An order production scheduling and real-time early warning management system and method

Abstract

The application discloses an order production scheduling and real-time early warning management system, comprising an order scheduling module, a process tracking module, a progress early warning module and a resource board module, wherein the order scheduling module is configured to determine scheduling information according to order product information; the process tracking module is configured to track the current state of the product by associating the ERP, MES and PLM systems; the progress early warning module is configured to conduct multi-level comprehensive risk early warning according to the current date, the delivery date and the current state; and the resource board module is configured to summarize order product production information and conduct statistical analysis. The application also discloses an order production scheduling and real-time early warning management method. The application can deeply integrate specific business knowledge, realize full closed-loop management from intelligent scheduling to real-time early warning, fill the digital gap between the planning and execution layers, and improve the overall operation resilience, delivery reliability and customer satisfaction.

Description

Technical Field

[0001] This invention relates to the field of industrial software and intelligent manufacturing, and in particular to an order production scheduling and real-time early warning management system and method. Background Technology

[0002] In the current field of precision equipment component manufacturing, project management during the product introduction phase generally faces severe challenges. Traditional methods heavily rely on manually maintained Microsoft Excel spreadsheets for order tracking. While these spreadsheets incorporate complex logic based on delivery dates, process types, and supplier status, they have inherent flaws: data is scattered and updates are delayed, cross-departmental collaboration is inefficient, and progress and risk at key nodes depend on manual inspection and experience-based judgment, making real-time early warning and proactive intervention difficult. Especially when dealing with orders of multiple varieties, small batches, and short delivery times, existing tools cannot effectively perform reverse scheduling based on the final delivery date and lack scientific visualization analysis of capacity load, resulting in poor plan controllability, high risk of delays, and suboptimal resource allocation. Although general-purpose Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MES), and project management software exist, they often struggle to deeply adapt to the highly customized, fast-paced, and logically rigorous business rules and collaborative needs of specific scenarios, creating a disconnect between the system and management. Therefore, the industry urgently needs a professional solution that can deeply integrate specific business knowledge and realize a closed-loop management system from intelligent scheduling to real-time early warning, in order to bridge the digital gap between the planning and execution layers and improve overall operational resilience, delivery reliability and customer satisfaction.

[0003] Therefore, those skilled in the art are dedicated to developing an order production scheduling and real-time early warning management system and method that can deeply integrate specific business knowledge and realize a closed-loop management system from intelligent scheduling to real-time early warning, in order to fill the digital gap between the planning and execution layers and improve overall operational resilience, delivery reliability and customer satisfaction. Summary of the Invention

[0004] In view of the above-mentioned deficiencies of the prior art, the main technical problems to be solved by the present invention are: 1) High-precision reverse scheduling and dynamic buffer management. The system must take the customer's final delivery date as a hard constraint. Based on complex process routes, supplier cycles and internal capacity, it automatically reverse-calculates the latest completion time of each production and procurement node and intelligently and dynamically allocates buffers to cope with uncertainties in production. This is the cornerstone of the plan to ensure delivery.

[0005] 2) Real-time monitoring and concurrent processing performance for massive orders and data rows. When faced with hundreds of parallel projects and thousands of order rows, traditional manual tracking or simple systems cannot perform real-time calculations. The system needs to have a high-performance engine that can scan all order statuses and compare them with plans in milliseconds, and instantly make early warning judgments to ensure that nothing is missed. This is the core of achieving automated efficiency improvement.

[0006] 3) Intelligent conflict detection and resource balancing under multiple constraints. The system needs to identify time conflicts between orders caused by shared key resources (such as specific machine tools or process engineers) in real time during automatic scheduling, and be able to automatically propose adjustment suggestions or warnings based on delivery priority to prevent cascading delays caused by resource competition. This is a key leap from planning to reliable execution.

[0007] 4) Adaptive early warning rules and precise push mechanism. To avoid early warning fatigue under massive information, the system needs to be able to intelligently adjust the early warning threshold and push targets based on order characteristics (such as customer level, urgency status) and real-time progress, ensuring that key risks reach key responsible persons directly and improving the accuracy and efficiency of intervention.

[0008] To achieve the above objectives, the present invention provides an order production scheduling and real-time early warning management system, comprising: An order scheduling module, configured to determine production scheduling information based on order product information; A process tracking module, configured to track the current status of a product by associating with ERP, MES, and PLM systems; A progress warning module is configured to provide multi-level comprehensive risk warnings based on the current date, delivery date, and current status; and The resource dashboard module is configured to summarize order product production information and perform statistical analysis.

[0009] Furthermore, it also includes a supplier submodule, which is configured as follows: Determine the supplier's delivery date based on the order's information on purchased products and the product's complexity level; Calculate the total number of days from the order date to the supplier's delivery date, and use this as the supplier's delivery time in days; Update the current status of the purchased products and report it back to the process tracking module; and A multi-level comprehensive risk warning is issued based on the current date, the supplier's delivery date, and the current status of the purchased products.

[0010] Furthermore, the order scheduling module is configured as follows: Calculate the total number of days from the order date to the delivery date, as the delivery time in days; Expedited shipments are categorized based on delivery time in days; The number of days to allow for process completion and machining completion shall be determined based on the complexity level of the product. Determine whether the allowance for delivery days between the machining completion date and the delivery date is reasonable based on the delivery period and surface treatment; and Whether to allow for a production margin depends on the categorization of expedited orders and the complexity level of the product.

