An industrial Internet platform and a production collaboration management method

Abstract

The present invention provides an industrial Internet platform and a production collaborative management method, belonging to the technical field of production management. Specifically, it includes: determining the available production load based on production orders and production data under different production loads, obtaining the historical failure data of different production equipment, and combining the deviation between the production load corresponding to different historical failure data and different available production loads and production orders to determine the optimal production load in the available production loads, performing production scheduling processing of the factory with the optimal production load, and determining the production load adjustment strategy based on the change of order data and the analysis result of the monitoring data of production equipment during the production process, ensuring the efficiency of production processing.

Description

Technical Field

[0001] The present invention belongs to the technical field of production management, and particularly 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., in the invention patent application CN201911127154.6 "Green Scheduling Optimization Method for Intelligent Manufacturing Workshop Oriented to Complex Human-Machine Coupling", a multi-objective function for green scheduling optimization is constructed, 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, realizing the production scheduling management of the intelligent manufacturing workshop. However, the following technical problems exist in the above technical solution:

[0003] In the process of production collaborative management, the prior art solutions ignore generating differentiated production management strategies according to the failure probabilities of different production equipment under different production loads. For production equipment, there is a certain deviation in the failure probability under different operating loads. Therefore, in the process of production collaborative management, the failure probabilities of production equipment under different operating loads are ignored, and the production processing efficiency cannot be guaranteed.

[0004] In view of the above technical problems, specifically, the present application provides an industrial Internet platform and a production collaborative management method. Summary of the Invention

[0005] To achieve the object of the present invention, the present invention adopts the following technical solutions:

[0006] In the first aspect, the present application provides a production collaborative management method, specifically including:

[0007] S1 Based on the current production order, and combining the production data and defective data under the maximum production load, when it is determined that the management optimization of the production load of the factory can be carried out, proceed to the next step;

[0008] S2 Obtain the historical failure data of the production equipment in the factory during the production process. When it is determined that the production operation status of the factory does not meet the requirements based on the historical failure data, determine the available production load based on the production order and the production data under different production loads;

[0009] S3 Obtain the historical failure data of different production equipment, and combine the deviation between the production load corresponding to different historical failure data and different available production loads and the production order to determine the optimal production load in the available production load;

[0010] S4 performs production scheduling processing of the factory at the optimal production load, and determines an adjustment strategy for the production load based on the changes in order data and the analysis results of the monitoring data of production equipment during the production process.

[0011] The beneficial effects of the present invention are as follows:

[0012] Based on the current production order, production data at the maximum production load, and defective data, it is determined whether the management optimization of the production load of the factory can be carried out. It realizes an accurate assessment of the production processing duration of the current production order based on the production data and defective data at the maximum production load, and avoids the technical problem that the production processing efficiency is difficult to meet the requirements caused by the management optimization of the production load when the production processing duration at the maximum production load still does not meet the requirements. It also lays a foundation for generating a differentiated production load adjustment strategy according to the differences in production orders.

[0013] Determine the adjustment strategy of the production load based on the changes in order data and the analysis results of the monitoring data of production equipment during the production process. It not only considers the differences in the adjustment requirements of the production load caused by the differences in the changes in order data, but also considers the differences in the probability of abnormal production equipment caused by the differences in the monitoring data. It realizes the determination of the production load adjustment strategy from the operating reliability of production equipment and the changing requirements of production orders, ensuring the reliability of production processing and the efficiency of production processing.

[0014] A further technical solution is that the production data includes the daily average output of products at the maximum production load.

[0015] A further technical solution is that the defective data includes the defective rate and the number of defective products on different dates at the maximum production load.

[0016] A further technical solution is that determining that the management optimization of the production load of the factory can be carried out specifically includes:

[0017] Determine the daily average output of products at the maximum production load and the proportion of the daily average quantity in different defective rate intervals based on the production data and defective data at the maximum production load;

[0018] Based on the daily average output of the products and the reference defective rates in different defective rate intervals, and in combination with the production order, determine the corresponding production processing duration in different defective rate intervals;

[0019] Based on the corresponding production processing duration in different defective rate intervals and the proportion of the daily average quantity in different defective rate intervals, determine whether the management optimization of the production load of the factory can be carried out.

