Production scheduling method and apparatus based on MTO production mode, and computing device

Abstract

The invention relates to the field of management science and engineering, in particular to a production scheduling method and device based on an MTO production mode and computing equipment. The method comprises the following steps: acquiring real-time production data; inputting the production data into a pre-constructed product information model, and generating configurable BOM and process route data; generating a workshop-level work order based on the configurable BOM and the process route data; and when it is determined that the workshop-level work order meets the putting condition through an ORR mechanism, workshop production scheduling operation is carried out. According to the method, efficient, accurate and flexible production scheduling from order parameters to workshop plans in an MTO mode is realized through technical means such as automatic order generation of product configuration, ORR flow control delivery, dynamic priority ranking and local rearrangement, and the resource utilization rate and delivery reliability are remarkably improved.

Description

A scheduling method, apparatus, and computing equipment based on MTO production mode Technical Field

[0001] This application relates to the field of management science and engineering, and in particular to a scheduling method, apparatus and computing equipment based on the MTO production model. Background Technology

[0002] Valve manufacturers generally face challenges such as highly customized products, complex process routes, limited equipment and tooling resources, and poor material availability.

[0003] Traditional production scheduling methods primarily rely on ERP / MRP systems, manual scheduling in Excel, or limited APS tools, lacking the ability to dynamically adjust order priorities, respond to order insertions, identify capacity bottlenecks, and optimize multi-resource collaboration. This leads to frequent problems in actual production, such as unfeasible plans, uneven equipment load, delivery delays, and work-in-process accumulation, severely impacting delivery efficiency and cost control. Especially when facing urgent order insertions or order changes, existing methods struggle to quickly reschedule, causing production chaos.

[0004] Therefore, there is an urgent need for a production scheduling solution based on the MTO (Manufacturing to Order) production model to support valve manufacturing companies in precise, flexible, and efficient production scheduling under complex MTO scenarios. Summary of the Invention

[0005] Therefore, it is necessary to provide a production scheduling solution based on the MTO production model to address the problems of traditional scheduling methods being difficult to execute stably and efficiently in complex MTO (Manufacturing to Order) discrete manufacturing scenarios with multiple varieties, small batches, and high customization, due to complex processes, numerous resource constraints, and frequent dynamic changes in orders. This solution includes: acquiring real-time production data; inputting the production data into a pre-built product information model to generate a configurable BOM and process route data; generating workshop-level work orders based on the configurable BOM and process route data; and performing workshop scheduling operations when the workshop-level work orders meet the deployment conditions through an ORR (Order of Return) mechanism.

[0006] Preferably, the product information model includes: a configurable BOM structure module, used to determine a BOM template and generate a preliminary material structure based on preset rules after inputting order parameters; a material feature value differentiation module, used to match material codes with feature values ​​corresponding to the material requirements in the material library according to the material requirements in the preliminary material structure; an attribute group division module, used to call the corresponding process route template and generate detailed process route data according to the material code and its associated characteristics; and a work order output module, used to generate workshop-level work orders and output the corresponding workshop teams according to the material codes and the process route data.

[0007] Preferably, the step of determining that the workshop-level work order meets the deployment conditions through the ORR mechanism includes: obtaining the current workshop equipment load data, work-in-process quantity, and bottleneck resource occupancy rate; determining, based on preset load threshold rules, whether the available time of the equipment on which the target process depends in a future preset time window is greater than or equal to the standard processing time of the workshop-level work order; and verifying that the special tooling fixtures required by the workshop-level work order are in a non-maintenance and unoccupied state in the time window; if both the equipment and the fixtures meet the availability conditions, then the workshop-level work order is determined to meet the deployment conditions.

[0008] Preferably, upon receiving a disturbance event signal, the process further includes: traversing the affected workshop-level work orders and their subsequent process dependency chains, and identifying related work orders that share the same equipment or special fixtures based on the equipment type and special fixture identifier recorded in each work order; freezing work orders that have already started or whose planned start time is less than a preset freeze window; and for affected work orders that are not frozen, partially reallocating equipment, special tooling fixtures, and time windows, and updating the corresponding local production scheduling segments.