[0011] Furthermore, the multi-level comprehensive risk warning based on the current date, delivery date, and current status specifically includes: If the current date is later than the delivery date, the risk status will be marked as overdue; If the current status is "shipped" or "in stock," then mark the risk status as "normal." If the number of days allowed between the machining completion date and the delivery date is unreasonable, the risk status will be marked as high risk. If the process is not completed within the reserved number of days for process completion, the risk status will be marked as high risk. Determine whether the risk status is high-risk based on the number of days remaining from the current date to the delivery date, combined with the current status; and By comparing the ratio of the remaining days from the current date to the delivery date to the estimated delivery days with the predetermined value, we can determine whether the risk status is high and whether it is necessary to expedite the completion of the process or expedite the start-up of the machine.

[0012] Furthermore, the multi-level comprehensive risk warning based on the current date combined with the supplier's delivery date and the current status of the purchased products specifically includes: If the current date is later than the supplier's delivery date, the risk status of the purchased product will be marked as overdue. If the current status of the purchased product is "shipped" or "in stock", then mark the risk status of the purchased product as "normal". Determine whether the risk status of the purchased product is high-risk based on the remaining days from the current date to the supplier's delivery date and the current status of the purchased product; and By comparing the ratio of the remaining days from the current date to the supplier's delivery date to the supplier's delivery period with the predetermined value, we can determine whether the risk status of the purchased product is high-risk and whether it is necessary to urge the supplier to complete the process or expedite the installation.

[0013] This invention also provides a method for order production scheduling and real-time early warning management, comprising the following steps: Step 1: Determine production scheduling information based on order product information; Step 2: Track the current status of the product by linking it with ERP, MES, and PLM systems; Step 3: Conduct multi-level comprehensive risk warning based on the current date, delivery date, and current status; Step 4: Summarize the production information of the ordered products and perform statistical analysis.

[0014] Furthermore, step 1 specifically includes the following steps: Calculate the total number of days from the order date to the delivery date, as the delivery time in days; Expedited shipments are categorized based on delivery time in days; The number of days to allow for process completion and machining completion shall be determined based on the complexity level of the product. Whether the buffer between the machining completion date and the delivery date is reasonable is determined based on the surface treatment; and Whether to allow for a production margin depends on the categorization of expedited orders and the complexity level of the product.

[0015] Furthermore, step 3 specifically includes the following steps: If the current date is later than the delivery date, the risk status will be marked as overdue; If the current status is "shipped" or "in stock," then mark the risk status as "normal." If the buffer between the machining completion date and the delivery date is unreasonable, the risk status will be marked as high risk; If the process is not completed within the reserved number of days for process completion, the risk status will be marked as high risk. Determine whether the risk status is high-risk based on the number of days remaining from the current date to the delivery date, combined with the current status; and By comparing the ratio of the remaining days from the current date to the delivery date to the estimated delivery days with the predetermined value, we can determine whether the risk status is high and whether it is necessary to expedite the completion of the process or expedite the start-up of the machine.

[0016] Furthermore, step 3 also includes the following steps: Determine the supplier's delivery date based on the order's information on purchased products and the product's complexity level; Calculate the total number of days from the order date to the supplier's delivery date, and use this as the supplier's delivery time in days; Update and provide feedback on the current status of purchased products; and A multi-level comprehensive risk warning is issued based on the current date, the supplier's delivery date, and the current status of the purchased products.

[0017] Furthermore, the multi-level comprehensive risk warning based on the current date combined with the supplier's delivery date and the current status of the purchased products specifically includes the following steps: If the current date is later than the supplier's delivery date, the risk status of the purchased product will be marked as overdue. If the current status of the purchased product is "shipped" or "in stock", then mark the risk status of the purchased product as "normal". Determine whether the risk status of the purchased product is high-risk based on the remaining days from the current date to the supplier's delivery date and the current status of the purchased product; and By comparing the ratio of the remaining days from the current date to the supplier's delivery date to the supplier's delivery period with the predetermined value, we can determine whether the risk status of the purchased product is high-risk and whether it is necessary to urge the supplier to complete the process or expedite the installation.

[0018] Compared with the prior art, the present invention has the following advantages: The system achieves deep digitization and rule engineization of business logic, transforming the complex, experience-dependent judgment criteria (such as automatically determining "delivery risk level" based on dozens of conditions like delivery days, process status, and surface treatment type) in managing frequent order placements, numerous order lines, and inconsistent delivery dates into a built-in configurable rule base. This solidifies expert experience into intelligent algorithms that can be continuously optimized and iterated, fundamentally changing the traditional decision-making model that relies on personal experience. Simultaneously, the system constructs a real-time collaborative and proactive early warning network spanning orders, processes, production, and logistics. Through dynamic data dashboards and multi-level early warning triggering mechanisms (such as "high risk," "urging process completion," and "urging machine deployment"), it shifts from post-event remediation to pre-event intervention, enabling proactive perception and precise management of potential delay risks. Furthermore, the project pioneered intelligent scheduling simulation and visualized load analysis functions for capacity constraints. By integrating multi-dimensional data such as processing time, machine setup time, and machine tool capacity, it can intuitively display the utilization rate of individual machines and the overall capacity. It also supports intelligent suggestions for production margin based on "urgent level" and "process difficulty," providing scientific quantitative decision support for production planning and effectively improving resource utilization efficiency and delivery reliability. Finally, the system adopts a lightweight and modular design concept. While fully retaining and optimizing the original business logic, it achieves low-cost, highly flexible rapid deployment and adaptive adjustment through configurable dashboards, permissions, and process engines. This lays an open technical foundation for subsequent deep integration with MES, ERP, and other systems and the continuous evolution of management models. Detailed Implementation

[0019] The following describes several preferred embodiments of the present invention to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms, and the scope of protection of the present invention is not limited to the embodiments mentioned herein.