[0020] A further technical solution is that the benchmark defect rate within the defect rate range is the average of the defect rate endpoints corresponding to the defect rate range.

[0021] A further technical solution is that the method for determining the adjustment strategy of the production load is as follows:

[0022] Determine the change quantity of the production order based on the change situation of the order data, and determine the change quantity proportion factor with the ratio of the change quantity to the product quantity corresponding to the production order;

[0023] Based on the analysis result of the monitoring data of the production equipment during the production process, determine the production equipment within the preset monitoring data range corresponding to the production equipment, and use it as the suspected abnormal production equipment;

[0024] Based on the ratio of the change quantity proportion factor to the number of the suspected abnormal production equipment, determine the adjustment demand coefficient, and use the adjustment demand coefficient to determine the adjustment strategy of the production load.

[0025] A further technical solution is that using the adjustment demand coefficient to determine the adjustment strategy of the production load specifically includes:

[0026] When the adjustment demand coefficient is not greater than the preset demand coefficient threshold, it is determined that no adjustment of the production load is required;

[0027] When the adjustment demand coefficient is greater than the preset demand coefficient threshold, determine whether the adjustment demand coefficient is within the preset adjustment demand coefficient range. If so, switch the production load to the maximum production load for the production scheduling process of the factory. If not, based on the preset adjustment factor corresponding to the production demand coefficient, determine the switching target of the available production load to which the production load is switched.

[0028] A further technical solution is that the switching target of the available production load is based on the product of the preset adjustment factor and the production load to determine the adjusted production load, and use the available production load closest to the adjusted production load as the switching target of the available production load.

[0029] In a second aspect, the present application provides an industrial Internet platform that adopts the above-mentioned production collaboration management method, specifically including:

[0030] An available load determination module, an optimal load generation module, and an adjustment strategy output module;

[0031] Among them, 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;

[0032] The optimal load generation module is responsible for determining the optimal production load among the available production loads;

[0033] The adjustment strategy output module is responsible for determining the adjustment strategy for the production load.

[0034] Other features and advantages will be described in the following specification. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification and the accompanying drawings.

[0035] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given in conjunction with the accompanying drawings and are described in detail as follows. Description of the Drawings

[0036] By referring to the accompanying drawings and describing its exemplary embodiments in detail, the above and other features and advantages of the present invention will become more obvious;

[0037] Figure 1 is a flowchart of a production collaboration management method;

[0038] Figure 2 is a flowchart for determining the management optimization of the production load of a factory;

[0039] Figure 3 is a flowchart for determining that the production operation status of a factory does not meet the requirements;

[0040] Figure 4 is a flowchart of a method for determining the optimal production load;

[0041] Figure 5 is a flowchart of a method for determining the adjustment strategy of the production load;

[0042] Figure 6 is a framework diagram of an industrial Internet platform. Detailed Embodiments

[0043] To enable those skilled in the art of this technology 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 accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this specification.

[0044] In this application, by using the failure data and order data of production equipment under different production loads, the optimal production load in the production load is determined, which not only meets the requirements of production orders, but also avoids the technical problem that the production processing efficiency does not meet the requirements due to the failure data under the production load not meeting the requirements.

[0045] Based on the production data and defective data under the maximum production load, determine the daily average output and average defective rate of products under the maximum production load. Based on the daily average output and average defective rate of products, determine the production processing duration of the production order. When the production processing duration is greater than the preset duration threshold, it is determined that the management optimization of the production load of the factory cannot be carried out.

[0046] Based on the historical failure data of different production equipment during the production process, determine the historical failure times of different production equipment during the production process. Based on the historical failure times, determine the potential hazard production equipment in the production equipment. When the proportion of the number of potential hazard production equipment in the production equipment is greater than 0.3, it is determined that the production operation status of the factory does not meet the requirements.

[0047] The available production load is the production load within the preset duration range of the production processing duration of the production order.

