Production management method and system based on multi-region management

Abstract

The invention relates to the technical field of production management, in particular to a production management method and system based on multi-area management, and the method comprises the steps: carrying out the digital modeling of the physical layout of a production workshop, obtaining a workshop digital model, and dividing a production area into a plurality of management sub-areas according to the workshop digital model; obtaining production equipment state information and material circulation information in each management sub-region in real time, and generating region state information of each management sub-region according to the production equipment state information and the material circulation information; and judging whether a starting condition of the production management system is met or not according to the area state information. According to the method, the overall production efficiency can be effectively improved by monitoring and analyzing the state information of each management sub-region in real time and identifying and solving the production bottleneck in time, and the target scheduling strategy is generated through the position information of the abnormal region and the bottleneck type, so that equipment and human resources can be better configured, and resource waste is reduced.

Description

Technical Field

[0001] This invention relates to the field of production management technology, specifically to a production management method and system based on multi-region management. Background Technology

[0002] Currently, traditional methods often rely on manual recording and periodic reporting, resulting in untimely information acquisition and difficulty in quickly responding to sudden problems in production. Moreover, traditional methods usually cannot track equipment status and production processes in real time, which can easily lead to the omission of potential bottlenecks and malfunctions. Furthermore, in traditional management, resource allocation is often based on experience and historical data, lacking dynamic adjustment capabilities, which can easily lead to waste or shortage of equipment and human resources.

[0003] Furthermore, due to the lack of data-driven analysis support, the decision-making process of traditional methods often relies on subjective judgment, which may lead to erroneous production scheduling and management decisions. Moreover, when production problems occur, traditional methods usually require a long time for information collection and problem analysis, resulting in slow response speed, increased downtime, and the lack of effective information sharing mechanisms in traditional methods, leading to poor communication between various links in the production process, reducing overall transparency and synergy. Summary of the Invention

[0004] To achieve the above objectives, the present invention provides the following technical solution: a production management method based on multi-region management, comprising: The physical layout of the production workshop is digitally modeled to obtain a digital model of the workshop, and the production area is divided into multiple management sub-areas based on the digital model of the workshop. Real-time acquisition of production equipment status information and material flow information in each management sub-region, and generation of regional status information for each management sub-region based on the production equipment status information and material flow information; Based on the regional status information, determine whether the startup conditions of the production management system are met; the startup conditions include that the initialization status of each management sub-region is completed and the running level is greater than the first preset running threshold. In response to the fulfillment of the start-up conditions, the system analyzes the regional status information according to the preset regional anomaly judgment rules, identifies the abnormal regions with production bottlenecks, and determines the location information and bottleneck type of the abnormal regions. Based on the location information and bottleneck type of the abnormal area, and combined with the preset equipment scheduling strategy library, a target scheduling strategy for the abnormal area is generated; the target scheduling strategy includes equipment movement path or task change instruction. The target scheduling strategy is sent to the corresponding production equipment or management terminal to adjust production activities in abnormal areas and collect the adjusted area status data in real time.

[0005] Preferably, after adjusting production activities within the abnormal area and collecting real-time data on the adjusted area status, the method further includes: Based on the adjusted regional status data and the regional status information before adjustment, determine whether the production efficiency improvement index is greater than the preset efficiency threshold. When the production efficiency improvement index is greater than the preset efficiency threshold, the abnormal area is confirmed to have returned to normal, and the equipment scheduling strategy library is updated according to the status of the restored area.

[0006] Preferably, based on the regional status information, it is determined whether the start-up conditions of the production management system are met, including: Obtain the initialization status and operational status of each managed sub-region from the regional status information; Determine whether the initialization status of each management sub-region is complete. If so, then it is further determined whether the total number of the first target areas is not less than a preset value; the first target area is the area whose running degree is greater than the first preset running threshold and whose position attribute is the left area or the right area. If the initialization status of each management sub-region is not all complete initialization, then determine whether the running status of each management sub-region is equal to the second preset running threshold; the second preset running threshold is greater than the first preset running threshold. When the total number of the first target areas is not less than a preset value or the operating level of each managed sub-area is equal to the second preset operating threshold, the start-up conditions of the production management system are confirmed to be met.

[0007] Preferably, based on production equipment status information and material flow information, regional status information for each management sub-region is generated, including: Based on the status information of production equipment, determine the operating load rate and failure downtime probability of equipment in each management sub-area; Based on the material flow information, determine the material accumulation and flow rate in each management sub-area; The system integrates operating load rate, failure downtime probability, material accumulation, and turnover speed to generate regional status information that characterizes the health of each management sub-region. The regional status information also includes the location attributes of each production area; the location attributes include left area location, right area location, left rear area location, or right rear area location.

