Industrial internet platform and production collaborative management method

Abstract

The invention provides an industrial internet platform and a production collaborative management method, and belongs to the technical field of production management, and the method specifically comprises the steps: carrying out the determination of an available production load based on a production order and production data under different production loads, obtaining the historical fault data of different production devices, and carrying out the processing of the historical fault data; determining the optimal production load in the available production loads by combining the deviation conditions of the production loads corresponding to different historical fault data and different available production loads and the production orders, and carrying out the production scheduling processing of the factory through the optimal production load. The adjustment strategy of the production load is determined according to the change condition of the order data and the analysis result of the monitoring data of the production equipment in the production processing process, and the production processing efficiency is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of production management, and in particular relates to an industrial Internet platform and a production collaborative management method. Background Art

[0002] In order to realize the production management of kitchen utensils, kitchen and bathroom appliances, etc., a multi-objective function of green scheduling optimization is constructed in the invention patent application CN201911127154.6 "Green Scheduling Optimization Method for Intelligent Manufacturing Workshops with Complex Human-Machine Coupling". A greedy strategy is formulated according to the objective function of the problem, and the model is solved by improving the non-dominated sorting genetic algorithm to realize the production scheduling management of the intelligent manufacturing workshop. However, the above technical solution has the following technical problems: In the process of production collaborative management, the existing technical solutions ignore the generation of differentiated production management strategies based on the failure probabilities of different production equipment under different production loads. For production equipment, there is a certain deviation in the probability of failure under different operating loads. Therefore, in the process of production collaborative management, the failure probability of production equipment under different operating loads is ignored, and the efficiency of production processing cannot be guaranteed.

[0003] In response to the above technical problems, this application specifically provides an industrial Internet platform and a production collaborative management method. Summary of the invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present application provides a production collaborative management method, specifically comprising: S1 takes the current production order as the basis and combines the production data under the maximum production load and the defect data to determine that the management optimization of the factory's production load can be carried out, and then proceeds to the next step; S2: obtaining historical fault data of the production equipment of the factory during the production process, and determining, based on the historical fault data, that the production operation status of the factory does not meet the requirements, determining the available production load based on the production order and the production data under different production loads; S3 obtains historical fault data of different production equipment, and determines the optimal production load among the available production loads by combining the deviations between the production loads corresponding to the different historical fault data and the different available production loads and the production order; S4 performs production scheduling processing of the factory based on the optimal production load, and determines the adjustment strategy of the production load based on the changes in order data and the analysis results of the monitoring data of the production equipment during the production process.

[0005] The beneficial effects of the present invention are: Based on the current production orders, production data under the maximum production load and bad data, determine whether the factory's production load management can be optimized. This realizes accurate evaluation of the generation and processing time of the current production order based on the production data under the maximum production load and bad data. This avoids the technical problem of production processing efficiency failing to meet requirements when the production processing time under the maximum production load still does not meet requirements and then performs production load management optimization. This also lays the foundation for generating differentiated generation load adjustment strategies based on differences in production orders.

[0006] The production load adjustment strategy is determined based on the changes in order data and the analysis results of the monitoring data of the production equipment during the production process. It not only takes into account the differences in the needs for production load adjustment caused by the differences in the changes in order data, but also takes into account the differences in the probability of abnormalities in production equipment caused by the differences in monitoring data. It realizes the determination of the production load adjustment strategy based on the operating reliability of the production equipment and the changes in the production orders, thereby ensuring the reliability and efficiency of the production process.

[0007] A further technical solution is that the production data includes an average daily output of the product under the maximum production load.

[0008] A further technical solution is that the defective data includes the defective rate and the number of defective products on different dates under the maximum production load.

[0009] A further technical solution is to determine whether the management optimization of the production load of the factory can be carried out, including: Determine the average daily output of products under the maximum production load and the average daily quantity ratio in different defect rate ranges based on the production data and defect data under the maximum production load; Based on the average daily output of the product, the benchmark defective rate in different defective rate ranges, and in combination with the production order, determine the corresponding production processing time in different defective rate ranges; Based on the corresponding production processing time in different defect rate ranges and the average daily quantity ratio in different defect rate ranges, determine whether the management optimization of the factory's production load can be carried out.

