a reasonable time.

[0108] Calculate the total completion time of the production schedule: This is a measure of the performance of the current production schedule and is used for subsequent comparison with the new production schedule.

[0109] Step S1062, randomly swapping the production times corresponding to two processes in the production scheduling plan, generating a new production scheduling plan, and calculating the total completion time of the new production scheduling plan.

[0110] In this step, the production times corresponding to the two processes in the production scheduling plan are randomly swapped. This is the "disturbance" step in the simulated annealing algorithm, which generates new candidate solutions by randomly changing part of the solution.

[0111] In this step, the total completion time of the new production schedule is calculated, and the newly generated production schedule is evaluated to determine its performance.

[0112] Step S1063, determining whether to accept the new production scheduling plan based on the total completion time of the production scheduling plan and the total completion time of the new production scheduling plan.

[0113] In this step, whether to accept the new production schedule is determined based on the total completion time of the production schedule and the total completion time of the new production schedule. If the total completion time of the new production schedule is less than or equal to the total completion time of the current production schedule, the new production schedule is accepted unconditionally. If the total completion time of the new production schedule is longer, the Metropolis criterion (i.e., the probability calculated based on the current temperature and the energy difference between the two solutions) is used to decide whether to accept the new production schedule.

[0114] Step S1064, when accepting the new production scheduling plan, calculate a new initial temperature based on the initial temperature and the cooling rate.

[0115] In this step, if the new production schedule is accepted, the new initial temperature is calculated based on the initial temperature and the cooling rate: There may be a misunderstanding here, because usually we directly reduce the current temperature according to the cooling rate after each iteration instead of recalculating the initial temperature. But according to the description, if the new production schedule is accepted, it may mean adjusting the temperature reduction strategy in some way (although this is not a standard practice of the simulated annealing algorithm).

[0116] Step S1065, performing iterative calculation based on the new initial temperature and the new production scheduling plan.

[0117] In this step, iterative calculation is performed based on the new initial temperature (or updated temperature) and the new production scheduling plan: the loop of steps S1062 to S1064 is continued until the stop condition is met.

[0118] Step S1066, when the number of iterative calculations reaches the maximum number of iterations, or the calculated new initial temperature drops to a set threshold, determine the updated production time for each process.

[0119] In this step, when the number of iterative calculations reaches the maximum number of iterations, or the calculated new initial temperature (or current temperature) drops to the set threshold, the iteration is stopped and the updated production time of each process is determined. At this point, the current production schedule (i.e., the schedule accepted after the last iteration) is considered to be the optimized production schedule, and the production time of each process contained therein is the updated production time.

[0120] In these embodiments, the production time can be optimized through a preset algorithm for updating, thereby improving the efficiency of order processing and the degree of automation of production scheduling, and further improving the efficiency of production scheduling and resource utilization.

[0121] According to the present application, the order production control method also includes: a real-time monitoring and adjustment mechanism, which can further improve production efficiency and resource utilization.

[0122] In some embodiments, the order production control method further includes:

[0123] Step S108, obtaining the progress information of each process, the status information of each work center and the resource usage in real time.

[0124] In this step, electronic equipment can continuously monitor and collect key information in the production process, including but not limited to: progress information of each process, status information of each work center and resource usage.

[0125] In this step, the progress information of each process refers to the completion status of each process, such as the percentage completed, the remaining workload, the estimated completion time, etc. The status of the production equipment in each work center, such as busy, idle, maintenance, etc. Resource usage, where resources include manpower, raw materials, etc. Through the above, it is helpful to optimize resource allocation, coordinate the equipment of each work center, etc., reduce waste, and improve production efficiency.

[0126] Step S109, inputting the progress information, status information and resource usage into a production time adjustment model for adjusting the production time of unfinished processes, and adjusting the production time of unfinished processes in the target scheduling solution.