[0008] Preferably, based on preset regional anomaly determination rules, the regional status information is analyzed to identify abnormal regions with production bottlenecks, including: Based on the operating load rate and material accumulation in the regional status information, determine whether each managed sub-region is in a high load or high inventory state; When a management sub-region is under high load or high inventory, the system determines whether the region meets the preset bottleneck triggering conditions based on the region's failure downtime probability and turnover rate. When a management sub-region meets a preset bottleneck triggering condition, the management sub-region is identified as an abnormal region with a production bottleneck. At the same time, the location attributes of the abnormal area are obtained to determine the specific location of the abnormal area on the production line.

[0009] Preferably, based on the location information and bottleneck type of the abnormal area, and in conjunction with a pre-defined equipment scheduling strategy library, a target scheduling strategy for the abnormal area is generated, including: Based on the location information of the abnormal area, candidate support areas that are adjacent to the abnormal area and match the location attributes are selected from all management sub-areas; Based on the bottleneck type, candidate scheduling schemes for resolving that type of bottleneck are matched from the equipment scheduling strategy library; The final target scheduling strategy is determined based on the equipment capabilities of the candidate support areas and the execution costs of the candidate scheduling schemes. The equipment capacity is determined by the operating load rate and equipment performance parameters in the area status information generated in the previous step.

[0010] Preferably, the final target scheduling strategy is determined based on the equipment capabilities of the candidate support areas and the execution costs of the candidate scheduling schemes, including: Obtain the number of available devices and their performance parameters within the candidate support area; Based on the candidate scheduling schemes, calculate the scheduling time required for the equipment to move from the candidate support area to the abnormal area and the impact on the production in the original area; When the equipment performance parameters meet the production needs of the abnormal area and the impact value is less than the preset impact threshold, the candidate scheduling scheme is determined as the target scheduling strategy. The issuance and execution of the target scheduling strategy depends on the scheduling time and impact value data determined in the previous step.

[0011] Preferably, based on the adjusted regional status data and the regional status information before adjustment, it is determined whether the production efficiency improvement index is greater than a preset efficiency threshold, including: Collect the material output and effective equipment operating time within the preset time period after adjustment, and use it as the adjusted regional status data. Calculate the baseline production efficiency based on the historical material output and historical equipment operation time in the area status information before adjustment. Calculate the current production efficiency based on the adjusted material output and effective equipment operating time; Calculate the difference between the current production efficiency and the benchmark production efficiency, and determine the ratio of this difference to the benchmark production efficiency as the production efficiency improvement index; The production efficiency improvement index is compared with a preset efficiency threshold to determine whether abnormal areas have returned to normal.

[0012] Preferably, in response to a production efficiency improvement index exceeding a preset efficiency threshold, the abnormal area is confirmed to have returned to normal, and the equipment scheduling strategy library is updated based on the status of the restored area, including: When it is determined that the production efficiency improvement index is greater than the preset efficiency threshold, it is confirmed that the bottleneck in the abnormal area has been eliminated and returned to normal. Extract the target scheduling strategy used for the abnormal area and the corresponding actual improvement effect data; the actual improvement effect data comes from the adjusted area status data. The target scheduling strategy and actual improvement effect data are used as new samples and added to the equipment scheduling strategy library; The updated equipment scheduling strategy library is used to optimize the next strategy generation logic in order to achieve closed-loop control of production management.

[0013] A production management system based on multi-region management, applicable to the aforementioned production management method based on multi-region management, includes: The area division unit is used to digitally model the physical layout of the production workshop to obtain a digital model of the workshop, and to divide the production area into multiple management sub-areas based on the digital model of the workshop. The status detection unit is used to acquire the status information of production equipment and material flow information in each management sub-area in real time, and generate the regional status information of each management sub-area based on the status information of production equipment and material flow information. The startup determination unit is used to determine whether the startup conditions of the production management system are met based on the area status information. The startup conditions include that the initialization status of each management sub-area is completed and the running level is greater than the first preset running threshold. The anomaly analysis unit is used to analyze the regional status information according to the preset regional anomaly judgment rules in response to the fulfillment of the start-up conditions, identify the abnormal regions with production bottlenecks, and determine the location information and bottleneck type of the abnormal regions. The target scheduling unit is used to generate a target scheduling strategy for the abnormal area based on the location information and bottleneck type of the abnormal area, combined with a preset equipment scheduling strategy library; the target scheduling strategy includes equipment movement paths or task change instructions. The production adjustment unit is used to send the target scheduling strategy to the corresponding production equipment or management terminal to adjust the production activities in the abnormal area and collect the adjusted area status data in real time.

[0014] Compared with the prior art, the beneficial effects of the present invention are: (1) By real-time monitoring and analysis of the status information of each management sub-area, the present invention can identify and solve production bottlenecks in a timely manner, which can effectively improve the overall production efficiency. Moreover, by generating target scheduling strategies based on the location information of abnormal areas and bottleneck types, it can better configure equipment and human resources, reduce resource waste, and by monitoring the operating load rate and failure downtime probability of equipment, it can detect potential problems early and reduce downtime caused by equipment failure. (2) This invention achieves closed-loop control of production management by updating the equipment scheduling strategy library and optimizing the strategy generation logic using historical data, thereby continuously improving management level and efficiency. Moreover, through digital modeling and real-time data collection, the production process becomes more transparent, making it easier to comprehensively monitor and evaluate the production status. Furthermore, by optimizing scheduling strategies and resource allocation, unnecessary production delays and material accumulation are reduced, thereby lowering production and operating costs. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart of the overall method in one embodiment of the present invention; Figure 2 This is a schematic diagram of the overall system architecture in one embodiment of the present invention.