[0009] Preferably, the partial reallocation of equipment, special tooling fixtures, and time windows for unfrozen affected work orders includes: extracting the required equipment type, special tooling fixture identifier, and standard processing time for each work order from the unfrozen affected work orders; traversing the available machines in the current workshop that meet the equipment type, as well as special tooling fixtures that are in a non-maintenance state and not occupied by frozen work orders, to form a candidate resource set; searching for time windows that meet the time conditions in the candidate resource set for each work order based on the process sequence dependency; and updating if at least one combination of machine, special tooling fixture, and time window exists.

[0010] Preferably, the method further includes sorting workshop-level work orders based on a dynamic priority index, wherein the dynamic priority index satisfies: priority index = α·product priority + β·product standard cycle + γ·critical rate + δ·completeness rate; where α, β, γ, and δ are configurable weight parameters, and α+β+γ+δ=1; the product priority is the ratio of the difference between the order delivery date and the current time to the standard processing time; when multiple work orders share the same equipment or special tooling fixtures, resources are preferentially allocated to work orders with higher priority indices; when order delivery dates change, resource conflicts occur, or production anomalies occur, the priority index of the affected work orders is recalculated and the production schedule is updated.

[0011] Preferably, the real-time production data includes: dynamic order data, process routes, manufacturing resource data, production status data, and constraint rule sets.

[0012] The second aspect of this application provides a production scheduling system based on the MTO (Manufacturing Execution) production mode, comprising: a data acquisition unit for acquiring real-time production data, including order parameters, equipment load data, work-in-process status, and disturbance event signals; a product configuration engine coupled with a pre-built product information model for generating a configurable BOM and process route data based on the order parameters; a work order generation unit for generating workshop-level work orders based on the configurable BOM and process route data; an ORR (Order of Responsibility) control unit for determining whether the workshop-level work orders meet the deployment conditions based on equipment availability, special tooling fixture status, and dynamic priority index; a dynamic rescheduling unit for freezing protected work orders and partially reallocating equipment, special tooling fixtures, and time windows for unfrozen affected work orders upon receiving a disturbance event signal; a production scheduling output unit for outputting an updated workshop operation scheduling plan; and a shift scheduling unit for assigning tasks to corresponding workshop shifts according to the workshop operation scheduling plan.

[0013] Preferably, the ORR control unit includes a priority calculation subunit, used to calculate the dynamic priority index of each workshop-level work order according to the formula: Priority Index = α·Product Priority + β·Customer Value Level + γ·Criticality Rate + δ·Completeness Rate; where α, β, γ, and δ are configurable weight parameters and their sum is 1; a resource verification subunit, used to verify whether the available time of the equipment on which the target process depends in the future preset time window is not less than the standard processing time, and to confirm that the required special tooling fixture is in a non-maintenance and unoccupied state; and a sorting and placement subunit, used to sort multiple workshop-level work orders in descending order according to the dynamic priority index when multiple work orders compete for the same equipment or special tooling fixture, and to release high-priority work orders to the scheduling engine first.

[0014] A third aspect of this application provides a computing device, including: a processor, and a memory connected to the processor and storing program instructions, which, when executed by the processor, cause the processor to perform the scheduling method based on the MTO production mode as described above.

[0015] This application constructs an MTO (Manufacturing Execution to Order) scheduling technology system that integrates product configuration-driven production, ORR (Order of Return) load control, dynamic priority allocation, and local incremental rearrangement. This system achieves automatic conversion from customer-selected parameters to executable workshop plans. It utilizes a configurable BOM (Bill of Materials) and feature value matching to accurately generate work orders. The ORR mechanism, combined with equipment / fixture availability and dynamic priority indices, controls the work order delivery pace. In the event of disturbances, only unfrozen work orders undergo local resource reallocation. This solution effectively addresses pain points in customized valve production, such as low efficiency of manual BOM maintenance, frequent resource conflicts, and rigid and difficult-to-adjust plans. It significantly improves scheduling accuracy, equipment and dedicated tooling utilization, and ensures the reliability of high-priority order delivery. Attached Figure Description

[0016] Figure 1 is a flowchart illustrating the production scheduling method based on the MTO production mode provided in an embodiment of this application.