[0127] In this step, the progress information, status information and resource usage are input into the production time adjustment model used to adjust the production time of unfinished processes. This model is usually built based on complex algorithms and logic, and can comprehensively consider multiple factors, such as dependencies between processes, capacity constraints of work centers, availability of resources, etc., to generate optimal or suboptimal production scheduling solutions.

[0128] In this step, the progress information, status information and resource usage obtained in step S108 are used as input to provide real-time and accurate data support for the production time adjustment model. As an example, the production time adjustment model can be established based on, for example, a genetic algorithm, a simulated annealing algorithm, a particle swarm optimization algorithm, etc.

[0129] In this step, the production time adjustment model takes into account the production objectives (such as minimizing the production cycle, maximizing equipment utilization, balancing the load of each process, etc.) and constraints (such as equipment capacity limitations, dependencies between processes, resource availability, etc.) based on the input information, and performs intelligent analysis and calculation to evaluate the current production status and predict future development trends.

[0130] In this step, based on the results of the model calculation, the electronic equipment can automatically adjust the production time of the unfinished process in the target scheduling plan. This adjustment may be to advance, postpone or reallocate the process to different work centers to cope with emergencies and changes in production, ensure the smooth execution of the production plan, and optimize the overall production efficiency and resource utilization. In addition, the adjusted production time can ensure the feasibility and effectiveness of the production plan, while minimizing the impact of uncertain factors in the production process (such as equipment failure, raw material shortage, etc.) on the production plan.

[0131] In these embodiments, through this series of steps, the production scheduling plan can maintain a high degree of flexibility and adaptability, and respond to various changes in the production process in a timely manner, thereby improving production efficiency, reducing production costs, and enhancing the competitiveness of the enterprise.

[0132] According to the present application, the order production control method also includes production bottleneck prediction and work task allocation based on bottleneck information.

[0133] In some embodiments, the order production control method further includes:

[0134] Step S110, obtaining the current process queue, current resource usage and the current status of each work center.

[0135] In this step, the current process queue refers to a collection of processes to be processed or being processed, including information such as the priority of the process, the time required, and the resources required.

[0136] In this step, the current resource usage covers the current usage status, remaining quantity and predictable future demand of various production resources (such as equipment, manpower, raw materials, etc.).

[0137] In this step, the current status of each work center includes the work center's production capacity, load situation, maintenance status, whether other tasks are being processed, etc.

[0138] In this step, obtaining the current process queue, current resource usage and the current status of each work center can provide the necessary data support for subsequent bottleneck prediction and task allocation.

[0139] Step S111, based on the process queue, current resource usage and current status input into a production bottleneck prediction model for predicting production bottlenecks, the production bottleneck information of each work center is determined.

[0140] In this step, the production bottleneck prediction model is a model based on data analysis, machine learning or optimization algorithms to predict possible bottlenecks in the production process. Bottlenecks usually refer to key points that limit the improvement of overall production efficiency, such as insufficient resources, limited capacity work centers, etc.

[0141] In this step, the information collected in step S108 is input into the prediction model, and the model will calculate the bottlenecks that each work center may encounter in the future based on this information. The model will also output the production bottleneck information of each work center, including the bottleneck type (such as resource bottleneck, capacity bottleneck, etc.), bottleneck degree (such as expected waiting time, production capacity limit, etc.) and possible solutions.

[0142] Step S112: adjusting the production task allocation and / or production resource allocation of each work center based on the production bottleneck information of each work center.

[0143] In this step, the production tasks of each work center are reallocated or adjusted according to the results of the production bottleneck prediction model, so that the bottleneck can be alleviated or eliminated by optimizing the task allocation and improving the overall production efficiency. The allocation of production resources can also be adjusted based on the production bottleneck information.

[0144] In these embodiments, through the above steps, the enterprise can more accurately identify and solve the bottleneck problems in the production process, improve production efficiency and resource utilization, and thus enhance the competitiveness of the enterprise.

