Intelligent factory management method and system based on digitization

Abstract

The invention discloses a smart factory management method and system based on digitization, and the method comprises the steps: analyzing the number of missing components caused by the maintenance of production equipment, and carrying out the weighted distribution of the number of components to each piece of production equipment based on the operation state of the production equipment and the comprehensive health score of the equipment, analyzing the load of the production equipment after the assembly production quantity is increased, analyzing the influence of the load on the damage coefficient of each part of the production equipment, and further analyzing the influence of the damage coefficient of the parts of the production equipment on the first maintenance time and the first maintenance duration of the production equipment to obtain second maintenance time and second maintenance duration; comparing the difference value of the second maintenance time of each piece of production equipment with the second maintenance duration, judging whether the duration between the second maintenance time can meet the second maintenance duration or not, further analyzing the influence relationship of the load on the second maintenance time, and adjusting the load of the production equipment based on the influence relationship. The method has the characteristics of improving accuracy and production efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of smart factory management, and in particular to a digital-based smart factory management method and system. Background Art

[0002] With the rapid development of intelligent manufacturing technology, most companies will establish production chains in order to reduce costs. In the production chain, products will be produced by multiple production links, and then the components produced by the production links will be assembled by the assembly link.

[0003] At present, the existing technology usually adopts the method of partitioning the production of components and then assembling them to achieve the rational use of the smart factory site, so that each component is produced in a different workshop and the productivity of each workshop is fully utilized. However, during the production process, the production equipment needs to be maintained. When the production equipment is maintained, it may cause the assembly link to be unable to obtain enough components, resulting in the assembly link being unable to guarantee production and low production efficiency. Moreover, during the maintenance of the production equipment, due to the different loads of the production equipment, it is easy to cause the parts of the production equipment to be different. The existing technology cannot accurately adjust the load of the production equipment. It may happen that when the current production equipment is being maintained, other production equipment also needs maintenance due to low production equipment health scores due to unreasonable production planning, resulting in production equipment maintenance conflicts. Multiple equipment are maintained at the same time, and the production efficiency of the assembly link cannot be guaranteed. Therefore, it is very necessary to design a digital-based smart factory management method and system to improve accuracy and production efficiency. Summary of the Invention

[0004] The purpose of the present invention is to provide a digital-based smart factory management method and system to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a digital-based smart factory management method, comprising:

[0006] Evaluate the comprehensive health score of the production equipment at the target time based on the pre-trained equipment maintenance prediction model, and determine the first maintenance time of the production equipment according to the comprehensive health score of the equipment;

[0007] Obtaining a first maintenance duration for the production equipment based on a difference between the real-time operating status of the production equipment and the ideal operating status, analyzing the number of components that failed to be produced as planned due to the production equipment during the first maintenance duration, and weighting and allocating the number of components to each production equipment based on the real-time operating status of the production equipment and the comprehensive health score of the equipment;

[0008] Obtaining an adjusted load of the production equipment, obtaining a damage coefficient for each component of the production equipment based on the adjusted load, adjusting the first maintenance time to the second maintenance time, and adjusting the first maintenance duration to the second maintenance duration based on the damage coefficient, identifying a difference between the second maintenance times of production equipment with adjacent second maintenance times, determining whether the equipment to be maintained first can be maintained within the difference, analyzing the difference between the second maintenance time of the equipment and the expected maintenance time if the maintenance cannot be completed, analyzing the number of components that need to be adjusted based on the difference, and adjusting the equipment based on the number of components;

[0009] Develop production plans and perform production and equipment maintenance based on the current maintenance time, maintenance duration and load standards of production equipment.

[0010] According to the above technical solution, the adjusted load of the production equipment is obtained, the damage coefficient of each component of the production equipment is obtained based on the adjusted load, the first maintenance time is adjusted to the second maintenance time, and the first maintenance duration is adjusted to the second maintenance duration based on the damage coefficient, the difference between the second maintenance times of production equipment with adjacent second maintenance times is identified, and it is determined whether the equipment to be maintained first can complete maintenance within the difference. When maintenance cannot be completed, the difference between the second maintenance time of the equipment and the expected maintenance time is analyzed, the number of components that need to be adjusted based on the difference is analyzed, and the equipment is adjusted according to the number of components, including the following steps:

[0011] Analyze the damage effect of the adjusted load on each component of the production equipment, search a database for a corresponding damage coefficient based on the damage effect, analyze and adjust the first maintenance time and the first maintenance duration under the damage coefficient to obtain the second maintenance time and the second maintenance duration, sort the production equipment based on the second maintenance time, identify the difference between the second maintenance time of the first equipment and the second equipment, determine whether the difference can meet the second maintenance duration of the first equipment, analyze the relationship between the load and the maintenance time of the production equipment, analyze the load adjustment coefficient based on the relationship, and adjust the load of the production equipment according to the load adjustment coefficient to obtain the first load;

[0012] Analyze the difference in maintenance time of production equipment, analyze the surplus of components that the production equipment can produce after maintenance in the difference, analyze the component demand in the assembly process, identify the surplus of components, weightedly distribute the surplus of components according to the difference in the second maintenance time and the first load of the production equipment, and identify the current load of the production equipment to obtain the second load.

[0013] According to the above technical solution, the damage impact of the adjusted load on each component of the production equipment is analyzed, a database is searched to match the corresponding damage coefficient according to the damage impact, the first maintenance time and the first maintenance duration are adjusted under the damage coefficient to obtain the second maintenance time and the second maintenance duration, the production equipment is sorted based on the second maintenance time, the serial numbers of the equipment in the sorting are identified, the difference between the second maintenance time of the first equipment and the second equipment is identified based on the sequence number, and it is judged whether the difference can meet the second maintenance duration of the first equipment, the relationship between the load and the maintenance time of the production equipment is analyzed based on the judgment result, the load adjustment coefficient is analyzed based on the relationship, and the load of the production equipment is adjusted according to the load adjustment coefficient to obtain the first load, including the following steps;

[0014] Obtain the number of components M4 added to the production equipment, calculate the production efficiency before and after the increase in the number of components M4 using a formula, further convert the load F1 of the production equipment before the increase and the load F2 after the increase, calculate the difference between the load F1 and the load F2, i.e., the load increase, and retrieve the corresponding influence coefficient η of the load increase on the first maintenance time from the database based on the difference;

[0015] Search the database according to the load F2, match the damage coefficient of the production equipment component corresponding to the load F2, and retrieve the corresponding influence weight γ of the influence coefficient η on the first maintenance time in the database according to the damage coefficient of the component;

[0016] Obtain a first maintenance time t1, calculate a second maintenance time t2 using the formula t2 = η × γ × t1, sort the production equipment in descending order according to the second maintenance time to obtain a second maintenance schedule for the production equipment, and mark the corresponding production equipment according to the order in the second maintenance schedule, with the order marking marking the production equipment as first equipment, second equipment, third equipment, and so on;

[0017] Obtain the load F2 and search the knowledge graph set in the database to match the corresponding load on the operating status of the production equipment. Search the database according to the influence relationship, retrieve the corresponding influence coefficient ε on the first maintenance duration in the database, obtain the first maintenance duration T1, and calculate the second maintenance duration T2 by the formula T2 = ε × T1;

[0018] Identify the marks in the production equipment and the corresponding second maintenance time, calculate the difference t3 between the second maintenance times of the first device and the second device. If t3 < T2, then bind the first device and the second device and mark them as conflict devices, and traverse the second maintenance time table to determine all conflict devices. Otherwise, bind the first device and the second device and mark them as normal devices. Here, only the first device and the second device are used as examples, and it is not a two - time operation on the first device and the second device. It can be understood that adjacent devices with conflicts are bound and marked as conflict devices, and adjacent devices without conflicts are bound and marked as normal devices;

[0019] Identify the marks in the production equipment. When there are only conflict device marks in the production equipment, retrieve the set load adjustment coefficient ω in the database according to the value of T2 - t3, and calculate the load F3 that the second device needs to adjust through the formula F3 = ω×F2, and allocate the load F3 to the first device.

[0020] When there are both conflict device marks and normal device marks in the production equipment, identify the sequence marks in the conflict devices. When the conflict devices are the first device and the second device, after adjusting the load of the second device to the first device, identify the adjusted load F4 of the second device, calculate the third maintenance time and the third maintenance duration T3 of the second device under this load, obtain the second maintenance time and the second maintenance duration of the third device, calculate the difference t4 between the third maintenance time of the second device and the second maintenance time of the third device, retrieve the corresponding influence weight σ of the load adjustment coefficient ω in the database according to the value of t4 - T3, and calculate the load F4 that the second device needs to adjust through the formula F4 = σ×ω×F2, and allocate the load F4 to the first device, and mark the adjusted load of the production equipment as the first load.