[0016] In the diagram: 1. Area division unit; 2. Status detection unit; 3. Startup determination unit; 4. Anomaly analysis unit; 5. Target scheduling unit; 6. Production adjustment unit. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 This invention provides a technical solution: a production management method based on multi-region management, comprising: S1. Digitally model the physical layout of the production workshop to obtain a digital model of the workshop, and divide the production area into multiple management sub-areas based on the digital model of the workshop. S2. Real-time acquisition of production equipment status information and material flow information in each management sub-region, and generation of regional status information for each management sub-region based on the production equipment status information and material flow information; S3. Based on the regional status information, determine whether the startup conditions of the production management system are met; the startup conditions include that the initialization status of each management sub-region is completed and the running level is greater than the first preset running threshold. S4. In response to the fulfillment of the start-up conditions, the system analyzes the regional status information according to the preset regional anomaly judgment rules, identifies the abnormal regions with production bottlenecks, and determines the location information and bottleneck type of the abnormal regions. S5. Based on the location information and bottleneck type of the abnormal area, and combined with the preset equipment scheduling strategy library, generate a target scheduling strategy for the abnormal area; the target scheduling strategy includes equipment movement path or task change instruction. S6. Distribute the target scheduling strategy to the corresponding production equipment or management terminal to adjust production activities in abnormal areas and collect the adjusted area status data in real time.

[0019] It should be noted that by digitally modeling the physical layout of the production workshop, a virtual digital model of the workshop is constructed. This model reflects the actual structure, equipment location, and material flow path within the workshop. Based on this digital model, the production area is divided into multiple management sub-areas. Each sub-area can be managed independently, facilitating the monitoring and scheduling of production activities in different areas. Real-time acquisition of production equipment status information (such as operating status, fault information, etc.) and material flow information (such as material inflow and outflow, inventory level, etc.) in each management sub-region; based on the collected equipment status and material flow information, generate regional status information for each management sub-region, which is used to assess the production status of the region; Based on the generated regional status information, the system determines whether the startup conditions of the production management system are met. The startup conditions include: the initialization status of all managed sub-regions has been completed, and the operating level of each sub-region exceeds the preset first operating threshold (i.e., a certain production efficiency or capacity is achieved). Once the activation conditions are met, the system will analyze the regional status information according to the preset regional anomaly judgment rules to identify abnormal regions with production bottlenecks; determine the location of these abnormal regions and the bottleneck type (e.g., equipment failure, material shortage, workflow disruption, etc.) in order to take subsequent measures. For the identified abnormal areas, a corresponding target scheduling strategy is generated by combining the preset equipment scheduling strategy library. The target scheduling strategy may include equipment movement paths (e.g., moving a piece of equipment to another area to reduce its workload) or task change instructions (e.g., adjusting the work task of a piece of equipment to improve overall production efficiency). The generated target scheduling strategy is sent to the corresponding production equipment or management terminal to adjust production activities in abnormal areas; the adjusted area status data is collected in real time to evaluate the effectiveness of the scheduling strategy.

[0020] In an optional embodiment, after adjusting production activities within the abnormal area and collecting the adjusted area status data in real time, the method further includes: Based on the adjusted regional status data and the regional status information before adjustment, determine whether the production efficiency improvement index is greater than the preset efficiency threshold. When the production efficiency improvement index is greater than the preset efficiency threshold, the abnormal area is confirmed to have returned to normal, and the equipment scheduling strategy library is updated according to the status of the restored area.

[0021] It should be noted that after adjustments are made to the abnormal area (such as equipment relocation, task change, etc.), the system will continue to monitor the status of the area in real time; these status data may include multiple indicators such as production speed, equipment uptime, failure occurrence, and material flow efficiency. The adjusted regional status data is compared with the regional status information before the adjustment to calculate the production efficiency improvement index. This index is usually derived through some specific formula or algorithm and reflects the change in efficiency before and after the adjustment. For example, the production efficiency improvement index can be the percentage change of a key performance indicator (KPI), such as output, equipment utilization rate or production cycle time. Once the productivity improvement index is calculated, the system compares it with a preset efficiency threshold. This preset efficiency threshold is set based on historical data, industry standards, or corporate goals and is used to measure whether productivity has reached an acceptable level of improvement. If the production efficiency improvement index is greater than the preset efficiency threshold, the system will consider that the production status of the abnormal area has returned to normal; this means that after adjustment, the production efficiency of the area has reached a satisfactory level and can operate stably. After confirming that the abnormal area has returned to normal, the system will also update the equipment scheduling strategy library according to the status of the restored area. The purpose of this step is to ensure that future production management can refer to or apply the currently successful scheduling strategies so as to respond and adjust quickly in similar situations. The update may include optimized equipment scheduling schemes, new best practices, and records of successful cases.