[0010] A further technical solution is that the reference defective rate within the defective rate interval is the average value of the defective rate endpoints corresponding to the defective rate interval.

[0011] A further technical solution is that the method for determining the adjustment strategy of the production load is: Determine the changed quantity of the production order based on the change of the order data, and determine the changed quantity proportional factor based on the ratio of the changed quantity to the product quantity corresponding to the production order; According to the analysis results of the monitoring data of the production equipment during the production process, the production equipment whose monitoring data is within the preset monitoring data interval corresponding to the production equipment is determined and regarded as the suspected abnormal production equipment; Based on the ratio of the change quantity proportional factor to the quantity of the suspected abnormal production equipment, an adjustment demand coefficient is determined, and the adjustment strategy of the production load is determined using the adjustment demand coefficient.

[0012] A further technical solution is to use the adjustment demand coefficient to determine the adjustment strategy of the production load, which specifically includes: When the adjustment demand coefficient is not greater than the preset demand coefficient threshold, it is determined that no production load adjustment is required; When the adjustment demand coefficient is greater than the preset demand coefficient threshold, it is determined whether the adjustment demand coefficient is within the preset adjustment demand coefficient range. If so, the production load is switched to the maximum production load for production scheduling of the factory. If not, the switching target of the available production load to which the production load is switched is determined based on the preset adjustment factor corresponding to the production demand coefficient.

[0013] A further technical solution is that the switching target of the available production load is determined based on the product of the preset adjustment factor and the production load, and the available production load closest to the adjusted production load is used as the switching target of the available production load.

[0014] In a second aspect, the present application provides an industrial Internet platform, which adopts the above-mentioned production collaborative management method, specifically including: Available load determination module, optimal load generation module, adjustment strategy output module; The available load determination module is responsible for determining the available production load based on the production order and the production data under different production loads; The optimal load generation module is responsible for determining the optimal production load among the available production loads; The adjustment strategy output module is responsible for determining the adjustment strategy of the production load.

[0015] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0016] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings; Figure 1 It is a flowchart of a production collaborative management method; Figure 2 It is a flow chart that determines the management optimization of the production load of the factory; Figure 3 It is a flow chart to determine that the production operation status of the factory does not meet the requirements; Figure 4 is a flow chart of a method for determining an optimal production load; Figure 5 is a flow chart of a method for determining a production load adjustment strategy; Figure 6 It is a framework diagram of an industrial Internet platform. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0019] In the present application, the optimal production load in the production load is determined by utilizing the fault data and order data of the production equipment under different production loads, which not only meets the needs of the production orders, but also avoids the technical problem of the production processing efficiency not meeting the requirements due to the failure data under the production load not meeting the requirements.

[0020] The average daily output and average defective rate of products under the maximum production load are determined based on the production data and defective data under the maximum production load. The production processing time of the production order is determined based on the average daily output and average defective rate. When the production processing time is greater than the preset time threshold, it is determined that management optimization of the factory's production load cannot be performed.

[0021] The historical failure data of different production equipment in the production process is used to determine the historical failure times of different production equipment in the production process, and the production equipment with hidden dangers in the production equipment is determined based on the historical failure times. When the number of production equipment with hidden dangers in the production equipment accounts for more than 0.3, it is determined that the production operation status of the factory does not meet the requirements.

[0022] The available production load is the production load whose production processing time of the production order is within the preset time range.

[0023] The optimal production load is the available production load with the smallest ratio between the number of production equipment with historical failure data and the production processing time of the production order.

[0024] The changed quantity of the production order is determined based on the changes in the order data, and the changed quantity proportional factor is determined based on the ratio of the changed quantity to the number of products corresponding to the production order. The production equipment whose monitoring data is within the preset monitoring data interval corresponding to the production equipment is regarded as suspected abnormal production equipment. Based on the ratio of the changed quantity proportional factor to the number of suspected abnormal production equipment, the adjustment demand coefficient is determined, and the adjustment strategy of the production load is determined using the adjustment demand coefficient.