[0145] According to the present application, the method for determining the production scheduling plan also includes work center status monitoring, raw material shortage detection and abnormal notification mechanism, so as to ensure the smooth progress of the production process.

[0146] In some embodiments, the order production control method further includes:

[0147] Step S120, obtaining raw material information and work status information of each work center.

[0148] In this step, raw material information includes raw material inventory, in-transit quantity, quality status, usage rate, and estimated consumption time, etc. The working status information of each work center includes the operating status of the equipment (such as running, idle, faulty, and under maintenance), capacity utilization, staffing, and environmental parameters (such as temperature and humidity). This information can maintain the normal production and reflect the real-time capabilities and potential problems of the work center.

[0149] Step S130, determining whether there is an abnormality based on the work status information of each work center, and determining whether there is a shortage of raw materials based on the raw material information.

[0150] In this step, work center anomaly detection: By comparing the work center status information with the preset normal range or threshold, determine whether there is an anomaly. Anomalies may include equipment failure, insufficient production capacity, staff shortage, environmental problems, etc.

[0151] In this step, raw material shortage detection: Based on the inventory of raw materials and the expected consumption rate, calculate whether the raw materials can meet the current and future production needs. If the inventory is not enough to support production, it is considered a shortage of raw materials.

[0152] Step S140, when there is an abnormality in the work center and / or a shortage of raw materials, perform at least one of the following operations: generate an alternative production scheduling plan, and output notification information.

[0153] In this step, when an abnormality in a work center or a shortage of raw materials is detected, the electronic device will automatically generate a notification message. This information usually includes the specific content of the abnormality or shortage, the scope of impact, the degree of urgency, and the recommended response measures. Alternative production scheduling plans can also be generated.

[0154] In this step, the notification information is sent to the corresponding preset personnel according to the organizational structure and division of responsibilities of the enterprise. The preset personnel can be production supervisors, maintenance engineers, purchasing specialists, inventory managers, etc. They can take corresponding actions to solve the problem based on the notification information.

[0155] In these embodiments, through real-time monitoring and rapid notification mechanisms, enterprises can promptly discover and respond to problems and challenges in the production process, reducing downtime and production delays. Different departments and personnel can collaborate based on notification information to jointly solve production bottlenecks and obstacles and improve overall production efficiency. Based on the data and analysis results in the notification information, enterprises can optimize resource allocation, such as adjusting production plans, increasing raw material procurement, and deploying human resources to ensure the smooth progress of production activities. In this way, through the above steps, the flexibility and adaptability of the production scheduling plan are further enhanced, which helps enterprises better cope with complex and changing production environments.

[0156] Based on the above embodiments, by integrating order information, process plan information and work center information, it is possible to achieve comprehensive optimization of production scheduling, improve the automation of order processing and production scheduling, reduce human errors and delays, improve customer satisfaction and enhance corporate competitiveness.

[0157] By recursively decomposing orders and processes, complex production processes can be decomposed into simple procureable materials and processes, thereby improving the utilization efficiency of production resources and reducing production costs. Specifically, large orders can be decomposed into small orders, or complex products can be decomposed into simple components. This helps to reduce production difficulty and costs. Process decomposition: Each component or process is further decomposed until all materials are procureable. This helps to clarify each step and required resources in the production process. Based on the decomposition results, optimize the allocation and utilization of production resources. Reduce production costs by reducing unnecessary inventory and waiting time. Reduce delays and bottlenecks in the production process through precise planning and control to ensure smooth production.

[0158] By adopting the reverse scheduling method, the earliest start time of each process is calculated backwards from the order delivery time, which improves production efficiency and on-time delivery rate of orders, ensuring that products are delivered to customers on time. It can also optimize the production process and reduce waiting time and resource waste.

[0159] In summary, the above three methods are helpful to improve the efficiency and accuracy of production scheduling, optimize resource allocation, reduce production costs, and improve customer satisfaction and corporate competitiveness.