[0020] This invention belongs to the interdisciplinary field of industrial software and intelligent manufacturing, specifically positioned as a front-end extension of Advanced Planning and Scheduling (APS) and Manufacturing Execution System (MES) under Manufacturing Operations Management (MOM). Through data mining and a business rule engine, it achieves digital management and real-time decision support for the entire order lifecycle during the product introduction phase, serving as a key collaboration and early warning platform connecting the planning and execution layers.

[0021] This invention aims to design and implement an "Order Production Scheduling and Real-time Early Warning Management System" to completely solve the core pain points of inefficiency, delayed risks, and unstable delivery caused by the current reliance on manual Excel management. The fundamental goal of the system construction is to transform the business rules and expert experience stored in spreadsheets into executable digital intelligence, and to build an automated operational platform that is absolutely guided by customer delivery dates, uses process nodes as control levers, and is driven by real-time data.

[0022] The core of this invention revolves around four main business logics: First, based on the final delivery date of the order, the system will automatically reverse-engineer the planned time of key nodes in the entire process from process design, machining to surface treatment for each order, combining standard process cycle, resource calendar and dynamic buffer model, forming an accurate "planning baseline" and changing manual estimation to system calculation.

[0023] Secondly, the system will establish a real-time monitoring engine to continuously compare the deviation between the actual progress of orders and the "planned baseline". It will also have a built-in multi-level risk judgment rule library based on delivery time margin, task status, and process complexity, which will automatically identify warning states such as "high risk" and "need to be expedited", thus realizing a paradigm shift from passive response to proactive intervention.

[0024] Third, the system will automatically link risk status with the visualization interface. Once an alert is triggered, the corresponding order's identifier (such as color and sorting) in the dashboard will change in real time, creating a clear "management red light" to ensure that problems are not overlooked.

[0025] Fourth, the system will dynamically sort and filter all orders based on the urgency of delivery and the level of risk, always pushing the most urgent and challenging tasks to the manager's attention and optimizing the allocation of management attention.

[0026] To achieve the aforementioned business vision, a series of key technologies need to be overcome: First, we build a flexibly configurable business rule engine to transform hundreds of complex Excel judgment logics (such as delivery risk calculation formulas) into maintainable and iterative digital rules.

[0027] Second, we will develop a high-performance data processing and status monitoring architecture to ensure that tens of thousands of order items can be scanned and calculated in real time within seconds, meeting the needs of large-scale concurrency.

[0028] Third, we designed an intelligent scheduling algorithm based on constraint theory, which comprehensively considers multiple constraints such as equipment capacity and material preparation during reverse calculation to generate a feasible and optimized plan.

[0029] Fourth, establish a stable and reliable data integration channel to connect with existing ERP, MES and other systems, automatically acquire key data such as orders, materials and inventory, and break down information silos.

[0030] The system implementation will follow the principles of "value-driven and agile iteration" and will be steadily advanced in three phases: The first phase (pilot verification) will select typical product lines, complete the development of the core scheduling and early warning modules, and compare and verify them with historical data to ensure the accuracy of the core logic.

[0031] The second phase (functional improvement and promotion) will expand the system's functions, such as integrating workshop work reporting, improving supplier collaboration, and promoting its use in more business units, while establishing a preliminary data analysis dashboard.

[0032] The third phase (Deepening and Optimization) will focus on enhancing the system's intelligence, introducing machine learning algorithms to optimize buffer settings and early warning thresholds, and building complete capacity forecasting and simulation functions to support strategic decision-making. The key to the project's success lies in close business-technology collaboration; therefore, a cross-functional team will be formed to ensure that business knowledge is accurately extracted and integrated into the system design.

[0033] The implementation of this plan is expected to achieve the following core values: The on-time delivery rate of orders has been significantly improved, the production cycle has been effectively shortened, and management personnel have been freed from the heavy workload of data sorting and manual tracking, so that they can focus on anomaly handling and decision optimization, ultimately building the company's new generation of competitiveness in the high-end manufacturing field with speed and reliability at its core.

[0034] The key technologies of this invention include: 1) Automatically schedule production based on delivery dates, specifying the deadline and completion date for each node.

[0035] 2) Automatically issue risk warnings based on the project's progress status.

[0036] 3) Identify risks based on status and automatically update colors.

[0037] 4) Automatic sorting and tracking are performed based on the final delivery date.