[0017] Figure 2 is a flowchart of the production scheduling method based on the MTO production mode provided in the embodiments of this application.

[0018] Figure 3 is a schematic diagram of the production scheduling system 300 based on the MTO production mode provided in the embodiment of this application.

[0019] Figure 4 is a structural schematic diagram of the ORR control unit 304 provided in an embodiment of this application.

[0020] Figure 5 is a structural schematic diagram of a computing device 900 provided in an embodiment of this application. Detailed Implementation

[0021] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings. Preferred embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0022] It should be noted that when an element is referred to as being "set on" another element, it can be directly on the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," "top," "bottom," "end," "top," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0023] Workload control (WLC) technology is suitable for make-to-order production.

[0024] Order Reviews and Release (ORR) is an implementation method of Work Controller (WLC). ORR technology is used in WLC systems to determine, guided by WLC theory, which tasks must be released and when to release these selected tasks.

[0025] A Bill of Materials (BOM) is a structured list that describes the raw materials, parts, components, assemblies, and quantities that make up a product.

[0026] The Master Production Schedule (MPS) is a component of a closed-loop planning system. It coordinates sales planning and production resources to formulate an independent demand plan for the final product production quantity and delivery date within a specific time period.

[0027] Material Requirements Planning (MRP) is a material planning and management model used in industrial manufacturing enterprises. It involves planning each item as the planning object based on its subordinate and quantity relationships at each level of the product structure, using the completion date as the time base, and prioritizing the release of plans for each item according to the length of its lead time.

[0028] Just-in-Time (JIT) production is also known as stockless production, zero inventories, one-piece flow, or supermarket production.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0030] The production scheduling scheme based on the MTO production mode provided in this application will be described below with reference to embodiments. Please refer to Figures 1 and 2. Figure 1 is a schematic flowchart of the production scheduling method based on the MTO production mode provided in an embodiment of this application. Figure 2 is a flowchart of the production scheduling method based on the MTO production mode provided in an embodiment of this application.

[0031] As shown in Figure 1, the production scheduling method based on the MTO production mode provided in this application includes the following steps.

[0032] S101: Obtain real-time production data.

[0033] Real-time production data includes, but is not limited to, dynamic order data, process routes, manufacturing resource data, production status data, and constraint rule sets. The system receives customer sales orders (dynamic order data) and extracts structured optional items such as order configuration parameters, valve diameter, pressure rating, material type, connection method, drive type, and sealing requirements; as well as current equipment status, work-in-process queue, and fixture maintenance plan.

[0034] S102: Input the production data into the pre-built product information model to generate configurable BOM and process route data.

[0035] The configuration parameters from real-time production data are input into a pre-built product information model. This product information model includes a configurable BOM rule base, a feature value mapping table, and a process template base. Based on the input parameters, it automatically matches and outputs the corresponding configurable BOM, which includes a list of required raw materials, standard parts, and self-made parts. It also includes the process route bound to the BOM, which includes the process sequence, standard working hours for each process, required equipment types, special tooling and fixture requirements, and personnel skill levels.

[0036] In this embodiment, after inputting production data, the order parameters are parsed, the configurable BOM rule base is traversed, a template that meets all conditions is found, and the corresponding configurable BOM is instantiated and output. Based on the structure module of this configurable BOM, the BOM template can be matched according to the order parameters. This solves the problem that, under the highly customized nature of valves, a BOM needs to be created for each order, which is inefficient, difficult to reuse, and prone to mismatch due to reliance on experience in material selection.

[0037] Furthermore, the product information model may include a configurable BOM structure module, used to determine the BOM template and generate a preliminary material structure based on preset rules after order parameters are input. The preliminary material structure may include a template ID, configuration condition expressions, and a list of sub-items (general material placeholders, such as {valve body}, {bolt}), etc.

[0038] The material feature value differentiation module is used to match material codes with corresponding feature values ​​from the material library based on the material requirements in the preliminary material structure. This module may include a material master data table, where each record may contain: a material code (e.g., B-2100), and feature value fields (e.g., material=WCB, applicable DN=100, surface treatment=shot peening). For each general placeholder in the BOM, the module extracts its required features and then performs a query to match the corresponding material code. The matched code can then be returned.