[0160] Figure 2 A flowchart of another order production control method provided in an embodiment of the present application includes the entire process from information collection to real-time monitoring and adjustment, such as Figure 2 As shown, the specific implementation method of the present invention is as follows:

[0161] 201. Information Collection:

[0162] Collect order information, including order quantity, delivery time, etc.

[0163] Collect process planning information, including the production flow and steps for each product.

[0164] Collect work center information, including the capacity of production equipment, available time, etc.

[0165] 202. Order and process breakdown:

[0166] According to the process plan, the order is broken down into specific processes. For example, the production process of a product may include multiple steps, such as cutting, assembly, inspection, etc.

[0167] For each process, if self-made materials are required, further decompose the processes of these self-made materials until all materials can be obtained through procurement.

[0168] The required production time of each process is determined through the external interface. The production time of the process is obtained through the external interface (mpm system), and the delivery time of the process refers to the earliest start time of the process plus the time required for the process production, which is used to determine the earliest start time of the next process. This should be calculated in the next step and has been changed.

[0169] 203. Earliest start time calculation:

[0170] Based on the delivery time of the order and the required production time of each process, the earliest start time of each process is calculated backwards. This calculation process usually starts from the delivery time and gradually calculates the start time of each process forward to ensure that all processes can be completed on time.

[0171] Consider the dependencies between processes and ensure that the predecessor process is completed before the successor process. In other words, the successor process can only start after the predecessor process is completed.

[0172] 204. Production scheduling optimization:

[0173] Preliminary Scheduling: Generates a preliminary schedule based on the earliest start time and processing time of the operations using a simple sorting and allocation algorithm.

[0174] Using the scheduling algorithm, all process information and work center information are input into the algorithm to generate a preliminary scheduling plan. Among them, the work center information includes the status and processing capacity of the work center. The status of the work center includes idle and occupied, and the processing capacity of the work center includes what processes can be performed; the process information mainly includes the production time and the earliest start time of the process.

[0175] The specific steps are as follows:

[0176] 1. Input: process information and work center information, including the processing time of each process.

[0177] 2. Initialization: Create an empty scheduling plan and set the initial idle time of all work centers to 0.

[0178] 3. Sorting: Sort by the earliest start time of the process, and then sort the processes by the processing time from short to long. If the earliest time is the same, sort by the process production time from short to long. This is mainly to reduce the waiting time of other tasks, because a long task may increase the waiting time of other tasks.

[0179] 4. Assign operations: Select the operations with the shortest processing time in turn. Find the earliest idle work center. Assign the operations to the work center and update the idle time of the work center.

[0180] 5. Output: Generated preliminary scheduling plan.

[0181] During the scheduling process, a preliminary allocation is first made based on the earliest start time of the process, ensuring that each process starts as soon as possible at or after the earliest start time.

[0182] The preliminary scheduling plan can also be optimized to form an optimized scheduling plan, arrange the specific production time of the process, and generate a detailed production plan.

[0183] The optimization scheme adopts the simulated annealing process, and the specific steps are as follows:

[0184] 1. Initialization: Starting from the initial scheduling plan, set the initial temperature to 1000, the cooling rate to 0.95, and the maximum number of iterations to 1000. The specific parameters are adjusted according to the actual situation to achieve better optimization results.

[0185] 2. Neighborhood search: Randomly swap the positions of two processes and recalculate a new scheduling plan.

[0186] 3. Evaluate the quality of the solution: Calculate the total completion time of the current schedule and the new schedule.

[0187] 4. Accept new solutions: Decide whether to accept new scheduling solutions based on the acceptance probability. The setting of the acceptance probability will affect the exploration and intensity of the algorithm in the search space. A higher acceptance probability may make the algorithm more likely to accept inferior solutions, making it easier to jump out of the local optimal solution, but this may also increase the time it takes for the algorithm to converge to the global optimal solution. On the contrary, a lower acceptance probability may make it more difficult for the algorithm to jump out of the local optimal solution, but may reduce the algorithm's search time.