[0025] Example 1 like Figure 1 As shown, the present application provides a first aspect, which provides a production collaborative management method, specifically comprising: S1 takes the current production order as the basis and combines the production data under the maximum production load and the defect data to determine that the management optimization of the factory's production load can be carried out, and then proceeds to the next step; Furthermore, the production data includes an average daily output of the product under the maximum production load.

[0026] Specifically, the defective data includes the defective rate and the number of defective products on different dates under the maximum production load.

[0027] Specifically, Figure 2 As shown, it is determined that the management and optimization of the factory's production load can be carried out, including: Determine the average daily output of products under the maximum production load and the average daily quantity ratio in different defect rate ranges based on the production data and defect data under the maximum production load; Based on the average daily output of the product, the benchmark defective rate in different defective rate ranges, and in combination with the production order, determine the corresponding production processing time in different defective rate ranges; Based on the corresponding production processing time in different defect rate ranges and the average daily quantity ratio in different defect rate ranges, determine whether the management optimization of the factory's production load can be carried out.

[0028] Optionally, the benchmark defective rate within the defective rate interval is the average value of the defective rate endpoints corresponding to the defective rate interval.

[0029] It is understandable that based on the corresponding production processing time in different defect rate intervals and the daily average quantity ratio in different defect rate intervals, it is determined whether the management optimization of the factory's production load can be carried out, specifically including: When the corresponding production processing time in different defect rate intervals is greater than the preset processing time threshold, it is determined that the management optimization of the production load of the factory cannot be performed; When there is a defect rate interval whose corresponding production processing time is not greater than the preset processing time threshold, it is determined whether the sum of the daily average quantity proportions of the defect rate intervals whose corresponding production processing time is not greater than the preset processing time threshold is greater than the preset daily average quantity proportion. If so, it is determined that the management optimization of the factory's production load can be carried out. If not, it is determined that the management optimization of the factory's production load cannot be carried out.

[0030] Furthermore, when it is determined that management optimization of the production load of the factory cannot be performed, production scheduling processing of the factory is performed with the maximum production load.

[0031] In another possible embodiment, determining that management optimization of the production load of the factory can be performed specifically includes: Determine the average daily output and average defect rate of products under the maximum production load based on the production data and defect data under the maximum production load; Determine the production processing time based on the average daily output and average defect rate of the product and in combination with the production order; Based on the production processing time, determine whether the management optimization of the factory's production load can be carried out.

[0032] Furthermore, when the production processing time is longer than a preset time threshold, it is determined that management optimization of the production load of the factory cannot be performed.

[0033] S2: obtaining historical fault data of the production equipment of the factory during the production process, and determining, based on the historical fault data, that the production operation status of the factory does not meet the requirements, determining the available production load based on the production order and the production data under different production loads; It should be noted that the historical failure data of the production equipment during the production process includes the historical failure times of the production equipment and the production loads corresponding to different historical failure times.

[0034] Specifically, Figure 3 As shown, determining that the production operation status of the factory does not meet the requirements specifically includes: Determine the number of historical failures of different production equipment during the production process using historical failure data of different production equipment during the production process; Determine the production equipment with hidden dangers among the production equipment based on the number of historical failures; Whether the production operation status of the factory meets the requirements is determined according to the number of the production equipment with hidden dangers.

[0035] Furthermore, the production equipment with hidden dangers is production equipment whose number of historical failures does not meet the requirements.

[0036] It can be understood that when the number of the production equipment with hidden dangers is greater than the preset number of equipment, it is determined that the production operation status of the factory does not meet the requirements.

[0037] Specifically, when the production operation status of the factory meets the requirements, the production scheduling process of the factory is performed with the maximum production load.