[0048] The optimal production load is the available production load with the smallest ratio of the number of production equipment with historical failure data to the production processing duration of the production order.

[0049] Based on the change situation of the order data, determine the change quantity of the production order, and based on the ratio of the change quantity to the product quantity corresponding to the production order, determine the change quantity proportional factor. Monitor the production equipment within the preset monitoring data range corresponding to the production equipment, and regard it as a suspected abnormal production equipment. Based on the ratio of the change quantity proportional factor to the number of suspected abnormal production equipment, determine the adjustment demand coefficient, and use the adjustment demand coefficient to determine the adjustment strategy of the production load.

[0050] Embodiment 1

[0051] As Figure 1 shown, the first aspect provided by this application is that this application provides a production collaboration management method, which specifically includes:

[0052] S1 Based on the current production order, and in combination with the production data and defective data under the maximum production load, when it is determined that the management optimization of the production load of the factory can be carried out, proceed to the next step;

[0053] Further, the production data includes the daily average output of products under the maximum production load.

[0054] Specifically, the defective data includes the defective rate and the number of defective products on different dates under the maximum production load.

[0055] Specifically, as Figure 2 shown, it is determined that the management optimization of the production load of the factory can be carried out, specifically including:

[0056] Determine the daily average output of products under the maximum production load and the proportion of the daily average quantity in different defective rate intervals based on the production data and defective data under the maximum production load;

[0057] Based on the daily average output of the products, the benchmark defective rate in different defective rate intervals, and in combination with the production order, determine the corresponding production processing duration in different defective rate intervals;

[0058] Based on the corresponding production processing duration in different defective rate intervals and the proportion of the daily average quantity in different defective rate intervals, determine whether the management optimization of the production load of the factory can be carried out.

[0059] Optionally, the benchmark defective rate in the defective rate interval is the average value of the defective rate endpoints corresponding to the defective rate interval.

[0060] It can be understood that based on the corresponding production processing duration in different defective rate intervals and the proportion of the daily average quantity in different defective rate intervals, determining whether the management optimization of the production load of the factory can be carried out specifically includes:

[0061] When the corresponding production processing duration in different defective rate intervals is greater than the preset processing duration threshold, it is determined that the management optimization of the production load of the factory cannot be carried out;

[0062] When there is a defective rate interval where the corresponding production processing duration is not greater than the preset processing duration threshold, then judge whether the sum of the proportion of the daily average quantity in the defective rate interval where the corresponding production processing duration is not greater than the preset processing duration threshold is greater than the preset proportion of the daily average quantity. If so, it is determined that the management optimization of the production load of the factory can be carried out. If not, it is determined that the management optimization of the production load of the factory cannot be carried out.

[0063] Further, when it is determined that the management optimization of the production load of the factory cannot be carried out, the production scheduling process of the factory is carried out with the maximum production load.

[0064] In another possible embodiment, determining that the management optimization of the production load of the factory can be carried out specifically includes:

[0065] Determine the daily average output of products and the average defective rate under the maximum production load based on the production data and defective data under the maximum production load;

[0066] Based on the daily average output and average defect rate of the product, and in combination with the production order, determine the production processing duration;

[0067] Based on the production processing duration, determine whether the production load management of the factory can be optimized.

[0068] Furthermore, when the production processing duration is greater than the preset duration threshold, it is determined that the production load management of the factory cannot be optimized.

[0069] S2 Obtain the historical failure data of the production equipment in the factory during the production processing. When it is determined that the production operation status of the factory does not meet the requirements based on the historical failure data, determine the available production load based on the production order and production data under different production loads;

[0070] It should be noted that the historical failure data of the production equipment during the production processing includes the historical failure times of the production equipment and the production loads corresponding to different historical failure times.

[0071] Specifically, as Figure 3 shown, determining that the production operation status of the factory does not meet the requirements specifically includes:

[0072] Determine the historical failure times of different production equipment during the production processing based on the historical failure data of different production equipment during the production processing;

[0073] Based on the historical failure times, determine the potential hazard production equipment among the production equipment;

[0074] According to the number of potential hazard production equipment, determine whether the production operation status of the factory meets the requirements.