[0038] Based on the core logic of "starting with the end in mind, dynamic early warning, and visual tracking," the main technical indicators of this invention are as follows: The accuracy of reverse scheduling calculation measures the degree to which the system automatically calculates the planned dates of each node based on the final delivery date, process logic and buffer rules. This is the foundation of automated scheduling. The accuracy and coverage of risk warnings are assessed by the system through real-time comparison of status and time baselines. This ensures that the system automatically identifies and triggers various risk warnings, guaranteeing no omissions and no false alarms. The consistency of status-color mapping rule response examines the immediacy and synchronization of the system's automatic color updates to the front-end dashboard based on the risk assessment results from the backend, achieving zero-latency visual alerts. Dynamic sorting and timely information highlighting: The quantitative system uses the urgency of delivery and risk level as core weights to dynamically rearrange the order list and highlight key tasks. The responsiveness and logical rationality of this system ensure that management attention is efficiently guided to the highest priority.

[0039] These four indicators together constitute the technical benchmark for closed-loop management capabilities, from intelligent planning and real-time perception to visualization-driven management. Example 1

[0040] This embodiment provides an order production scheduling and real-time early warning management system, including an order scheduling module, a process tracking module, a progress early warning module, and a resource dashboard module.

[0041] The order scheduling module can determine production scheduling information based on order product information.

[0042] Specifically, the order scheduling module can: 1) Calculate the total number of days from the order date to the delivery date, and use this as the delivery period in days.

[0043] 2) Classify expedited shipments according to the delivery time in days.

[0044] When the delivery period is ≤7 days, it is called "express"; when the delivery period is between 8 and 14 days, it is called "urgent"; when the delivery period is between 15 and 20 days, it is called "normal"; and when the delivery period is >20 days, it is called "regular".

[0045] 3) Determine the number of days to allow for process completion and machining completion based on the product's complexity level.

[0046] When the product difficulty level is A+, the process completion allowance is 2.5 days of delivery days; when the product difficulty level is A, the process completion allowance is 2.2 days of delivery days; when the product difficulty level is B, the process completion allowance is 1.8 days of delivery days; when the product difficulty level is C, the process completion allowance is 1.7 days of delivery days.

[0047] After the manufacturing process is completed, machining work begins immediately. When the product difficulty level is A+, the machining allowance is 2 days of delivery time; when the product difficulty level is A, the machining allowance is 2.5 days of delivery time; when the product difficulty level is B, the machining allowance is 4 days of delivery time; and when the product difficulty level is C, the machining allowance is 5 days of delivery time.

[0048] 4) Determine whether the number of days allowed between the machining completion date and the delivery date is reasonable based on the surface treatment.

[0049] When there is no surface treatment and the reserved delivery days are less than 1, it is unreasonable; When the surface treatment is perfluoroalkoxy resin (PFA) or polytetrafluoroethylene (PTFE), it is unreasonable to allow less than 6 days for delivery.

[0050] 5) Determine whether to allow for a margin in production based on the grading of expedited orders and the difficulty level of the product.

[0051] When urgent shipments are classified as "urgent" or "critical", leave two spare shipments as backups. When expedited shipments are classified as "general" or "regular", leave one extra shipment as a backup. When the product difficulty level is A+ or A, leave an extra 2 pieces to prevent scrap. When the product difficulty level is B or C, no allowance is allowed.

[0052] The current status of a product includes: awaiting processing, awaiting machine installation, in the process of machining, heat treatment, machining after heat treatment, welding, post-weld processing, subsequent processing, engraving, surface treatment, cleaning, packaging, incoming material inspection, defective incoming materials awaiting processing, shipped, and already in storage.

[0053] The process tracking module tracks the current status of products by linking with ERP, MES, and Product Lifecycle Management (PLM) systems.

[0054] If an associated PLM process route is published, the pending process will not be displayed. If the associated MES system has received materials but has not yet started production, it will display "Pending Loading". Each process can be linked to the MES and benchmarked against the PLM process sub-segments; The system automatically updates the shipment and inventory records in the linked ERP system.

[0055] The progress warning module provides multi-level comprehensive risk warnings based on the current date, delivery date, and current status, as detailed below: 1) If the current date is later than the delivery date, mark the risk status as overdue.

[0056] 2) If the current status is "shipped" or "in stock", then mark the risk status as "normal".

[0057] 3) If the number of days allowed between the machining completion date and the delivery date is unreasonable, the risk status will be marked as high risk.

[0058] 4) If the process is not completed within the reserved number of days for process completion, the risk status will be marked as high risk.

[0059] 5) When the product is a self-produced part, the risk status is determined based on the number of days remaining from the current date to the delivery date and the current status of the product, as follows: When the current status of a product is "in process" and the remaining days are ≤4, the product risk status will be marked as high risk. When the current status of a product is heat treatment and the remaining days are ≤4, the product risk status will be marked as high risk. When the current status of a product is heat-treated and machined, and the remaining days are ≤3, the product risk status will be marked as high risk. When the current status of a product is post-processing, engraving, surface treatment, or incoming material inspection, and the remaining days are ≤1, the product risk status will be marked as high risk. When the current status of the product is welding and the remaining days are ≤3, the product risk status will be marked as high risk. When the current status of a product is post-weld processing and the remaining days are ≤2, the product risk status will be marked as high risk. When the current status of a product is cleaning and the remaining days are ≤0.5, the product risk status will be marked as high risk. When a product is currently in packaging and has ≤0.5 days remaining, the product risk status will be marked as high risk.