[0038] Optionally, determining that the production operation status of the factory does not meet the requirements specifically includes: Determine the number of historical failures of different production equipment during the production process using historical failure data of different production equipment during the production process; Based on the production loads corresponding to different historical failure times, the number of production equipment with historical failures and the historical failure times of different production equipment under different production loads are determined. Based on the number of production equipment with historical failures and the historical failure times of different production equipment under different production loads, the failure potential coefficient under different production loads is determined. Whether the production operation status of the factory meets the requirements is determined based on the potential failure coefficients under different production loads.

[0039] Furthermore, when the number of production loads whose fault potential coefficients do not meet the requirements is greater than a preset number of loads, it is determined that the production operation status of the factory does not meet the requirements.

[0040] Specifically, the method for determining the available production load is: Determine the average daily output of products under different production loads based on production data under different production loads; The production processing time under different production loads is determined by the average daily output of the product and the production order, and the production load whose production processing time is within a preset time interval is used as the available production load.

[0041] S3 obtains historical fault data of different production equipment, and determines the optimal production load among the available production loads by combining the deviations between the production loads corresponding to the different historical fault data and the different available production loads and the production order; Specifically, Figure 4 As shown, the method for determining the optimal production load is: Based on the historical fault data of different production equipment, determine the production equipment with historical fault data under the available production load, and use it as the matching fault production equipment; Determining the production processing time under the available production load based on the production order; The matching deviation coefficient under the available production load is determined by multiplying the number of matching faulty production equipment by the production processing time, and the matching deviation coefficient is used to determine whether the available production load is the optimal production load.

[0042] Furthermore, the optimal production load is the available production load with the smallest matching deviation coefficient.

[0043] Optionally, the method for determining the optimal production load is: S31 determines, based on historical failure data of different production equipment, production equipment with historical failure data under the available production load, and uses it as a matching failure production equipment, and determines a failure potential coefficient under the available production load based on the number of matching failure production equipment and the number of historical failures of different matching failure production equipment under the available production load; S32 determines the production processing hidden danger coefficient of different production equipment under the available production load based on the historical failure times of different production equipment and the deviation between the production load corresponding to the different historical failure times and the available production load; S33 determines the production processing time under the available production load based on the production order; S34 determines the matching deviation coefficient under the available production load through the fault potential coefficient, the production processing potential coefficients of different production equipment under the available production load, and the production processing time, and uses the matching deviation coefficient to determine whether the available production load is the optimal production load.

[0044] S4 performs production scheduling processing of the factory based on the optimal production load, and determines the adjustment strategy of the production load based on the changes in order data and the analysis results of the monitoring data of the production equipment during the production process.

[0045] It should be noted that if Figure 5 As shown, the method for determining the adjustment strategy of the production load is: Determine the changed quantity of the production order based on the change of the order data, and determine the changed quantity proportional factor based on the ratio of the changed quantity to the product quantity corresponding to the production order; According to the analysis results of the monitoring data of the production equipment during the production process, the production equipment whose monitoring data is within the preset monitoring data interval corresponding to the production equipment is determined and regarded as the suspected abnormal production equipment; Based on the ratio of the change quantity proportional factor to the quantity of the suspected abnormal production equipment, an adjustment demand coefficient is determined, and the adjustment strategy of the production load is determined using the adjustment demand coefficient.

[0046] Furthermore, the adjustment strategy of the production load is determined by using the adjustment demand coefficient, which specifically includes: When the adjustment demand coefficient is not greater than the preset demand coefficient threshold, it is determined that no production load adjustment is required; When the adjustment demand coefficient is greater than the preset demand coefficient threshold, it is determined whether the adjustment demand coefficient is within the preset adjustment demand coefficient range. If so, the production load is switched to the maximum production load for production scheduling of the factory. If not, the switching target of the available production load to which the production load is switched is determined based on the preset adjustment factor corresponding to the production demand coefficient.

[0047] It should be noted that the switching target of the available production load is determined based on the product of the preset adjustment factor and the production load to adjust the production load, and the available production load closest to the adjusted production load is used as the switching target of the available production load.