[0075] Furthermore, the potential hazard production equipment is the production equipment with historical failure times not meeting the requirements.

[0076] It can be understood that when the number of potential hazard production equipment is greater than the preset equipment number, it is determined that the production operation status of the factory does not meet the requirements.

[0077] Specifically, when the production operation status of the factory meets the requirements, the production scheduling of the factory is processed with the maximum production load.

[0078] Optionally, determining that the production operation status of the factory does not meet the requirements specifically includes:

[0079] Determine the historical failure times of different production equipment during the production processing based on the historical failure data of different production equipment during the production processing;

[0080] Determine the number of production devices with historical failures and the historical failure times of different production devices at different production loads based on the production loads corresponding to different historical failure times, and determine the potential failure coefficients at different production loads based on the number of production devices with historical failures and the historical failure times of different production devices at different production loads;

[0081] Determine whether the production operation status of the factory meets the requirements based on the potential failure coefficients at different production loads.

[0082] Furthermore, when the number of production loads with potential failure coefficients not meeting the requirements is greater than the preset load number, it is determined that the production operation status of the factory does not meet the requirements.

[0083] Specifically, the method for determining the available production loads is as follows:

[0084] Determine the daily average production output of products at different production loads based on the production data at different production loads;

[0085] Determine the production processing duration at different production loads through the daily average production output of products and the production orders, and regard the production loads with the production processing duration within the preset duration range as the available production loads.

[0086] S3 Obtain the historical failure data of different production devices, and determine the optimal production load among the available production loads in combination with the deviation between the production loads corresponding to different historical failure data and the different available production loads and the production orders;

[0087] Specifically, as Figure 4 shown, the method for determining the optimal production load is as follows:

[0088] Based on the historical failure data of different production devices, determine the production devices with historical failure data at the available production loads and regard them as the matching failure production devices;

[0089] Determine the production processing duration at the available production loads based on the production orders;

[0090] Determine the matching deviation coefficient at the available production loads by multiplying the number of the matching failure production devices by the production processing duration, and use the matching deviation coefficient to determine whether the available production load is the optimal production load.

[0091] Furthermore, the optimal production load is the available production load with the smallest matching deviation coefficient.

[0092] Optionally, the method for determining the optimal production load is as follows:

[0093] Based on the historical failure data of different production devices, S31 determines the production devices with historical failure data under the available production load and takes them as the matching faulty production devices. Based on the number of the matching faulty production devices and the historical failure times of different matching faulty production devices under the available production load, the potential fault coefficient under the available production load is determined;

[0094] Based on the historical failure times of different production devices and the deviation between the production load corresponding to different historical failure times and the available production load, S32 determines the production processing potential hazard coefficient of different production devices under the available production load;

[0095] Based on the production order, S33 determines the production processing duration under the available production load;

[0096] Through the potential fault coefficient, the production processing potential hazard coefficient of different production devices under the available production load, and the production processing duration, S34 determines the matching deviation coefficient under the available production load, and uses the matching deviation coefficient to determine whether the available production load is the optimal production load.

[0097] S4 performs production scheduling processing on the factory with the optimal production load, and determines the adjustment strategy of the production load based on the change situation of the order data and the analysis result of the monitoring data of the production devices during the production process.

[0098] It should be noted that, as Figure 5 shown, the method for determining the adjustment strategy of the production load is:

[0099] Based on the change situation of the order data, determine the change quantity of the production order, and use the ratio of the change quantity to the product quantity corresponding to the production order to determine the change quantity proportion factor;

[0100] According to the analysis result of the monitoring data of the production devices during the production process, determine the production devices whose monitoring data is within the preset monitoring data range corresponding to the production devices, and take them as the suspected abnormal production devices;

[0101] Based on the ratio of the change quantity proportion factor to the number of the suspected abnormal production devices, determine the adjustment demand coefficient, and use the adjustment demand coefficient to determine the adjustment strategy of the production load.