[0022] In an optional embodiment, determining whether the startup conditions of the production management system are met based on the area status information includes: Obtain the initialization status and operational status of each managed sub-region from the regional status information; Determine whether the initialization status of each management sub-region is complete. If so, then it is further determined whether the total number of the first target areas is not less than a preset value; the first target area is the area whose running degree is greater than the first preset running threshold and whose position attribute is the left area or the right area. If the initialization status of each management sub-region is not all complete initialization, then determine whether the running status of each management sub-region is equal to the second preset running threshold; the second preset running threshold is greater than the first preset running threshold. When the total number of the first target areas is not less than a preset value or the operating level of each managed sub-area is equal to the second preset operating threshold, the start-up conditions of the production management system are confirmed to be met.

[0023] It should be noted that regional status information is collected from each management sub-region; this information includes the initialization status (i.e., whether initialization is complete) and operational status (i.e., current production efficiency or output level) of each sub-region. Check the initialization status of each management sub-region to ensure that each region has completed initialization; if the initialization status of all sub-regions is "initialization complete", then proceed to the next step. After confirming the initialization status of all managed sub-regions, the system will further check the conditions of the "first target region". The first target region is defined as: the region whose operation level is greater than the first preset operation threshold and whose location attribute is the left zone or the right zone. The total number of first target regions that meet these conditions is counted and it is determined whether the number is not less than a preset value (this preset value is set in advance to determine whether sufficient production activities exist). If the initialization status of any management sub-region is not completed, the system will then determine whether the running status of each management sub-region is equal to the second preset running threshold. The second preset running threshold is a standard higher than the first preset running threshold, indicating that the system expects that under certain circumstances, even if the initialization is not completed, each region should achieve a high running efficiency. If any of the following conditions are met, the system confirms that the startup conditions of the production management system have been met: the total number of the first target areas is not less than the preset value, which means that there are enough operating areas to support the entire production process; the operating level of each management sub-area is equal to the second preset operating threshold, indicating that even if the initialization is not completed, the production efficiency has still reached an acceptable high level.

[0024] In an optional embodiment, regional status information for each management sub-region is generated based on production equipment status information and material flow information, including: Based on the status information of production equipment, determine the operating load rate and failure downtime probability of equipment in each management sub-area; Based on the material flow information, determine the material accumulation and flow rate in each management sub-area; The system integrates operating load rate, failure downtime probability, material accumulation, and turnover speed to generate regional status information that characterizes the health of each management sub-region. The regional status information also includes the location attributes of each production area; the location attributes include left area location, right area location, left rear area location, or right rear area location.

[0025] It should be noted that the operating load rate refers to the ratio between the actual load of equipment operating within a certain period of time and its maximum carrying capacity. By analyzing the status of production equipment (such as current output, set capacity, etc.), the operating load rate of equipment in each management sub-area can be calculated. This helps to understand the utilization efficiency of the equipment. Downtime probability refers to the likelihood of equipment failing and shutting down during operation. By monitoring historical failure data and maintenance records, the downtime probability of equipment within a managed sub-area can be estimated. This information helps assess equipment reliability and maintenance needs. Material accumulation refers to the amount of material that has not been processed or transferred in a certain management sub-area. By monitoring the entry and exit of materials, the system can calculate the material accumulation in each management sub-area. This indicator can reflect the smoothness of the production process and potential bottlenecks. Flow rate refers to the speed at which materials move within each managed sub-area, usually expressed as the amount of material moved per unit time. By tracking the movement of materials in the production process, the flow rate can be determined, thereby judging the efficiency of the production line. The various indicators obtained above (operating load rate, failure downtime probability, material accumulation and turnover speed) are integrated to form comprehensive regional status information. This process may include weighted averaging, standardization or other algorithms to generate a comprehensive indicator or score that characterizes the health of each management sub-region. This regional status information can intuitively display the operating status of each management sub-region, help managers identify problem areas and improve the accuracy of decision-making. The regional status information also needs to include the location attributes of each production area. These location attributes can be: left area location; right area location; left rear area location; right rear area location. The addition of location attributes is to provide more detailed contextual information, so that the spatial layout of the area can be taken into account during management and scheduling.

[0026] In an optional embodiment, the regional status information is analyzed according to a preset regional anomaly determination rule to identify abnormal regions with production bottlenecks, including: Based on the operating load rate and material accumulation in the regional status information, determine whether each managed sub-region is in a high load or high inventory state; When a management sub-region is under high load or high inventory, the system determines whether the region meets the preset bottleneck triggering conditions based on the region's failure downtime probability and turnover rate. When a management sub-region meets a preset bottleneck triggering condition, the management sub-region is identified as an abnormal region with a production bottleneck. At the same time, the location attributes of the abnormal area are obtained to determine the specific location of the abnormal area on the production line.