[0060] 6) By comparing the ratio of the remaining days from the current date to the delivery date to the estimated delivery period with the predetermined value, determine whether the risk status is high-risk, and determine whether it is necessary to expedite the completion of the process or expedite the start-up of the machine, as detailed below: During the pending process stage, if the remaining days are less than or equal to the delivery days / 3, the product risk status is marked as high risk; if the remaining days are less than or equal to the delivery days / 2, a message to expedite the completion of the process is automatically sent to the process manager. During the waiting period before deployment, if the remaining days are ≤7 or ≤ delivery days / 2.5, the product risk status will be marked as high risk; if the remaining days are ≤ delivery days / 1.7, a message urging deployment will be automatically sent to the project manager.

[0061] The resource dashboard module summarizes and statistically analyzes order product production information, which may include the following: Monthly order volume distribution, monthly shipment volume distribution, order volume summary, self-produced / outsourced statistics, shipment volume statistics, self-produced process completion status, delivery time distribution, etc.

[0062] In some embodiments, when the product is a purchased component, a supplier submodule is also included, which is capable of: 1) Determine the supplier's delivery date based on the order's purchased product information and the product's difficulty level.

[0063] When the product difficulty level is A+, if the delivery period is ≤20 days, the supplier's delivery date will be reduced by 2 days; if 20 < delivery period ≤30 days, the supplier's delivery date will be reduced by 3 days; if the delivery period is >30 days, the supplier's delivery date will be reduced by 4 days. When the product difficulty level is A, if the delivery period is ≤15 days, the supplier's delivery date will be reduced by 1 day; if 15 < delivery period ≤20 days, the supplier's delivery date will be reduced by 2 days; if 20 < delivery period ≤25 days, the supplier's delivery date will be reduced by 3 days; if 25 < delivery period ≤30 days, the supplier's delivery date will be reduced by 3 days; if the delivery period >30 days, the supplier's delivery date will be reduced by 5 days. When the product difficulty level is B, if the delivery period is ≤7 days, the supplier's delivery date will be reduced by 1 day; if 7 < delivery period ≤15 days, the supplier's delivery date will be reduced by 2 days; if 15 < delivery period ≤20 days, the supplier's delivery date will be reduced by 5 days; if 20 < delivery period ≤25 days, the supplier's delivery date will be the order date + 20 days; if 25 < delivery period ≤30 days, the supplier's delivery date will be the order date + 20 days; if the delivery period >30 days, the supplier's delivery date will be the order date + 20 days. When the product difficulty level is C, if the delivery period is ≤7 days, the supplier's delivery date will be reduced by 1 day; if 7 < delivery period ≤15 days, the supplier's delivery date will be reduced by 3 days; if 15 < delivery period ≤20 days, the supplier's delivery date will be reduced by 5 days; if 20 < delivery period ≤25 days, the supplier's delivery date will be the order date + 20 days; if 25 < delivery period ≤30 days, the supplier's delivery date will be the order date + 20 days; if the delivery period >30 days, the supplier's delivery date will be the order date + 20 days.

[0064] 2) Calculate the total number of days from the order date to the supplier's delivery date, and use this as the supplier's delivery time in days.

[0065] 3) The supplier updates the current status of the purchased products and feeds it back to the process tracking module.

[0066] The current status of purchased products includes pending processing, pending machine installation, in the process of machining, heat treatment, post-heat treatment machining, welding, post-weld processing, assembly, engraving, surface treatment, cleaning, packaging, incoming material inspection, defective incoming materials pending processing, shipped, and already in storage.

[0067] 4) A multi-level comprehensive risk warning system is implemented based on the current date, supplier delivery date, and the current status of purchased products. This includes: 4.1) If the current date is later than the supplier's delivery date, mark the risk status of the purchased product as overdue.

[0068] 4.2) If the current status of the purchased product is "shipped" or "in stock", then mark the risk status of the purchased product as "normal".

[0069] 4.3) Determine whether the risk status of the purchased product is high-risk based on the number of days remaining from the current date to the supplier's delivery date and the current status of the purchased product, as follows: When the current status of a purchased product is "in process" and the remaining days are ≤4, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is heat treatment and the remaining days are ≤4, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is heat-treated and machined, and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. If the current status of a purchased product is engraving or surface treatment, and the remaining days are ≤2, then the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is incoming inspection and the remaining days are ≤1, the risk status of the purchased product will be marked as high risk. When the current status of a purchased product is assembly and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is welding and the remaining days are ≤3, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is post-weld processing and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is cleaning and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. When the current status of a purchased product is "packaged" and the remaining days are ≤1, the risk status of the purchased product will be marked as high risk.

[0070] 4.4) By comparing the ratio of the remaining days from the current date to the supplier's delivery date to the supplier's delivery period with the predetermined value, determine whether the risk status of the purchased product is high-risk, and determine whether it is necessary to expedite the supplier's completion of the process or to expedite its deployment, as detailed below: During the pending process stage, if the remaining days are less than or equal to the delivery days / 2, the product risk status is marked as high risk; if the remaining days are less than or equal to the delivery days / 1.5, a message urging the completion of the process is automatically sent to the purchasing manager. During the waiting period before product launch, if the remaining days are less than or equal to the delivery date / 2.5, the product risk status will be marked as high risk; if the remaining days are less than or equal to the delivery date / 1.7, a reminder message to launch the product will be automatically sent to the purchasing manager. Example 2

[0071] This embodiment also provides a method for order production scheduling and real-time early warning management, including the following steps: 1. Determine production scheduling information based on order product information.