[0039] The attribute grouping module is used to generate detailed process route data by calling the corresponding process route template based on the material code and its associated characteristics. Material attributes can be stored in basic attribute groups, production attribute groups, default process ID lists, standard working hours, equipment types, fixture identifiers, etc. Basic attribute groups can include codes, names, and units; production attribute groups can include default process ID lists, standard working hours, equipment types, and fixture identifiers. During processing, the module reads the matching material's "production attribute group" based on the material code and its associated characteristics, calls the process route template library (e.g., "a certain valve body processing route"), and generates a process sequence.

[0040] The product information model also includes a work order output module, which is used to generate and output workshop-level work orders based on the material codes and process route data.

[0041] S103: Generate workshop-level work orders based on the configurable BOM and the process route data.

[0042] Based on the work order output module, workshop-level work orders are generated and output according to the material code and the process route data. Each workshop-level work order contains at least one specific operation and may include the following attributes: operation number, operation name, required processing equipment type, required special tooling fixture identifier, standard processing time, required complete set of materials list (from BOM decomposition), order ID, and delivery date, etc.

[0043] In some implementations, all generated workshop-level work orders are not immediately scheduled for production, but are instead temporarily stored in an order pool, awaiting a deployment decision. In this case, the order pool acts as a buffer, aggregating all workshop-level work orders that are awaiting production but have not yet been released.

[0044] In this embodiment, after inputting customer selection parameters, the configurable BOM structure module filters applicable BOM templates according to rules to generate a preliminary material structure. The material feature value differentiation module accurately matches specific material codes from the material library based on the material requirements in the structure and parameters (such as DN and material). The attribute group division module reads the production attribute groups of the selected materials and automatically extracts the corresponding processes, equipment, fixtures, and other information to form a complete process route. Finally, a customized bill of materials (MBOM) and bound process route are output, realizing one-click conversion from customer configuration to shop floor tasks. Without manual intervention, the system can automatically, accurately, and efficiently map any legal customer selection combination into executable manufacturing instructions.

[0045] S104: When the ORR mechanism determines that the workshop-level work order meets the deployment conditions, workshop production scheduling is performed.

[0046] In this application, the ORR mechanism based on the WLC (Workload Control) strategy determines whether the deployment conditions are met; if they are met, a portion of workshop-level work orders are selected from the order pool and released, entering the scheduling stage.

[0047] Furthermore, determining that the workshop-level work order meets the release conditions through the ORR mechanism includes: acquiring current workshop data, including equipment load data, work-in-process quantity, and bottleneck resource occupancy rate. Based on the ORR (Order Review and Release) mechanism, the backlog of current workshop-level work orders in the order pool and the actual operating status of the workshop, including equipment utilization rate, work-in-process quantity, and bottleneck resource occupancy rate, are periodically or event-triggered.

[0048] Based on preset load threshold rules, for example, it is determined whether the available time of the equipment on which the target process depends in the future preset time window is greater than or equal to the standard processing time of the workshop-level work order; at the same time, it is verified that the special tooling fixture required by the workshop-level work order is in a non-maintenance and unoccupied state in the time window; if the equipment and the fixture both meet the availability conditions, it is determined that the workshop-level work order meets the deployment conditions.

[0049] The calculation process involves determining the available window for the target equipment. For example, for work order W-1001 (requires a CNC lathe, 120 minutes of operation), the idle time periods of CNC-01 to CNC-05 are scanned. If CNC-03 has a continuous idle period of a certain duration in T+2h, it is considered a candidate. Fixture availability is verified, for example, by querying fixture JG-ZF100: whether it is in an "available" state (not under maintenance, not occupied by other non-frozen work orders) in [T+2h, T+4h]. A comprehensive judgment is made: only when both the equipment and the fixture meet the requirements is the work order marked as "available for deployment".

[0050] Furthermore, it also includes sorting workshop-level work orders based on a dynamic priority index, wherein the dynamic priority index satisfies: priority index = α·product priority + β·product standard cycle + γ·criticality rate + δ·completeness rate; where α, β, γ, and δ are configurable weight parameters, and α+β+γ+δ=1; wherein, product priority usually reflects the strategic or commercial importance of the order / product, and is usually preset by the enterprise based on customer level, contract terms, profit contribution, or whether it is a model project, etc.