[0188] According to the embodiment of the present application, the acceptance probability can be set and changed.

[0189] 5. Cooling: Gradually lower the temperature and eventually obtain an optimized scheduling plan.

[0190] 205. Real-time monitoring and adjustment:

[0191] During the production process, IoT devices and sensors are used to monitor the progress of each process, the status of the work center, and resource usage in real time.

[0192] Input real-time data into the scheduling system, and the system automatically updates and adjusts the production plan. The specific steps are as follows:

[0193] ① Monitor the actual start and end time of each process and compare it with the planned time.

[0194] ② If a process is delayed or completed ahead of schedule, recalculate the earliest start time of the subsequent processes and adjust the production time of the relevant processes.

[0195] ③ Based on historical data and current production conditions, predict potential production bottlenecks and resource conflicts and make adjustments in advance. The specific steps are as follows:

[0196] 1.1: Data collection and organization: Historical production data: including the processing time, start and end time, work center ID, process status, etc. of each process. Current production situation: including the current process queue, resource usage, work center status, etc.

[0197] 1.2: Use a simple rule engine to identify potential production bottlenecks, such as checking whether the work center is overloaded or whether the task is timed out.

[0198] 1.3: Collect analysis results and identify production bottlenecks.

[0199] 1.4: Automatically or semi-automatically adjust the production plan based on the analysis results. For example, for overloaded work centers, adjust task allocation and move some tasks to work centers with lighter loads; for overtime tasks, adjust resource allocation and add more manpower or equipment to ensure task completion.

[0200] In the dispatching system, an early warning mechanism is set up. When an abnormal situation occurs (such as equipment failure, shortage of raw materials, etc.), the system automatically generates alternative dispatching plans and notifies relevant personnel to handle them.

[0201] The order production control method provided in the embodiment of the present application enables enterprises to manage the production process more efficiently, ensure on-time delivery of orders, while reducing production costs and inventory pressure and improving overall competitiveness.

[0202] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0203] According to the aforementioned embodiments, the embodiments of the present application provide a production control device for an order, and the modules included in the device, as well as the units included in the modules, can be implemented by a processor in a computer device; of course, they can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU, Central Processing Unit), a microprocessor (MPU, Microprocessor Unit), a digital signal processor (DSP, Digital Signal Processing) or a field programmable gate array (FPGA, Field Programmable Gate Array), etc.

[0204] The embodiment of the present application provides a production control device for an order, Figure 3 A schematic diagram of the structure of a production control device for an order provided in an embodiment of the present application, such as Figure 3 As shown, the order production control device 400 is used to:

[0205] A first acquisition module 401 is used to acquire order information of an order, process plan information of the order, and work center information of a work center, where the work center is used to produce the product of the order, and the work center information at least includes information related to the production capacity of the work center;

[0206] A first determination module 402, configured to decompose the order into multiple processes according to the process plan information, and determine the time required for each process of each order;

[0207] A second determination module 403 is used to calculate the earliest start time of each process of each order according to the order information and the required time;

[0208] A generating module 404, configured to generate the production scheduling plan based on the earliest start time and the work center information;

[0209] The control module 405 is used to control the work center to produce the order based on the production scheduling plan.

[0210] In some embodiments, the work center information includes: idle time of the work center, and generating a production scheduling solution based on the earliest start time and the work center information includes:

[0211] Sorting based on the earliest start time to obtain a first sorting result;

[0212] Optimizing the sorting of the first sorting result based on the time required for each process of each order from short to long, to obtain a second sorting result;

[0213] Selecting target processes in sequence from the second sorting results;

[0214] Based on the idle time of the work center corresponding to the target process and the earliest start time of the corresponding target process, the idle time of the work center is allocated to the corresponding target process to generate the production scheduling plan.