[0027] It should be noted that the production status of each management sub-region is judged based on two key indicators in the regional status information: operating load rate and material accumulation amount. If the operating load rate of a management sub-region is close to or reaches its maximum carrying capacity, it indicates that the region is operating at high load. If the material accumulation amount in a management sub-region is higher than the preset threshold, it indicates that the region may face high inventory problems. Each management sub-area is checked one by one, and the "high load" or "high inventory" status is determined based on the above two indicators. If a management sub-area is found to meet the conditions of high load (high operating load rate) or high inventory (large material accumulation), the system will conduct further analysis on this area. When a management sub-area is identified as being under high load or high inventory, the system will further analyze two additional indicators for that area: failure downtime probability and turnover rate; Failure downtime probability: If the failure downtime probability of the area is high, it means that the equipment reliability is low and may cause production interruption at any time; Turnover rate: If the turnover rate is low, it indicates that the material movement efficiency in the area is poor, which may lead to material backlog. If the above two indicators (probability of downtime due to failure and turnover speed) are combined, and the management sub-area meets the preset bottleneck triggering conditions, this is usually a comprehensive evaluation standard, indicating that there is a serious problem with the production efficiency of the area, which may lead to a decline in the overall efficiency of the production line. Once a management sub-region is determined to meet the bottleneck triggering conditions, the system marks it as an "abnormal region with a production bottleneck." This identification helps with subsequent processing and decision-making, allowing managers to prioritize and resolve these problematic regions. After identifying abnormal areas where production bottlenecks exist, the system also needs to obtain the location attributes of these areas; these location attributes can be left area, right area, left rear area, or right rear area; this information helps managers understand the specific location of the abnormal area on the production line, so as to take corresponding measures to adjust, optimize or intervene, and ensure the smooth flow of production.

[0028] In an optional embodiment, based on the location information and bottleneck type of the abnormal area, and in conjunction with a preset equipment scheduling strategy library, a target scheduling strategy for the abnormal area is generated, including: Based on the location information of the abnormal area, candidate support areas that are adjacent to the abnormal area and match the location attributes are selected from all management sub-areas; Based on the bottleneck type, candidate scheduling schemes for resolving that type of bottleneck are matched from the equipment scheduling strategy library; The final target scheduling strategy is determined based on the equipment capabilities of the candidate support areas and the execution costs of the candidate scheduling schemes. The equipment capacity is determined by the operating load rate and equipment performance parameters in the area status information generated in the previous step.

[0029] It should be noted that determining the location attributes of the identified abnormal areas (such as left area, right area, left rear area, or right rear area) provides the basis for subsequent filtering and matching. Based on the location information of the abnormal area, the system will filter out candidate support areas that are adjacent to the abnormal area and match the location attributes from all management sub-areas. For example, if the abnormal area is located in the left area, the system may select the area adjacent to the left area (such as the left rear area or the left front area) as a candidate support area. These candidate areas will be evaluated to determine whether they can provide support to alleviate the production bottleneck of the abnormal area. Based on the bottleneck type of the abnormal area (such as high load, high inventory, etc.), the system searches the equipment scheduling strategy library for suitable candidate scheduling solutions to resolve the bottleneck of that type. The equipment scheduling strategy library contains preset strategies for various production bottlenecks, such as adjusting the equipment running sequence, adding additional equipment, or reconfiguring the production process. After identifying candidate support areas and candidate scheduling schemes, the system evaluates the equipment capacity of each candidate support area. This capacity is typically determined by the operating load rate and equipment performance parameters in the previously generated area status information. For example, if the equipment operating load rate of a support area is low, it indicates that it is capable of handling more work. Consider the execution costs of candidate scheduling schemes, including time, resource consumption, and potential output loss; these factors directly affect the final scheduling decision. By considering the equipment capabilities of candidate support areas and the execution costs of candidate scheduling schemes, the system will determine a final target scheduling strategy. This strategy aims to effectively resolve production bottlenecks in abnormal areas while minimizing execution costs and maximizing production efficiency.

[0030] In an optional embodiment, the final target scheduling strategy is determined based on the device capabilities of the candidate support areas and the execution cost of the candidate scheduling schemes, including: Obtain the number of available devices and their performance parameters within the candidate support area; Based on the candidate scheduling schemes, calculate the scheduling time required for the equipment to move from the candidate support area to the abnormal area and the impact on the production in the original area; When the equipment performance parameters meet the production needs of the abnormal area and the impact value is less than the preset impact threshold, the candidate scheduling scheme is determined as the target scheduling strategy. The issuance and execution of the target scheduling strategy depends on the scheduling time and impact value data determined in the previous step.