[0051] The standard cycle of a product refers to the total standard processing time required for the product from material input to completion. It is derived by adding up the standard working hours of each process in the process route and reflects the complexity of the process and the difficulty of manufacturing.

[0052] Critical rate = Remaining lead time / Remaining standard processing time, Remaining lead time = Order lead time – Current time, Remaining standard processing time = Total standard processing time of unfinished processes.

[0053] The availability rate refers to the degree to which all materials required for a work order are available. It is usually expressed as a percentage: Availability rate = (Total number of required material items / Number of critical material items that have arrived) × 100%, or it can be determined by whether materials on the critical path (such as castings and forgings) have arrived.

[0054] When multiple work orders share the same equipment or special tooling fixtures, resources are allocated to work orders with higher priority indices. When order delivery dates change, resource conflicts occur, or production anomalies occur, the priority indices of the affected work orders are recalculated and the production schedule is updated.

[0055] Building upon this foundation, the system can also match multiple feasible process paths for the same material from a pre-stored process route template library, such as conventional routes, high-precision routes, modular machining, and integral casting. Combining current equipment load, fixture availability, and priority indices, the system employs heuristic search or constraint satisfaction algorithms to automatically select the process route with the minimum total weighted delay, the fewest resource conflicts, or the optimal energy consumption, while meeting quality constraints. For example, for high-priority urgent orders, the system may skip non-critical inspection steps and activate high-speed but high-energy-consuming equipment to compress the delivery cycle; while for orders with high quality control requirements, it will forcibly insert additional flaw detection procedures, even if it extends the lead time.

[0056] In this embodiment, by deeply coupling dynamic priority calculation with process route generation, the system ensures on-time delivery of critical orders while also taking into account quality compliance and resource efficiency. This solves the problem that static priorities cannot adapt to the variability of MTO orders and that high-value / urgent orders cannot be guaranteed resources. It enables business strategy-driven intelligent scheduling, which can allocate resources to strategic customers, urgent deliveries, or high-profit orders, maximizing corporate benefits and customer satisfaction under limited capacity. At the same time, it supports dynamic adjustment of weights to adapt to different needs.

[0057] Furthermore, this application also provides a dynamic rescheduling mechanism under disturbance events, wherein disturbance event signals may include order queue jumping, equipment failure, delivery date changes, etc. Specifically, when a disturbance event signal is received, the affected workshop-level work orders and their subsequent process dependency chains are traversed, and based on the equipment type and special fixture identifier recorded in each work order, related work orders sharing the same equipment or special fixture are identified; work orders that have started or whose planned start time is less than a preset freeze window are frozen; for affected work orders that are not frozen, equipment, special tooling fixtures, and time windows are partially reallocated, and the corresponding local production scheduling segments are updated.

[0058] Specifically, considering the long process chain and multiple resource constraints in valve production, this application combines a dynamic rearrangement mechanism with a constraint model (condition). For example, the same equipment can only execute one or a few processes at a time; equipment maintenance time needs to be reserved in advance; different valve specifications require special fixtures; maintenance fixtures are used; and available time periods after calibration are considered. From the unfrozen affected work orders, the required equipment type, special tooling fixture identifier, and standard processing time for each work order are extracted; available machines in the current workshop that meet the equipment type, as well as special tooling fixtures that are not under maintenance and not occupied by frozen work orders, are traversed to form a candidate resource set; based on the process sequence dependency, a time window that meets the time conditions is searched in the candidate resource set for each work order; if at least one combination that meets the machine type, special tooling fixture, and time window conditions exists, an update is performed.

[0059] In this embodiment, by using local updates and adjustments, the problems of large computational load and slow response of global reordering, as well as the disruption of stable plans and frequent adjustments due to the lack of a freeze strategy, which affect on-site execution, are solved. This achieves local, incremental, and controlled dynamic reordering, which can quickly respond to disturbances, maintain the continuity of the overall plan, and reduce downtime losses and scheduling chaos while ensuring the stability of critical work orders.