[0215] In some embodiments, the order production control device 400 is used to:

[0216] By using a scheduling optimization algorithm, the production scheduling scheme is optimized to obtain an updated production time for each process;

[0217] A target scheduling solution is generated based on the updated production time.

[0218] In some embodiments, the optimizing the production scheduling scheme by a scheduling optimization algorithm includes:

[0219] Setting the initial temperature, cooling rate and maximum number of iterations, and calculating the total completion time of the production scheduling plan;

[0220] Randomly swapping the production times corresponding to two processes in the production scheduling plan, generating a new production scheduling plan, and calculating the total completion time of the new production scheduling plan;

[0221] Determine whether to accept the new production scheduling plan based on the total completion time of the production scheduling plan and the total completion time of the new production scheduling plan;

[0222] In case of accepting the new production schedule, calculating a new initial temperature based on the initial temperature and the cooling rate;

[0223] Perform iterative calculation based on the new initial temperature and the new scheduling scheme;

[0224] When the number of iterative calculations reaches the maximum number of iterations, or the calculated new initial temperature drops to a set threshold, the updated production time of each process is determined.

[0225] In some embodiments, the order production control device 400 is further used to:

[0226] Obtain the progress information of each process, the status information of each work center and the resource usage in real time;

[0227] The progress information, the status information and the resource usage are input into a production time adjustment model for adjusting the production time of unfinished processes, so as to adjust the production time of unfinished processes in the target scheduling scheme.

[0228] In some embodiments, the order production control device 400 is further used to:

[0229] Get the current process queue, current resource usage and the current status of each work center;

[0230] Based on the process queue, the current resource usage and the current state, the production bottleneck prediction model for predicting the production bottleneck is input to determine the production bottleneck information of each work center;

[0231] Based on the production bottleneck information of each work center, adjust the production task allocation and / or production resource allocation of the work center.

[0232] In some embodiments, the order production control device 400 is further used to:

[0233] Obtain raw material information and work status information of each work center;

[0234] Determine whether there is an abnormality based on the work status information of each work center, and determine whether there is a shortage of raw materials based on the raw material information;

[0235] In the case of abnormality of the work center and / or shortage of raw materials, at least one of the following operations is performed: generating an alternative production scheduling plan, and outputting notification information.

[0236] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0237] in addition, Figure 3 The production control device for the order shown may be a software unit, a hardware unit, or a combination of software and hardware units built into an existing electronic device, or may be integrated into the electronic device as an independent pendant, or may exist as an independent terminal device.

[0238] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0239] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 4 As shown, the electronic device 3 of this embodiment may include: at least one processor 30 ( Figure 4 Only one processor 30 is shown in the figure), a memory 31, and a computer program 32 stored in the memory 31 and executable on at least one processor 30. When the processor 30 executes the computer program 32, the steps in any of the above-mentioned method embodiments are implemented. For example, Figure 1 Steps S101 to S104 in the illustrated embodiment. Alternatively, when the processor 30 executes the computer program 32, the functions of each module / unit in the above-mentioned device embodiments are realized, for example Figure 3 Functions of modules 401 to 404 are shown.

[0240] Exemplarily, the computer program 32 may be divided into one or more modules / units, one or more modules / units are stored in the memory 31, and are executed by the processor 30 to complete the present application. One or more modules / units may be a series of computer program 32 instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 32 in the electronic device 3.

[0241] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program 32. When the computer program 32 is executed by the processor 30, the steps in the above-mentioned method embodiments can be implemented.

[0242] An embodiment of the present application also provides an order production control system, characterized in that it includes: a work center and the electronic device mentioned above, and the work center is communicatively connected with the electronic device.