[0048] Example 2 Second, as Figure 6 As shown, the present application provides an industrial Internet platform, which adopts the above-mentioned production collaborative management method, specifically including: Available load determination module, optimal load generation module, adjustment strategy output module; The available load determination module is responsible for determining the available production load based on the production order and the production data under different production loads; The optimal load generation module is responsible for determining the optimal production load among the available production loads; The adjustment strategy output module is responsible for determining the adjustment strategy of the production load.

[0049] Optionally, determine that management optimization of the plant's production load can be performed, including: Determine the average daily output of the product under the maximum production load based on the production data under the maximum production load, and determine that the production processing time under the average daily output of the product does not meet the requirements in combination with the production order, then determine that the management optimization of the production load of the factory cannot be performed; When the production processing time under the average daily output of the product meets the requirements: Determine the average value of the defective rate on different dates under the maximum production load based on the defective data under the maximum production load, and determine that the production processing time of the production order does not meet the requirements based on the average value of the defective rate and the average daily output of the product, then determine that the management optimization of the production load of the factory cannot be performed; When the production processing time of the production order meets the requirements based on the average value of the defective rate and the average daily output of the product: Determine the daily average quantity ratio in different defective rate intervals under the maximum production load, based on the daily average output of the product, the benchmark defective rate in different defective rate intervals, and in combination with the production order, determine the corresponding production processing time in different defective rate intervals; Based on the corresponding production processing time in different defect rate intervals and the daily average quantity ratios in different defect rate intervals, when the sum of the daily average quantity ratios of the defect rate intervals whose corresponding production processing time is not greater than the preset processing time threshold is less than the preset daily average quantity ratio, it is determined that the management optimization of the production load of the factory cannot be performed; When the sum of the daily average quantity ratios of the defective rate intervals whose corresponding production processing time is not greater than the preset processing time threshold is not less than the preset daily average quantity ratio: Based on the defective rate and the number of defective products on different dates under the maximum production load, the defective rate assessment value under the maximum production load is determined, and the predicted processing time is determined based on the defective rate assessment value, the average daily output of the product, and the production order. The predicted processing time is used to determine whether the factory's production load management optimization can be carried out.

[0050] Furthermore, when the predicted processing time does not meet the requirement, it is determined that the management optimization of the production load of the factory cannot be performed.

[0051] Example 3 Optionally, determining that the production operation status of the factory does not meet the requirements specifically includes: Determine the number of historical failures of different production equipment in the production process based on historical failure data of different production equipment in the production process, and determine that there is a production equipment with hidden dangers in the production equipment based on the historical failure number: When the number of the hidden danger fault equipment does not meet the requirement, it is determined that the production operation status of the factory does not meet the requirement; When the number of potential hidden danger fault equipment meets the requirement: Based on the number of the hidden danger fault equipment and the historical fault times of different hidden danger fault equipment, the equipment fault hidden danger coefficient of the factory is determined; when the equipment fault hidden danger coefficient of the factory does not meet the requirements, it is determined that the production operation status of the factory does not meet the requirements; When it is determined based on the number of historical failures that there are no hidden dangers in the production equipment and the equipment failure hidden danger coefficient of the factory meets the requirements: The number of production equipment with historical failures and the number of historical failures of different production equipment under different production loads are determined based on the production loads corresponding to different historical failure times. When the number of production equipment with historical failures and the number of historical failures of different production equipment under different production loads meet the requirements, it is determined that the production operation status of the factory meets the requirements; When any of the number of production equipment with historical failures and the number of historical failures of different production equipment does not meet the required production load: Determine the potential failure coefficients under different production loads based on the number of production equipment with historical failures under different production loads and the number of historical failures of different production equipment; when the average value of the potential failure coefficients under different production loads does not meet the requirements, determine that the production operation status of the factory does not meet the requirements; When the average value of the potential fault coefficient under different production loads meets the requirements: When the number of production loads whose potential fault coefficients do not meet the requirements is greater than the preset number of loads, it is determined that the production operation status of the factory does not meet the requirements; When the number of production loads that do not meet the requirements of the potential fault coefficient is not greater than the preset number of loads: The abnormal operation coefficient of the factory is determined based on the potential failure coefficients under different production loads and the potential failure coefficients of the factory's equipment, and the abnormal operation coefficient is used to determine whether the production operation status of the factory meets the requirements.