[0060] Based on the same inventive concept, this application also provides a production scheduling system based on the MTO (Manufacturing Execution) production mode. Please refer to Figures 3 and 4. Figure 3 is a structural schematic diagram of the MTO-based production scheduling system 300 provided in an embodiment of this application, and Figure 4 is a structural schematic diagram of the ORR (Order of Return) control unit 304 provided in an embodiment of this application. The MTO-based production scheduling system 300 includes: a data acquisition unit 201, used to acquire real-time production data, including order parameters, equipment load data, work-in-process status, and disturbance event signals. The data acquisition unit 201 can connect to enterprise ERP, MES, Internet of Things (IIoT), and SCADA systems in real time via API interfaces or middleware to continuously collect real-time production data.

[0061] The product configuration engine 302, coupled with a pre-built product information model, generates configurable Bill of Materials (BOM) and process route data based on the order parameters. The embedded pre-built product information model includes a configurable BOM template library, a material feature value library, and attribute group definitions. Upon receiving order parameters, it automatically matches the BOM template, locates the specific code from the material master data through feature value comparison, and calls its "production attribute group" to generate the corresponding process route. This transforms the manual configuration process, which previously relied on engineer experience, into a system response, significantly improving BOM accuracy while ensuring a strict match between process routes and material characteristics, reducing the risk of mismatch.

[0062] The work order generation unit 303 is used to generate workshop-level work orders based on the configurable BOM and the process route data. It structurally integrates the BOM material list output by the product configuration engine with the process route sequence to generate standardized workshop-level work orders. Each work order includes fields such as work order ID, preceding process pointer, equipment type, dedicated tooling fixture identifier, and standard processing time. It outputs structured task units that can directly drive the scheduling engine, providing a unified and standardized scheduling object for subsequent ORR verification and resource allocation. The ORR control unit 304 is used to determine whether the workshop-level work order meets the deployment conditions based on equipment availability, dedicated tooling fixture status, and dynamic priority index. This prevents workshop overload (through resource verification) and ensures that high-value / urgent orders receive priority access to capacity (through dynamic priority), significantly improving on-time delivery rate and customer satisfaction while maintaining equipment load balance.

[0063] The dynamic rescheduling unit 305, upon receiving a disturbance event signal, freezes protected work orders and partially reallocates equipment, dedicated tooling fixtures, and time windows for affected work orders that are not frozen. By listening to disturbance event signals, it automatically identifies affected work orders, their dependencies, and resource sharing relationships; freezes work orders that have already started or are close to starting (freeze windows); extracts equipment / fixture requirements for the remaining work orders, searches the available resource pool for feasible time windows that satisfy process dependencies, and generates new local production schedule segments. This avoids the computational overhead and schedule oscillations caused by global rescheduling, adjusting only necessary parts while keeping frozen work orders unaffected, ensuring continuity of on-site execution.

[0064] The production scheduling output unit 306 is used to output the updated workshop operation production schedule.

[0065] The scheduling unit 307 is used to allocate tasks to corresponding workshop shifts according to the workshop operation scheduling plan. Based on the workshop operation scheduling plan provided by the scheduling output unit, the scheduling unit is responsible for allocating specific production tasks to specific shifts. Through scientific and reasonable scheduling, production line stagnation due to insufficient manpower or resource waste due to excessive manpower can be avoided, thereby improving overall work efficiency. In addition, the scheduling unit is also equipped with a feedback mechanism, that is, if it is found that some production tasks cannot be executed according to the predetermined plan during the scheduling process, further feedback can be provided to readjust the production plan or find alternative solutions.

[0066] Furthermore, the ORR control unit 304 includes a priority calculation subunit 3041, used to calculate the dynamic priority index of each workshop-level work order according to the formula: Priority Index = α·Product Priority + β·Customer Value Level + γ·Criticality Rate + δ·Completeness Rate; where α, β, γ, and δ are configurable weight parameters and their sum is 1; a resource verification subunit 3042, used to verify whether the available time of the equipment on which the target process depends in the future preset time window is not less than the standard processing time, and to confirm that the required special tooling fixture is in a non-maintenance and unoccupied state; and a sorting and placement subunit 3043, used to sort the work orders in descending order according to the dynamic priority index when multiple workshop-level work orders compete for the same equipment or special tooling fixture, and to release high-priority work orders to the scheduling engine first.