[0102] Furthermore, using the adjustment demand coefficient to determine the adjustment strategy of the production load specifically includes:

[0103] When the adjustment demand coefficient is not greater than the preset demand coefficient threshold, it is determined that no adjustment of the production load is required;

[0104] When the adjustment demand coefficient is greater than the preset demand coefficient threshold, it is judged 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 the production scheduling process of the factory. If not, based on the preset adjustment factor corresponding to the production demand coefficient, the switching target of the available production load to which the production load is switched is determined.

[0105] It should be noted that the switching target of the available production load is based on the product of the preset adjustment factor and the production load to determine the adjusted production load, and the available production load closest to the adjusted production load is used as the switching target of the available production load.

[0106] Embodiment 2

[0107] In a second aspect, as Figure 6 shown, the present application provides an industrial Internet platform, which adopts the above-mentioned production collaboration management method, and specifically includes:

[0108] An available load determination module, an optimal load generation module, and an adjustment strategy output module;

[0109] Among them, the available load determination module is responsible for determining the available production load based on the production order and production data under different production loads;

[0110] The optimal load generation module is responsible for determining the optimal production load among the available production loads;

[0111] The adjustment strategy output module is responsible for determining the adjustment strategy of the production load.

[0112] Optionally, it is determined that the management optimization of the production load of the factory can be carried out, and specifically includes:

[0113] Determine the daily average output of products under the maximum production load based on the production data under the maximum production load, and combine the production order to determine that when the production processing duration under the daily average output of the products does not meet the requirements, it is determined that the management optimization of the production load of the factory cannot be carried out;

[0114] When the production processing duration under the daily average output of the products meets the requirements:

[0115] Determine the average value of the defect rates on different dates under the maximum production load based on the defective data under the maximum production load. Based on the average value of the defect rates and the daily average output of the products, when the production processing duration of the production order does not meet the requirements, it is determined that the management optimization of the production load of the factory cannot be carried out;

[0116] When it is determined that the production processing duration of the production order meets the requirements based on the average value of the defective rate and the daily average production volume of the product:

[0117] Determine the proportion of the daily average quantity in different defective rate intervals under the maximum production load. Based on the daily average production volume of the product, the benchmark defective rate in different defective rate intervals, and in combination with the production order, determine the corresponding production processing duration in different defective rate intervals;

[0118] Based on the corresponding production processing duration in different defective rate intervals and the proportion of the daily average quantity in different defective rate intervals, when the sum of the proportions of the daily average quantity in the defective rate intervals where the corresponding production processing duration is not greater than the preset processing duration threshold is less than the preset daily average quantity proportion, it is determined that the management optimization of the production load of the factory cannot be carried out;

[0119] When the sum of the proportions of the daily average quantity in the defective rate intervals where the corresponding production processing duration is not greater than the preset processing duration threshold is not less than the preset daily average quantity proportion:

[0120] Based on the defective rate and the quantity of defective products on different dates under the maximum production load, determine the defective rate evaluation quantity under the maximum production load. Based on the defective rate evaluation quantity, the daily average production volume of the product, and the production order, determine the predicted processing duration, and use the predicted processing duration to determine whether the management optimization of the production load of the factory can be carried out.

[0121] Furthermore, when the predicted processing duration does not meet the requirements, it is determined that the management optimization of the production load of the factory cannot be carried out.

[0122] Embodiment 3

[0123] Optionally, determining that the production operation status of the factory does not meet the requirements specifically includes:

[0124] Based on the historical failure data of different production equipment during the production process, determine the historical failure times of different production equipment during the production process. When it is determined that there are potential hazard production equipment among the production equipment based on the historical failure times:

[0125] When the quantity of the potential hazard failure equipment does not meet the requirements, it is determined that the production operation status of the factory does not meet the requirements;

[0126] When the quantity of the potential hazard failure equipment meets the requirements:

[0127] Based on the quantity of the potential hazard failure equipment and the historical failure times of different potential hazard failure equipment, determine the equipment failure hazard coefficient of the factory. When the equipment failure hazard 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;