[0031] It should be noted that after confirming the candidate support areas, the system will first collect the number and performance parameters of available devices in these areas; these performance parameters may include the device's processing power, operating speed, failure rate, etc., and this information is crucial for subsequent decision-making. Based on the selected candidate scheduling scheme, the system needs to calculate the scheduling time required for the device to move from the candidate support area to the abnormal area; this time typically includes the device preparation time, the movement time, and the time required to put the device into use in the new area. Assess the impact of this scheduling on production in the original region; this may involve calculating the extent to which production efficiency in the region decreases during the equipment's absence, such as the amount of output reduction or time delay; this impact value is an important indicator for determining whether the scheduling plan is feasible. Once the equipment performance parameters are obtained, the system needs to determine whether these parameters meet the production requirements of the abnormal area. For example, if the abnormal area requires specific production capacity, but the performance of the available equipment is insufficient to meet this requirement, the candidate scheduling scheme will be excluded. Check if the impact value is less than the preset impact threshold; the impact threshold is a predefined standard used to evaluate the impact of the scheduling scheme on the production of other areas; if the impact value exceeds this threshold, it may cause serious disruption to the production of the original area, making the scheduling scheme unsuitable. If the equipment performance parameters meet the production needs of the abnormal area and the impact value is less than the preset impact threshold, the system will determine the candidate scheduling scheme as the target scheduling strategy; this means that under the premise of balancing production efficiency and resource allocation, an optimal solution is selected to solve the production bottleneck in the abnormal area. The final implementation of the target scheduling strategy will depend on the previously determined scheduling time and impact value data. This data will guide relevant personnel or systems in the specific operations of equipment scheduling, including when to start moving equipment and how to coordinate resources, to ensure that the impact on overall production can be effectively controlled during implementation.

[0032] In an optional embodiment, determining whether the production efficiency improvement index is greater than a preset efficiency threshold based on the adjusted regional state data and the regional state information before adjustment includes: Collect the material output and effective equipment operating time within the preset time period after adjustment, and use it as the adjusted regional status data. Calculate the baseline production efficiency based on the historical material output and historical equipment operation time in the area status information before adjustment. Calculate the current production efficiency based on the adjusted material output and effective equipment operating time; Calculate the difference between the current production efficiency and the benchmark production efficiency, and determine the ratio of this difference to the benchmark production efficiency as the production efficiency improvement index; The production efficiency improvement index is compared with a preset efficiency threshold to determine whether abnormal areas have returned to normal.

[0033] It should be noted that after the adjustment measures are implemented, the system will collect two key indicators related to the abnormal area within a preset time period: material output (i.e., the number of products produced during this period) and equipment effective operating time (i.e., the effective time that the equipment is actually put into production, excluding ineffective time such as downtime or failure); these data represent the status of the area after the adjustment. Based on the regional status information before adjustment, the system will extract historical material output and historical equipment operating time; this historical data will be used to calculate the baseline production efficiency, that is, the production efficiency before adjustment; this baseline value provides a reference point for subsequent evaluation. The current production efficiency is calculated based on the adjusted material output and effective equipment operating time. The current production efficiency is an important indicator reflecting the adjusted production status. To assess the effectiveness of the adjustments, the system calculates the difference between the current production efficiency and the baseline production efficiency, and determines the ratio of this difference to the baseline production efficiency as the production efficiency improvement index. This index reflects the degree of impact of the adjustment measures on production efficiency; a positive value indicates improvement, while a negative value indicates deterioration. The calculated production efficiency improvement index is compared with a preset efficiency threshold. The preset efficiency threshold is a predefined standard used to determine whether a satisfactory improvement effect has been achieved. If the production efficiency improvement index is greater than this threshold, the adjustment measures can be considered successful and the production efficiency of the abnormal area has been restored or improved. Otherwise, it indicates that the adjustment measures may not have achieved the expected effect.

[0034] In an optional embodiment, in response to a production efficiency improvement index greater than a preset efficiency threshold, it is confirmed that the abnormal area has returned to normal, and the equipment scheduling strategy library is updated according to the status of the restored area, including: When it is determined that the production efficiency improvement index is greater than the preset efficiency threshold, it is confirmed that the bottleneck in the abnormal area has been eliminated and returned to normal. Extract the target scheduling strategy used for the abnormal area and the corresponding actual improvement effect data; the actual improvement effect data comes from the adjusted area status data. The target scheduling strategy and actual improvement effect data are used as new samples and added to the equipment scheduling strategy library; The updated equipment scheduling strategy library is used to optimize the next strategy generation logic in order to achieve closed-loop control of production management.