[0072] 1.1 Calculate the total number of days from the order date to the delivery date, and use this as the delivery period in days.

[0073] 1.2 Classify expedited shipments according to the delivery time in days.

[0074] When the delivery period is ≤7 days, it is called "express"; when the delivery period is between 8 and 14 days, it is called "urgent"; when the delivery period is between 15 and 20 days, it is called "normal"; and when the delivery period is >20 days, it is called "regular".

[0075] 1.3 Determine the number of days to allow for process completion and machining completion based on the product's complexity level.

[0076] When the product difficulty level is A+, the process completion allowance is 2.5 days of delivery days; when the product difficulty level is A, the process completion allowance is 2.2 days of delivery days; when the product difficulty level is B, the process completion allowance is 1.8 days of delivery days; when the product difficulty level is C, the process completion allowance is 1.7 days of delivery days.

[0077] After the manufacturing process is completed, machining work begins immediately. When the product difficulty level is A+, the machining allowance is 2 days of delivery time; when the product difficulty level is A, the machining allowance is 2.5 days of delivery time; when the product difficulty level is B, the machining allowance is 4 days of delivery time; and when the product difficulty level is C, the machining allowance is 5 days of delivery time.

[0078] 1.4. Determine whether the allowance for delivery days between the machining completion date and the delivery date is reasonable based on the surface treatment.

[0079] When there is no surface treatment and the reserved delivery days are less than 1, it is unreasonable; If the surface treatment is PFA or polytetrafluoroethylene (PTFE), and the estimated delivery time is less than 6 days, it is unreasonable.

[0080] 1.5. Determine whether to allow for a margin in production based on the grading of urgent orders and the difficulty level of the product.

[0081] When urgent shipments are classified as "urgent" or "critical", leave two spare shipments as backups. When expedited shipments are classified as "general" or "regular", leave one extra shipment as a backup. When the product difficulty level is A+ or A, leave an extra 2 pieces to prevent scrap. When the product difficulty level is B or C, no allowance is allowed.

[0082] 2. Track the current status of products by linking with ERP, MES and PLM systems; the current status of products includes waiting for process, waiting to be put into machine, machining in progress, heat treatment, machining after heat treatment, welding, post-weld processing, post-processing, engraving, surface treatment, cleaning, packaging, incoming material inspection, incoming material defects pending processing, shipped, and warehoused.

[0083] If an associated PLM process route is published, the pending process will not be displayed. If the associated MES system has received materials but has not yet started production, it will display "Pending Loading". Each process can be linked to the MES and benchmarked against the PLM process sub-segments; The system automatically updates the shipment and inventory records in the linked ERP system.

[0084] 3. Conduct multi-level comprehensive risk warnings based on the current date, delivery date, and current status.

[0085] 3.1 If the current date is later than the delivery date, mark the risk status as overdue; 3.2 If the current status is "shipped" or "in stock," then mark the risk status as "normal." 3.3 If the number of days allowed between the machining completion date and the delivery date is unreasonable, the risk status will be marked as high risk; 3.4 If the process is not completed within the reserved number of days for process completion, the risk status will be marked as high risk; 3.5 When the product is a self-produced part, the risk status is determined based on the number of days remaining from the current date to the delivery date and the current status, as follows: When the current status of a product is "in process" and the remaining days are ≤4, the product risk status will be marked as high risk. When the current status of a product is heat treatment and the remaining days are ≤4, the product risk status will be marked as high risk. When the current status of a product is heat-treated and machined, and the remaining days are ≤3, the product risk status will be marked as high risk. When the current status of a product is post-processing, engraving, surface treatment, or incoming material inspection, and the remaining days are ≤1, the product risk status will be marked as high risk. When the current status of the product is welding and the remaining days are ≤3, the product risk status will be marked as high risk. When the current status of a product is post-weld processing and the remaining days are ≤2, the product risk status will be marked as high risk. When the current status of a product is cleaning and the remaining days are ≤0.5, the product risk status will be marked as high risk. When a product is currently in packaging and has ≤0.5 days remaining, the product risk status will be marked as high risk.

[0086] 3.6. By comparing the ratio of the remaining days from the current date to the delivery date to the estimated delivery period with the predetermined value, determine whether the risk status is high-risk, and determine whether it is necessary to expedite the completion of the process or expedite the start-up of the machine, as detailed below: During the pending process stage, if the remaining days are less than or equal to the delivery days / 3, the product risk status is marked as high risk; if the remaining days are less than or equal to the delivery days / 2, a message to expedite the completion of the process is automatically sent to the process manager. During the waiting period before deployment, if the remaining days are ≤7 or ≤ delivery days / 2.5, the product risk status will be marked as high risk; if the remaining days are ≤ delivery days / 1.7, a message urging deployment will be automatically sent to the project manager.