[0128] When it is determined based on the historical failure times that there are no potential hazard production equipment in the production equipment and the equipment failure hazard coefficient of the factory meets the requirements:

[0129] Using the production loads corresponding to different historical failure times, determine the number of production equipment with historical failures under different production loads and the historical failure times of different production equipment. When both the number of production equipment with historical failures under different production loads and the historical failure times of different production equipment meet the requirements, it is determined that the production operation status of the factory meets the requirements;

[0130] When any one of the number of production equipment with historical failures and the historical failure times of different production equipment does not meet the requirements for a production load:

[0131] Using the number of production equipment with historical failures under different production loads and the historical failure times of different production equipment, determine the failure hazard coefficients under different production loads. When the average value of the failure hazard coefficients under different production loads does not meet the requirements, it is determined that the production operation status of the factory does not meet the requirements;

[0132] When the average value of the failure hazard coefficients under different production loads meets the requirements:

[0133] When the number of production loads with failure hazard coefficients not meeting the requirements is greater than the preset load number, it is determined that the production operation status of the factory does not meet the requirements;

[0134] When the number of production loads with failure hazard coefficients not meeting the requirements is not greater than the preset load number:

[0135] Based on the failure hazard coefficients under different production loads and the equipment failure hazard coefficient of the factory, determine the operation status abnormal coefficient of the factory, and use the operation status abnormal coefficient to determine whether the production operation status of the factory meets the requirements.

[0136] Embodiment 4

[0137] Optionally, the above step S31 includes the following content:

[0138] S311 Based on the historical failure data of different production equipment, determine the production equipment with historical failure data under the available production load and use it as the matching failure production equipment. When the number of matching failure production equipment 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 number of matching failure production equipment under the available production load meets the requirements, proceed to step S312;

[0139] S312 When the historical failure times of different matching faulty production devices under the available production load all meet the requirements, proceed to step S314; when there are matching faulty production devices with historical failure times not meeting the requirements under the available production load, proceed to step S313;

[0140] S313 When the number of matching faulty production devices with historical failure times not meeting the requirements under the available production load 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 with historical failure times not meeting the requirements under the available production load is not greater than the preset number of matching faulty devices, proceed to step S314;

[0141] S314 Determine the potential fault coefficient under the available production load based on the number of matching faulty production devices and the historical failure times of different matching faulty production devices under the available production load. When the potential fault 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 potential fault coefficient under the available production load meets the requirements, proceed to step S32.

[0142] Optionally, the following content is included in the above step S32:

[0143] S321 Determine the production processing potential fault coefficient of different production devices under the available production load based on the historical failure times of different production devices and the deviation between the production loads corresponding to different historical failure times and the available production load. When the production processing potential fault coefficients of different production devices under the available production load all meet the requirements, proceed to step S33; when there are production devices with production processing potential fault coefficients not meeting the requirements under the available production load, proceed to step S322;

[0144] S322 When the number of production devices with production processing potential fault coefficients not meeting the requirements under the available production load is within the preset production device range, it is determined that the available production load does not belong to the optimal production load; when the number of production devices with production processing potential fault coefficients not meeting the requirements under the available production load is not within the preset production device range, proceed to step S323;

[0145] S323 Determine the comprehensive potential fault coefficient under the available production load based on the production processing potential fault coefficients of different production devices under the available production load. Based on the potential fault coefficient under the available production load corresponding to the preset potential fault coefficient threshold, when it is determined that the comprehensive potential fault 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 potential fault coefficient under the available production load meets the requirements, proceed to step S33.

[0146] Optionally, the above step S33 includes the following content:

[0147] S331 determines the production processing duration under the available production load based on the production order. When the production processing duration is not within the preset production duration interval corresponding to the potential fault 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 duration is not within the preset production duration interval corresponding to the potential fault coefficient under the available production load, proceed to step S332;

[0148] S332 determines the duration threshold under the available production load based on the production processing potential hazard coefficient of different production devices under the available production load and the potential fault coefficient under the available production load. When the production processing duration is less than the duration threshold, proceed 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.