[0052] Example 4 Optionally, the above step S31 includes the following contents: S311 determines the production equipment with historical fault data under the available production load based on the historical fault data of different production equipment, and uses it as the matching fault production equipment. When the number of matching fault production equipment under the available production load does not meet the requirement, it is determined that the available production load does not belong to the optimal production load. When the number of matching fault production equipment under the available production load meets the requirement, it proceeds to step S312; S312: When the number of historical failures of different matching faulty production equipment under the available production load all meets the requirement, proceed to step S314; when there is a matching faulty production equipment whose number of historical failures under the available production load does not meet the requirement, proceed to step S313; S313: When the number of matching faulty production devices whose historical fault times under the available production load do not meet the requirements is greater than the preset number of matching faulty devices, it is determined that the available production load does not belong to the optimal production load; when the number of matching faulty production devices whose historical fault times under the available production load do not meet the requirements is not greater than the preset number of matching faulty devices, the process proceeds to step S314; S314 determines the fault potential coefficient under the available production load based on the number of matching faulty production equipment and the number of historical failures of different matching faulty production equipment under the available production load. When the fault potential coefficient under the available production load does not meet the requirements, it is determined that the available production load does not belong to the optimal production load. When the fault potential coefficient under the available production load meets the requirements, proceed to step S32.

[0053] Optionally, the above step S32 includes the following contents: S321 determines the production processing hidden danger coefficients of different production equipment under the available production load based on the historical failure times of different production equipment and the deviations of the production loads corresponding to the different historical failure times and the available production load. When the production processing hidden danger coefficients of different production equipment under the available production load all meet the requirements, the process proceeds to step S33. When there is a production equipment whose production processing hidden danger coefficient under the available production load does not meet the requirements, the process proceeds to step S322. S322: When the number of production equipment whose production processing hidden danger coefficient under the available production load does not meet the requirements is within the preset production equipment interval, it is determined that the available production load does not belong to the optimal production load; when the number of production equipment whose production processing hidden danger coefficient under the available production load does not meet the requirements is not within the preset production equipment interval, the process proceeds to step S323; S323 determines the comprehensive hidden danger coefficient under the available production load by using the production processing hidden danger coefficients of different production equipment under the available production load, and based on the fault hidden danger coefficient under the available production load corresponding to the preset hidden danger coefficient threshold, when it is determined that the comprehensive hidden danger coefficient under the available production load does not meet the requirements, it is determined that the available production load does not belong to the optimal production load. When the comprehensive hidden danger coefficient under the available production load meets the requirements, proceed to step S33.

[0054] Optionally, the above step S33 includes the following contents: S331 determines the production processing time under the available production load based on the production order. When the production processing time is not within the preset production time interval corresponding to the fault potential coefficient under the available production load, it is determined that the available production load does not belong to the optimal production load. When the production processing time is not within the preset production time interval corresponding to the fault potential coefficient under the available production load, proceed to step S332; S332 determines the duration threshold under the available production load by using the production processing potential risk coefficient of different production equipment under the available production load and the fault potential risk coefficient under the available production load. When the production processing duration is less than the duration threshold, proceeds to step S34. When the production processing duration is not less than the duration threshold, it is determined that the available production load does not belong to the optimal production load.

[0055] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0056] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0057] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A production collaborative management method, characterized in that: Specifically include: When it is determined that the management optimization of the factory's production load can be performed based on the current production order and combined with the production data and defect data under the maximum production load, the next step is entered; Acquire historical fault data of the production equipment of the factory during the production process, and when determining based on the historical fault data that the production operation status of the factory does not meet the requirements, determine the available production load based on the production order and the production data under different production loads; Obtaining historical fault data of different production equipment, and determining the optimal production load among the available production loads in combination with the deviations between the production loads corresponding to the different historical fault data and the different available production loads and the production order; The optimal production load is used to perform production scheduling of the factory, and the production load adjustment strategy is determined based on the changes in order data and the analysis results of the monitoring data of the production equipment during the production process.