[0035] It should be noted that when the production efficiency improvement index is greater than the preset efficiency threshold, the system determines that the production bottleneck in the abnormal area has been eliminated and the area has returned to normal operation. This means that the previous production problems (such as equipment failure, resource shortage, etc.) have been effectively resolved and the production efficiency has returned to the expected level. After confirming that the abnormal area has returned to normal, the system will extract the target scheduling strategy used for that area; this strategy was formulated in the previous scheduling process to deal with specific production bottlenecks. Collect and record status data of the adjusted area to obtain data on the actual improvement effect; these data may include the increase in production efficiency, the increase in output, the improvement in equipment utilization, etc., reflecting the real effect after implementing the target scheduling strategy; The extracted target scheduling strategies and corresponding actual improvement effect data are added to the equipment scheduling strategy library as new samples. This step is very important because it incorporates successful experiences and data feedback from actual operations into the strategy library, providing a reference for future scheduling decisions. The updated equipment scheduling strategy library is used to optimize the next strategy generation logic. By analyzing newly added samples, the system can identify which strategies perform well in similar situations, and thus prioritize these strategies in future scheduling. This forms a continuous improvement process, enabling production management to achieve closed-loop control. That is, by continuously learning and adjusting strategies, the system can gradually improve production efficiency and better cope with possible future anomalies.

[0036] Example 2, please refer to Figure 2 This invention provides a technical solution: a production management system based on multi-region management, applicable to the aforementioned production management method based on multi-region management, comprising: Area division unit 1 is used to digitally model the physical layout of the production workshop to obtain a digital model of the workshop, and to divide the production area into multiple management sub-areas based on the digital model of the workshop. Status detection unit 2 is used to acquire the status information of production equipment and material flow information in each management sub-area in real time, and generate the regional status information of each management sub-area based on the status information of production equipment and material flow information. The startup determination unit 3 is used to determine whether the startup conditions of the production management system are met based on the area status information. The startup conditions include that the initialization status of each management sub-area is completed and the running degree is greater than the first preset running threshold. Anomaly analysis unit 4 is used to respond to the fulfillment of the start-up conditions, analyze the regional status information according to the preset regional anomaly judgment rules, identify the abnormal regions with production bottlenecks, and determine the location information and bottleneck type of the abnormal regions. The target scheduling unit 5 is used to generate a target scheduling strategy for the abnormal area based on the location information and bottleneck type of the abnormal area, combined with a preset equipment scheduling strategy library; the target scheduling strategy includes equipment movement path or task change instruction. Production adjustment unit 6 is used to send the target scheduling strategy to the corresponding production equipment or management terminal to adjust the production activities in the abnormal area and collect the adjusted area status data in real time.

[0037] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A production management method based on multi-region management, characterized in that, include: The physical layout of the production workshop is digitally modeled to obtain a digital model of the workshop, and the production area is divided into multiple management sub-areas based on the digital model of the workshop. Real-time acquisition of production equipment status information and material flow information in each management sub-region, and generation of regional status information for each management sub-region based on the production equipment status information and material flow information; Based on the regional status information, determine whether the startup conditions of the production management system are met; the startup conditions include that the initialization status of each management sub-region is completed and the running level is greater than the first preset running threshold. In response to the fulfillment of the start-up conditions, the system analyzes the regional status information according to the preset regional anomaly judgment rules, identifies the abnormal regions with production bottlenecks, and determines the location information and bottleneck type of the abnormal regions. Based on the location information and bottleneck type of the abnormal area, and combined with the preset equipment scheduling strategy library, a target scheduling strategy for the abnormal area is generated; the target scheduling strategy includes equipment movement path or task change instruction. The target scheduling strategy is sent to the corresponding production equipment or management terminal to adjust production activities in abnormal areas and collect the adjusted area status data in real time.

2. The production management method based on multi-region management according to claim 1, characterized in that, After adjusting production activities within the abnormal area and collecting real-time data on the adjusted area status, the method further includes: Based on the adjusted regional status data and the regional status information before adjustment, determine whether the production efficiency improvement index is greater than the preset efficiency threshold. When the production efficiency improvement index is greater than the preset efficiency threshold, the abnormal area is confirmed to have returned to normal, and the equipment scheduling strategy library is updated according to the status of the restored area.

3. The production management method based on multi-region management according to claim 2, characterized in that, Based on the regional status information, determine whether the startup conditions of the production management system are met, including: Obtain the initialization status and operational status of each managed sub-region from the regional status information; Determine whether the initialization status of each management sub-region is complete. If so, then it is further determined whether the total number of the first target areas is not less than a preset value; the first target area is the area whose running degree is greater than the first preset running threshold and whose position attribute is the left area or the right area. If the initialization status of each management sub-region is not all complete initialization, then determine whether the running status of each management sub-region is equal to the second preset running threshold; the second preset running threshold is greater than the first preset running threshold. When the total number of the first target areas is not less than a preset value or the operating level of each managed sub-area is equal to the second preset operating threshold, the start-up conditions of the production management system are confirmed to be met.

4. The production management method based on multi-region management according to claim 3, characterized in that, Based on production equipment status information and material flow information, generate area status information for each management sub-area, including: Based on the status information of production equipment, determine the operating load rate and failure downtime probability of equipment in each management sub-area; Based on the material flow information, determine the material accumulation and flow rate in each management sub-area; The system integrates operating load rate, failure downtime probability, material accumulation, and turnover speed to generate regional status information that characterizes the health of each management sub-region. The regional status information also includes the location attributes of each production area; the location attributes include left area location, right area location, left rear area location, or right rear area location.