[0149] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non - volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0150] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0151] The above is only one or more embodiments of this specification and is not used to limit this specification. For those skilled in the art, one or more embodiments of this specification can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A production collaborative management method, characterized in that, Specifically include: Based on the current production order, combined with production data and defective data under the maximum production load, when it is determined that the management optimization of the production load of the factory can be carried out, enter the next step; Obtain the historical failure data of the production equipment in the factory during the production process. When it is determined that the production operation status of the factory does not meet the requirements based on the historical failure data, determine the available production load based on the production order and production data under different production loads; Obtain the historical failure data of different production equipment, and combine the deviation between the production load corresponding to different historical failure data and different available production loads, as well as the production order, to determine the optimal production load among the available production loads; Perform production scheduling processing for the factory with the optimal production load, and determine the adjustment strategy of the production load based on the change situation of the order data and the analysis result of the monitoring data of the production equipment during the production process; The method for determining the optimal production load is: Based on the historical failure data of different production equipment, determine the production equipment with historical failure data under the available production load, and use it as the matching faulty production equipment; Determine the production processing duration under the available production load based on the production order; Determine the matching deviation coefficient under the available production load by multiplying the number of the matching faulty production equipment by the production processing duration, and use the matching deviation coefficient to determine whether the available production load is the optimal production load; The method for determining the adjustment strategy of the production load is: Determine the change quantity of the production order based on the change situation of the order data, and determine the change quantity proportion factor by the ratio of the change quantity to the product quantity corresponding to the production order; According to the analysis result of the monitoring data of the production equipment during the production process, determine the production equipment whose monitoring data is within the preset monitoring data range corresponding to the production equipment, and use it as the suspected abnormal production equipment; Based on the ratio of the change quantity proportion factor to the number of the suspected abnormal production equipment, determine the adjustment demand coefficient, and use the adjustment demand coefficient to determine the adjustment strategy of the production load.

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

3. The production collaborative management method according to claim 1, wherein 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, wherein, Determine that the management optimization of the production load of the factory can be carried out, specifically including: Determine the daily average output of products under the maximum production load and the proportion of the daily average quantity in different defective rate intervals based on the production data and defective data under the maximum production load; Based on the daily average output of products, the reference defective rate in different defective rate intervals, and combined with the production order, determine the corresponding production processing duration in different defective rate intervals; Based on the corresponding production processing duration in different defective rate intervals and the proportion of the daily average quantity in different defective rate intervals, determine whether the management optimization of the production load of the factory can be carried out.

5. The production collaborative management method according to claim 4, wherein The reference defective rate in 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 duration in different defect rate intervals and the proportion of the daily average quantity in different defect rate intervals, determine whether the management optimization of the factory's production load can be carried out, specifically including: When the corresponding production processing durations in different defect rate intervals are all greater than the preset processing duration threshold, it is determined that the management optimization of the factory's production load cannot be carried out; When there is a defect rate interval where the corresponding production processing duration is not greater than the preset processing duration threshold, determine whether the sum of the proportions of the daily average quantity in the defect rate intervals where the corresponding production processing duration is not greater than the preset processing duration 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, wherein When it is determined that the management optimization of the factory's production load cannot be carried out, the production scheduling process of the factory is carried out with the maximum production load.

8. The production collaborative management method according to claim 1, wherein, Use the adjustment demand coefficient to determine the adjustment strategy of the production load, specifically including: When the adjustment demand coefficient is not greater than the preset demand coefficient threshold, it is determined that no adjustment of the production load is required; When the adjustment demand coefficient is greater than the preset demand coefficient threshold, determine whether the adjustment demand coefficient is within the preset adjustment demand coefficient interval. If so, switch the production load to the maximum production load for the production scheduling process of the factory. If not, based on the preset adjustment factor corresponding to the production demand coefficient, determine the switching target of the available production load to which the production load is switched.

9. An industrial Internet platform that adopts a production collaboration management method described in any one of claims 1-8, characterized in that, Specifically including: Available load determination module, optimal load generation module, adjustment strategy output module; Among them, the available load determination module is responsible for determining the available production load based on production orders and 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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