[0087] 4. Summarize and statistically analyze order product production information, which may include the following: Monthly order volume distribution, monthly shipment volume distribution, order volume summary, self-produced / outsourced statistics, shipment volume statistics, self-produced process completion status, delivery time distribution, etc.

[0088] In some embodiments, when the product is a purchased component, the step further includes: 1) Determine the supplier's delivery date based on the order's purchased product information and the product's difficulty level.

[0089] When the product difficulty level is A+, if the delivery period is ≤20 days, the supplier's delivery date will be reduced by 2 days; if 20 < delivery period ≤30 days, the supplier's delivery date will be reduced by 3 days; if the delivery period is >30 days, the supplier's delivery date will be reduced by 4 days. When the product difficulty level is A, if the delivery period is ≤15 days, the supplier's delivery date will be reduced by 1 day; if 15 < delivery period ≤20 days, the supplier's delivery date will be reduced by 2 days; if 20 < delivery period ≤25 days, the supplier's delivery date will be reduced by 3 days; if 25 < delivery period ≤30 days, the supplier's delivery date will be reduced by 3 days; if the delivery period >30 days, the supplier's delivery date will be reduced by 5 days. When the product difficulty level is B, if the delivery period is ≤7 days, the supplier's delivery date will be reduced by 1 day; if 7 < delivery period ≤15 days, the supplier's delivery date will be reduced by 2 days; if 15 < delivery period ≤20 days, the supplier's delivery date will be reduced by 5 days; if 20 < delivery period ≤25 days, the supplier's delivery date will be the order date + 20 days; if 25 < delivery period ≤30 days, the supplier's delivery date will be the order date + 20 days; if the delivery period >30 days, the supplier's delivery date will be the order date + 20 days. When the product difficulty level is C, if the delivery period is ≤7 days, the supplier's delivery date will be reduced by 1 day; if 7 < delivery period ≤15 days, the supplier's delivery date will be reduced by 3 days; if 15 < delivery period ≤20 days, the supplier's delivery date will be reduced by 5 days; if 20 < delivery period ≤25 days, the supplier's delivery date will be the order date + 20 days; if 25 < delivery period ≤30 days, the supplier's delivery date will be the order date + 20 days; if the delivery period >30 days, the supplier's delivery date will be the order date + 20 days.

[0090] 2) Calculate the total number of days from the order date to the supplier's delivery date, and use this as the supplier's delivery time in days; 3) The supplier shall update and provide feedback on the current status of the purchased products.

[0091] The current status of purchased products includes pending processing, pending machine installation, in the process of machining, heat treatment, post-heat treatment machining, welding, post-weld processing, assembly, engraving, surface treatment, cleaning, packaging, incoming material inspection, defective incoming materials pending processing, shipped, and already in storage.

[0092] 4) A multi-level comprehensive risk warning system is implemented based on the current date, supplier delivery date, and the current status of purchased products. This includes: 4.1) If the current date is later than the supplier's delivery date, mark the risk status of the purchased product as overdue.

[0093] 4.2) If the current status of the purchased product is "shipped" or "in stock", then mark the risk status of the purchased product as "normal".

[0094] 4.3) Determine whether the risk status of the purchased product is high-risk based on the number of days remaining from the current date to the supplier's delivery date and the current status of the purchased product, as follows: When the current status of a purchased product is "in process" and the remaining days are ≤4, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is heat treatment and the remaining days are ≤4, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is heat-treated and machined, and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. If the current status of a purchased product is engraving or surface treatment, and the remaining days are ≤2, then the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is incoming inspection and the remaining days are ≤1, the risk status of the purchased product will be marked as high risk. When the current status of a purchased product is assembly and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is welding and the remaining days are ≤3, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is post-weld processing and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. When the current status of the purchased product is cleaning and the remaining days are ≤2, the risk status of the purchased product will be marked as high risk. When the current status of a purchased product is "packaged" and the remaining days are ≤1, the risk status of the purchased product will be marked as high risk.

[0095] 4.4) By comparing the ratio of the remaining days from the current date to the supplier's delivery date to the supplier's delivery period with the predetermined value, determine whether the risk status of the purchased product is high-risk, and determine whether it is necessary to expedite the supplier's completion of the process or to expedite its deployment, as detailed below: During the pending process stage, if the remaining days are less than or equal to the delivery days / 2, the product risk status is marked as high risk; if the remaining days are less than or equal to the delivery days / 1.5, a message urging the completion of the process is automatically sent to the purchasing manager. During the waiting period before product launch, if the remaining days are less than or equal to the delivery date / 2.5, the product risk status will be marked as high risk; if the remaining days are less than or equal to the delivery date / 1.7, a reminder message to launch the product will be automatically sent to the purchasing manager.

Claims

1. An order production scheduling and real-time early warning management system, characterized in that, include: An order scheduling module, configured to determine production scheduling information based on order product information; A process tracking module, configured to track the current status of a product by associating with ERP, MES, and PLM systems; A progress warning module is configured to provide multi-level comprehensive risk warnings based on the current date, delivery date, and current status. as well as The resource dashboard module is configured to summarize order product production information and perform statistical analysis.