5. A production management method based on multi-region management according to claim 4, characterized in that, Based on preset regional anomaly judgment rules, the regional status information is analyzed to identify abnormal regions with production bottlenecks, including: Based on the operating load rate and material accumulation in the regional status information, determine whether each managed sub-region is in a high load or high inventory state; When a management sub-region is under high load or high inventory, the system determines whether the region meets the preset bottleneck triggering conditions based on the region's failure downtime probability and turnover rate. When a management sub-region meets a preset bottleneck triggering condition, the management sub-region is identified as an abnormal region with a production bottleneck. At the same time, the location attributes of the abnormal area are obtained to determine the specific location of the abnormal area on the production line.

6. The production management method based on multi-region management according to claim 5, characterized in that, Based on the location information and bottleneck type of the abnormal area, and in conjunction with a pre-defined equipment scheduling strategy library, a target scheduling strategy for the abnormal area is generated, including: Based on the location information of the abnormal area, candidate support areas that are adjacent to the abnormal area and match the location attributes are selected from all management sub-areas; Based on the bottleneck type, candidate scheduling schemes for resolving that type of bottleneck are matched from the equipment scheduling strategy library; The final target scheduling strategy is determined based on the equipment capabilities of the candidate support areas and the execution costs of the candidate scheduling schemes. The equipment capacity is determined by the operating load rate and equipment performance parameters in the area status information generated in the previous step.

7. A production management method based on multi-region management according to claim 6, characterized in that, Based on the equipment capabilities of the candidate support areas and the execution costs of the candidate scheduling schemes, the final target scheduling strategy is determined, including: Obtain the number of available devices and their performance parameters within the candidate support area; Based on the candidate scheduling schemes, calculate the scheduling time required for the equipment to move from the candidate support area to the abnormal area and the impact on the production in the original area; When the equipment performance parameters meet the production needs of the abnormal area and the impact value is less than the preset impact threshold, the candidate scheduling scheme is determined as the target scheduling strategy. The issuance and execution of the target scheduling strategy depends on the scheduling time and impact value data determined in the previous step.

8. A production management method based on multi-region management according to claim 7, characterized in that, Based on the adjusted regional status data and the regional status information before adjustment, determine whether the production efficiency improvement index is greater than the preset efficiency threshold, including: Collect the material output and effective equipment operating time within the preset time period after adjustment, and use it as the adjusted regional status data. Calculate the baseline production efficiency based on the historical material output and historical equipment operation time in the area status information before adjustment. Calculate the current production efficiency based on the adjusted material output and effective equipment operating time; Calculate the difference between the current production efficiency and the benchmark production efficiency, and determine the ratio of this difference to the benchmark production efficiency as the production efficiency improvement index; The production efficiency improvement index is compared with a preset efficiency threshold to determine whether abnormal areas have returned to normal.

9. A production management method based on multi-region management according to claim 8, characterized in that, When the production efficiency improvement index exceeds a preset efficiency threshold, the system confirms that the abnormal area has returned to normal and updates the equipment scheduling strategy library based on the status of the restored area, including: When it is determined that the production efficiency improvement index is greater than the preset efficiency threshold, it is confirmed that the bottleneck in the abnormal area has been eliminated and returned to normal. Extract the target scheduling strategy used for the abnormal area and the corresponding actual improvement effect data; the actual improvement effect data comes from the adjusted area status data. The target scheduling strategy and actual improvement effect data are used as new samples and added to the equipment scheduling strategy library; The updated equipment scheduling strategy library is used to optimize the next strategy generation logic in order to achieve closed-loop control of production management.

10. A production management system based on multi-region management, applicable to the production management method based on multi-region management as described in any one of claims 1-9, characterized in that, include: The area division unit is used to digitally model the physical layout of the production workshop to obtain a digital model of the workshop, and to divide the production area into multiple management sub-areas based on the digital model of the workshop. The status detection unit is used to acquire the status information of production equipment and material flow information in each management sub-area in real time, and generate the regional status information of each management sub-area based on the status information of production equipment and material flow information. The startup determination unit is used to determine whether the startup conditions of the production management system are met based on the area status information. The startup conditions include that the initialization status of each management sub-area is completed and the running level is greater than the first preset running threshold. The anomaly analysis unit is used to analyze the regional status information according to the preset regional anomaly judgment rules in response to the fulfillment of the start conditions, identify the abnormal regions with production bottlenecks, and determine the location information and bottleneck type of the abnormal regions. The target scheduling unit is used to generate a target scheduling strategy for the abnormal area based on the location information and bottleneck type of the abnormal area, combined with a preset equipment scheduling strategy library; the target scheduling strategy includes equipment movement paths or task change instructions. The production adjustment unit is used to send the target scheduling strategy to the corresponding production equipment or management terminal to adjust the production activities in the abnormal area and collect the adjusted area status data in real time.

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