[0067] It should be noted that the production scheduling system based on the MTO production mode provided in this embodiment can refer to the above steps S101-S104 and any of their optional embodiments. Furthermore, the production scheduling system based on the MTO production mode provided in this embodiment and the embodiments of the production scheduling method based on the MTO production mode can be referenced each other, and will not be described again in this embodiment.

[0068] In summary, the production scheduling method based on the MTO production model provided in this application achieves efficient, accurate, and flexible production scheduling from order parameters to shop floor plans under the MTO model through technical means such as automatic order generation based on product configuration, ORR flow control and delivery, dynamic priority sorting, and partial rescheduling, which significantly improves resource utilization and delivery reliability.

[0069] Figure 5 is a structural schematic diagram of a computing device 900 provided in an embodiment of this application. This computing device can serve as a scheduling system based on the MTO production mode, executing various optional embodiments of the above-described scheduling method based on the MTO production mode. The computing device can be a terminal, or a chip or chip system inside the terminal. As shown in Figure 5, the computing device 900 includes: a processor 910, a memory 920, and a communication interface 930.

[0070] It should be understood that the communication interface 930 in the computing device 900 shown in Figure 5 can be used to communicate with other devices, and may specifically include one or more transceiver circuits or interface circuits.

[0071] The processor 910 can be connected to the memory 920. The memory 920 can be used to store the program code and data. Therefore, the memory 920 can be a storage unit inside the processor 910, an external storage unit independent of the processor 910, or a component that includes both the storage unit inside the processor 910 and the external storage unit independent of the processor 910.

[0072] Optionally, the computing device 900 may also include a bus. The memory 920 and communication interface 930 can be connected to the processor 910 via the bus. The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, a single line without an arrowhead is used in Figure 5, but this does not indicate that there is only one bus or one type of bus.

[0073] It should be understood that in the embodiments of this application, the processor 910 may be a Central Processing Unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor. Alternatively, the processor 910 may employ one or more integrated circuits to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0074] The memory 920 may include read-only memory and random access memory, and provides instructions and data to the processor 910. A portion of the processor 910 may also include non-volatile random access memory. For example, the processor 910 may also store device type information.

[0075] When the computing device 900 is running, the processor 910 executes computer execution instructions stored in the memory 920 to perform any of the operational steps of the above method and any of the optional embodiments thereof.

[0076] It should be understood that the computing device 900 according to the embodiments of this application can correspond to the corresponding subject in executing the methods according to the various embodiments of this application, and the above and other operations and / or functions of each module in the computing device 900 are respectively for implementing the corresponding processes of the methods of this embodiment. For the sake of brevity, they will not be described in detail here.

[0077] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0078] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0079] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device (system) embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0080] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0081] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0082] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A production scheduling method based on MTO (Manufacturing to Order) production mode, characterized in that, include: Obtain real-time production data; The production data is input into a pre-built product information model to generate configurable BOM and process route data; Based on the configurable BOM and the process route data, a workshop-level work order is generated; When the ORR mechanism determines that the workshop-level work order meets the deployment conditions, workshop production scheduling is carried out.

2. The production scheduling method according to claim 1, characterized in that, The product information model includes: a configurable BOM structure module, used to determine the BOM template and generate a preliminary material structure based on preset rules after inputting order parameters; a material feature value differentiation module, used to match material codes with corresponding feature values ​​from the material library according to the material requirements in the preliminary material structure; an attribute group division module, used to call the corresponding process route template and generate detailed process route data based on the material code and its associated characteristics; and a work order output module, used to generate workshop-level work orders based on the material code and the process route data and output them to the corresponding workshop team.

3. The production scheduling method according to claim 1, characterized in that, The determination that the workshop-level work order meets the deployment conditions through the ORR mechanism includes: obtaining the current workshop equipment load data, work-in-process quantity, and bottleneck resource occupancy rate; based on preset load threshold rules, determining whether the available time of the equipment on which the target process depends in a future preset time window is greater than or equal to the standard processing time of the workshop-level work order, and verifying that the special tooling fixtures required by the workshop-level work order are in a non-maintenance and unoccupied state in the time window; if both the equipment and the fixtures meet the availability conditions, then the workshop-level work order is determined to meet the deployment conditions.