2. The order production scheduling and real-time early warning management system according to claim 1, characterized in that, It also includes a supplier submodule, which is configured as follows: Determine the supplier's delivery date based on the order's information on purchased products and the product's complexity level; Calculate the total number of days from the order date to the supplier's delivery date, and use this as the supplier's delivery time in days; Update the current status of the purchased products and send the feedback to the process tracking module; as well as A multi-level comprehensive risk warning is issued based on the current date, the supplier's delivery date, and the current status of the purchased products.

3. The order production scheduling and real-time early warning management system according to claim 1, characterized in that, The order scheduling module is configured as follows: Calculate the total number of days from the order date to the delivery date, as the delivery time in days; Expedited shipments are categorized based on delivery time in days; The number of days to allow for process completion and machining completion shall be determined based on the complexity level of the product. Determine whether the allowance for delivery days between the machining completion date and the delivery date is reasonable based on the delivery period and surface treatment; and Whether to allow for a production margin depends on the categorization of expedited orders and the complexity level of the product.

4. The order production scheduling and real-time early warning management system according to claim 3, characterized in that, The multi-level comprehensive risk warning based on the current date, delivery date, and current status specifically includes: If the current date is later than the delivery date, the risk status will be marked as overdue; If the current status is "shipped" or "in stock," then mark the risk status as "normal." If the number of days allowed between the machining completion date and the delivery date is unreasonable, the risk status will be marked as high risk. If the process is not completed within the reserved number of days for process completion, the risk status will be marked as high risk. Determine whether the risk status is high-risk based on the number of days remaining from the current date to the delivery date, combined with the current status of the product; and By comparing the ratio of the remaining days from the current date to the delivery date to the estimated delivery days with the predetermined value, we can determine whether the risk status is high and whether it is necessary to expedite the completion of the process or expedite the start-up of the machine.

5. The order production scheduling and real-time early warning management system according to claim 2, characterized in that, The multi-level comprehensive risk warning based on the current date, supplier delivery date, and current status of purchased products specifically includes: If the current date is later than the supplier's delivery date, the risk status of the purchased product will be marked as overdue. If the current status of the purchased product is "shipped" or "in stock", then mark the risk status of the purchased product as "normal". Determine whether the risk status of the purchased product is high-risk based on the remaining days from the current date to the supplier's delivery date and the current status of the purchased product; and By comparing the ratio of the remaining days from the current date to the supplier's delivery date to the supplier's delivery period with the predetermined value, we can determine whether the risk status of the purchased product is high-risk and whether it is necessary to urge the supplier to complete the process or expedite the installation.

6. A method for order production scheduling and real-time early warning management, characterized in that, Includes the following steps: Step 1: Determine production scheduling information based on order product information; Step 2: Track the current status of the product by linking it with ERP, MES, and PLM systems; Step 3: Conduct multi-level comprehensive risk warning based on the current date, delivery date, and current status; Step 4: Summarize the production information of the ordered products and perform statistical analysis.

7. The order production scheduling and real-time early warning management method according to claim 6, characterized in that, Step 1 specifically includes the following steps: Calculate the total number of days from the order date to the delivery date, as the delivery time in days; Expedited shipments are categorized based on delivery time in days; The number of days to allow for process completion and machining completion shall be determined based on the complexity level of the product. Determine whether the allowance for delivery days between the machining completion date and the delivery date is reasonable based on the delivery period and surface treatment; and Whether to allow for a production margin depends on the categorization of expedited orders and the complexity level of the product.

8. The order production scheduling and real-time early warning management method according to claim 7, characterized in that, Step 3 specifically includes the following steps: If the current date is later than the delivery date, the risk status will be marked as overdue; If the current status is "shipped" or "in stock," then mark the risk status as "normal." If the number of days allowed between the machining completion date and the delivery date is unreasonable, the risk status will be marked as high risk. If the process is not completed within the reserved number of days for process completion, the risk status will be marked as high risk. Determine whether the risk status is high-risk based on the number of days remaining from the current date to the delivery date and the current status of the product; as well as By comparing the ratio of the remaining days from the current date to the delivery date to the estimated delivery days with the predetermined value, we can determine whether the risk status is high and whether it is necessary to expedite the completion of the process or expedite the start-up of the machine.

9. The order production scheduling and real-time early warning management method according to claim 8, characterized in that, Step 3 further includes the following steps: Determine the supplier's delivery date based on the order's information on purchased products and the product's complexity level; Calculate the total number of days from the order date to the supplier's delivery date, and use this as the supplier's delivery time in days; Update and provide feedback on the current status of purchased products; as well as A multi-level comprehensive risk warning is issued based on the current date, the supplier's delivery date, and the current status of the purchased products.

10. The order production scheduling and real-time early warning management method according to claim 9, characterized in that, The multi-level comprehensive risk warning based on the current date, supplier delivery date, and current status of purchased products specifically includes the following steps: If the current date is later than the supplier's delivery date, the risk status of the purchased product will be marked as overdue. If the current status of the purchased product is "shipped" or "in stock", then mark the risk status of the purchased product as "normal". Determine whether the risk status of the purchased product is high-risk based on the number of days remaining from the current date to the supplier's delivery date and the current status of the purchased product; as well as By comparing the ratio of the remaining days from the current date to the supplier's delivery date to the supplier's delivery period with the predetermined value, we can determine whether the risk status of the purchased product is high-risk and whether it is necessary to urge the supplier to complete the process or expedite the installation.