[0243] An embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0244] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. According to this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program 32, and the computer program 32 can be stored in a computer-readable storage medium, and the computer program 32 can implement the steps of the above-mentioned various method embodiments when executed by the processor 30. Among them, the computer program 32 includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the terminal, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0245] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0246] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0247] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0248] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0249] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A production control method for an order, characterized in that: include: Acquire order information of an order, process plan information of the order, and work center information of a work center, where the work center is used to produce a product of the order, and the work center information at least includes information related to the production capacity of the work center; Decomposing the order into multiple processes according to the process plan information, and determining the time required for each process of each order; Calculate the earliest start time of each process of each order according to the order information and the required time; Generate the production scheduling plan based on the earliest start time and the work center information; The work center is controlled based on the production scheduling plan to produce the order.

2. The method according to claim 1, characterized in that The work center information includes: the idle time of the work center, The generating the production scheduling scheme based on the earliest start time and the work center information comprises: Sorting based on the earliest start time to obtain a first sorting result; Optimizing the sorting of the first sorting result based on the time required for each process of each order from short to long, to obtain a second sorting result; Selecting target processes in sequence from the second sorting results; Based on the idle time of the work center corresponding to the target process and the earliest start time of the corresponding target process, the idle time of the work center is allocated to the corresponding target process to generate the production scheduling plan.

3. The method according to claim 2, characterized in that The method further comprises: By using a scheduling optimization algorithm, the production scheduling scheme is optimized to obtain an updated production time for each process; A target scheduling solution is generated based on the updated production time.

4. The method according to claim 3, characterized in that The step of optimizing the production scheduling scheme by using a scheduling optimization algorithm includes: Setting the initial temperature, cooling rate and maximum number of iterations, and calculating the total completion time of the production scheduling plan; Randomly swapping the production times corresponding to two processes in the production scheduling plan, generating a new production scheduling plan, and calculating the total completion time of the new production scheduling plan; Determine whether to accept the new production scheduling plan based on the total completion time of the production scheduling plan and the total completion time of the new production scheduling plan; In case of accepting the new production schedule, calculating a new initial temperature based on the initial temperature and the cooling rate; Perform iterative calculation based on the new initial temperature and the new scheduling scheme; When the number of iterative calculations reaches the maximum number of iterations, or the new initial temperature drops to a set threshold, an updated production time for each process is obtained.

5. The method according to claim 3, characterized in that: The method further comprises: Obtain progress information of each process, status information of each work center and resource usage; The progress information, the status information and the resource usage are input into a production time adjustment model for adjusting the production time of unfinished processes, so as to adjust the production time of unfinished processes in the target scheduling scheme.

6. The method according to any one of claims 1 to 5, characterized in that: The method also includes: Get the current process queue, current resource usage and the current status of each work center; Based on the process queue, the current resource usage and the current state, input into a production bottleneck prediction model for predicting production bottlenecks, and determine the production bottleneck information of each work center; Based on the production bottleneck information of each work center, adjust the production task allocation and / or production resource allocation of the work center.

7. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Obtain raw material information and work status information of each work center; Determine whether there is an abnormality based on the work status information of each work center, and determine whether there is a shortage of raw materials based on the raw material information; In the case of abnormality of the work center and / or shortage of raw materials, at least one of the following operations is performed: generating an alternative production scheduling plan, and outputting notification information.

8. A production control device for an order, characterized in that: include: A first acquisition module is used to acquire order information of an order, process plan information of the order, and work center information of a work center, where the work center is used to produce the product of the order, and the work center information at least includes information related to the production capacity of the work center; A first determination module, used to decompose the order into multiple processes according to the process plan information, and determine the time required for each process of each order; A second determination module, configured to calculate the earliest start time of each process of each order according to the order information and the required time; A generating module, configured to generate the production scheduling plan based on the earliest start time and the work center information; A control module is used to control the work center based on the production scheduling plan to produce the order.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. An order production control system, characterized in that: It comprises: a work center and the electronic device according to claim 9, wherein the work center is communicatively connected with the electronic device.

11. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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