4. The production scheduling method according to claim 3, characterized in that, It also includes, upon receiving a disturbance event signal: traversing the affected workshop-level work orders and their subsequent process dependency chains, and identifying related work orders that share the same equipment or special fixtures based on the equipment type and special fixture identifier recorded in each work order; freezing work orders that have already started or whose planned start time is less than the current time of a preset freeze window; and for affected work orders that are not frozen, partially reallocating equipment, special tooling fixtures, and time windows, and updating the corresponding local production scheduling segments.

5. The production scheduling method according to claim 4, characterized in that, The process of partially reallocating equipment, special tooling fixtures, and time windows for affected work orders that are not frozen includes: extracting the required equipment type, special tooling fixture identifier, and standard processing time for each work order from the affected work orders that are not frozen; traversing the available machines in the current workshop that meet the equipment type, as well as special tooling fixtures that are not under maintenance and are not occupied by frozen work orders, to form a candidate resource set; searching for time windows that meet the time conditions in the candidate resource set for each work order based on the process sequence dependency; and updating if at least one combination of machine, special tooling fixture, and time window meets the requirements.

6. The production scheduling method according to claim 1, characterized in that, It also includes sorting workshop-level work orders based on a dynamic priority index, wherein the dynamic priority index satisfies: priority index = α·product priority + β·product standard cycle + γ·critical rate + δ·completeness rate; where α, β, γ, and δ are configurable weight parameters, and α+β+γ+δ=1; the product priority is the ratio of the difference between the order delivery date and the current time to the standard processing time; when multiple work orders share the same equipment or special tooling fixtures, resources are preferentially allocated to work orders with higher priority indices; when order delivery dates change, resource conflicts occur, or production anomalies occur, the priority index of the affected work orders is recalculated and the production schedule is updated.

7. The production scheduling method according to claim 1, characterized in that, The real-time production data includes: dynamic order data, process routes, manufacturing resource data, production status data, and constraint rule sets.

8. A production scheduling system based on the MTO (Manufacturing Execution Tolerance) production model, characterized in that, include: The data acquisition unit is used to acquire real-time production data, including order parameters, equipment load data, work-in-process status, and disturbance event signals. The product configuration engine, coupled with a pre-built product information model, is used to generate configurable BOM and process route data based on the order parameters. The work order generation unit is used to generate workshop-level work orders based on the configurable BOM and the process route data. The ORR control unit is used to determine whether the workshop-level work order meets the deployment conditions based on equipment availability, special tooling fixture status and dynamic priority index. The dynamic reordering unit is used to freeze protected work orders and partially reallocate equipment, special tooling fixtures and time windows for affected work orders that are not frozen when a disturbance event signal is received. The production scheduling output unit is used to output the updated workshop operation production schedule; the shift scheduling unit is used to assign tasks to the corresponding workshop shifts according to the workshop operation production schedule.

9. The production scheduling system according to claim 8, characterized in that, The ORR control unit includes a priority calculation subunit, used to calculate the dynamic priority index of each workshop-level work order according to the formula: Priority Index = α·Product Priority + β·Customer Value Level + γ·Criticality Rate + δ·Completeness Rate; where α, β, γ, and δ are configurable weight parameters and their sum is 1; a resource verification subunit, used to verify whether the available time of the equipment on which the target process depends in the future preset time window is not less than the standard processing time, and to confirm that the required special tooling fixtures are in a non-maintenance and unoccupied state; and a sorting and placement subunit, used to sort multiple workshop-level work orders in descending order according to the dynamic priority index when multiple work orders compete for the same equipment or special tooling fixtures, and to release high-priority work orders to the scheduling engine first.

10. A computing device, characterized in that, include: A processor and a memory connected to the processor and storing program instructions that, when executed by the processor, cause the processor to perform the scheduling method based on the MTO production mode as described in any one of claims 1-7.

Images