2. The production collaborative management method according to claim 1, characterized in that: The production data includes an average daily output of the product under the maximum production load.

3. The production collaborative management method according to claim 1, characterized in that: The defective data includes the defective rate and the number of defective products on different dates under the maximum production load.

4. The production collaborative management method according to claim 1, characterized in that: Determine the ability to manage and optimize the factory's production load, including: Determine the average daily output of products under the maximum production load and the average daily quantity ratio in different defect rate ranges based on the production data and defect data under the maximum production load; Based on the average daily output of the product, the benchmark defective rate in different defective rate ranges, and in combination with the production order, determine the corresponding production processing time in different defective rate ranges; Based on the corresponding production processing time in different defect rate ranges and the average daily quantity ratio in different defect rate ranges, determine whether the management optimization of the factory's production load can be carried out.

5. The production collaborative management method according to claim 4, characterized in that: The reference defective rate within the defective rate interval is the average value of the defective rate endpoints corresponding to the defective rate interval.

6. The production collaborative management method according to claim 4, characterized in that: Based on the corresponding production processing time in different defect rate ranges and the daily average quantity ratio in different defect rate ranges, determine whether the factory's production load management optimization can be performed, including: When the corresponding production processing time in different defect rate intervals is greater than the preset processing time threshold, it is determined that the management optimization of the production load of the factory cannot be performed; When there is a defect rate interval whose corresponding production processing time is not greater than the preset processing time threshold, it is determined whether the sum of the daily average quantity proportions of the defect rate intervals whose corresponding production processing time is not greater than the preset processing time threshold is greater than the preset daily average quantity proportion. If so, it is determined that the management optimization of the factory's production load can be carried out. If not, it is determined that the management optimization of the factory's production load cannot be carried out.

7. The production collaborative management method according to claim 1, characterized in that: When it is determined that management optimization of the production load of the factory cannot be performed, production scheduling processing of the factory is performed at the maximum production load.

8. The production collaborative management method according to claim 1, characterized in that: The method for determining the adjustment strategy of the production load is: Determine the changed quantity of the production order based on the change of the order data, and determine the changed quantity proportional factor based on the ratio of the changed quantity to the product quantity corresponding to the production order; According to the analysis results of the monitoring data of the production equipment during the production process, the production equipment whose monitoring data is within the preset monitoring data interval corresponding to the production equipment is determined and regarded as the suspected abnormal production equipment; Based on the ratio of the change quantity proportional factor to the quantity of the suspected abnormal production equipment, an adjustment demand coefficient is determined, and the adjustment strategy of the production load is determined using the adjustment demand coefficient.

9. The production collaborative management method according to claim 8, characterized in that: The adjustment strategy of production load is determined by using the adjustment demand coefficient, specifically including: When the adjustment demand coefficient is not greater than the preset demand coefficient threshold, it is determined that no production load adjustment is required; When the adjustment demand coefficient is greater than the preset demand coefficient threshold, it is determined whether the adjustment demand coefficient is within the preset adjustment demand coefficient range. If so, the production load is switched to the maximum production load for production scheduling of the factory. If not, the switching target of the available production load to which the production load is switched is determined based on the preset adjustment factor corresponding to the production demand coefficient.

10. An industrial Internet platform, using a production collaborative management method according to any one of claims 1 to 9, characterized in that: Specifically include: Available load determination module, optimal load generation module, adjustment strategy output module; The available load determination module is responsible for determining the available production load based on the production order and the production data under different production loads; The optimal load generation module is responsible for determining the optimal production load among the available production loads; The adjustment strategy output module is responsible for determining the adjustment strategy of the production load.

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