[0021] According to the above technical solution, analyze the difference in the maintenance time of the production equipment, analyze the surplus of components that the production equipment that has completed maintenance can produce more during the period of the difference, analyze the surplus of components, and perform weighted distribution on the surplus of components according to the difference in the second maintenance time and the first load of the production equipment, and identify the current load of the production equipment to obtain the second load, including the following steps:

[0022] Obtain the component production of the first device after maintenance, calculate the increased component production M5 of the first device per unit time after maintenance, obtain the time when the maintenance of the first device is completed, identify the difference t5 between the maintenance completion time of the first device and the third maintenance time of the second device, calculate the total component production increased after the maintenance of the first device is completed by the formula M6 = t5 × M5, obtain the difference in maintenance time between adjacent production equipment, retrieve the allocation weight ψ for the increased total component production in the database based on the difference, obtain the first load of each production equipment, retrieve the database based on the first load, and retrieve the allocation weight for the increased total component production set in the database Calculate component reduction in production equipment using the formula The number of components produced by the corresponding production equipment is adjusted according to the component reduction amount, and the adjusted production equipment load is identified to obtain a second load.

[0023] According to the above technical solution, the method of evaluating the comprehensive health score of the production equipment at the target time based on the pre-trained equipment maintenance prediction model and determining the first maintenance time of the production equipment according to the comprehensive health score of the equipment includes the following steps:

[0024] Obtain historical production data and historical maintenance data, identify the interval time period between production equipment maintenance in the historical maintenance data to obtain the maintenance cycle, anchor the corresponding historical production data segment according to the maintenance cycle, bind it, identify the component output M1 of the production equipment in the historical production data segment, obtain the theoretical component output M2 of the production equipment, and calculate the production efficiency of the production equipment through the formula The production efficiency is converted into the load of the production equipment F = δ × Q, where δ represents the conversion coefficient;

[0025] Identify the operating status data of each component of the production equipment in the maintenance cycle in the historical maintenance data, retrieve the load F of the corresponding production equipment from the database according to the maintenance cycle, bind the load F with the operating status data of each component to construct a sample data set, retrieve the algorithm from the database, use the algorithm to build a model, inject the sample data set into the model for model training to obtain a state prediction model;

[0026] Obtain the type of component and its usage time t1, retrieve the corresponding health score attenuation model in the database according to the type of component, inject the usage time t1 into the attenuation model to obtain the attenuation coefficient α,

[0027] Predicting the operating status data of the production equipment at the target time according to the state prediction model, identifying the operating status characteristics of the production equipment, and retrieving the corresponding influence coefficient β on the component health score in the database according to the operating characteristics;

[0028] Acquire real-time operating status data of the production equipment, retrieve the basic health value score P0 set in the database based on the real-time operating status data, and calculate the actual health score of the production equipment parts at the target time using the formula P = α × β × P0;

[0029] Identify the type of parts of the production equipment, search the database according to the type of parts, retrieve the corresponding mutual influence relationship of parts, and retrieve the actual health score fusion weight of the corresponding parts in the database according to the influence relationship Calculate the comprehensive health score of production equipment at the target time through the formula Wherein, i=1, 2, 3...n, identifies the health score of the production equipment at the target time. When the comprehensive health score is less than the minimum threshold at the target time, the target time is marked as the first maintenance time t1 of the production equipment.

[0030] According to the above technical solution, the method includes obtaining a first maintenance duration of the production equipment based on the difference between the real-time operating status of the production equipment and the ideal operating status, analyzing the number of components that failed to be produced as planned due to the production equipment during the first maintenance duration, and weighting and allocating the number of components to each production equipment based on the real-time operating status of the production equipment and the comprehensive health score of the equipment, including the following steps:

[0031] analyzing the real-time operating status data of the production equipment, analyzing the impact of the status data on the maintenance duration to obtain a first maintenance duration for the production equipment, analyzing the impact of the real-time status data of the production equipment on the production volume of the production equipment to obtain a production speed for the production equipment, obtaining a number of missing components based on the maintenance duration and the production speed, and analyzing the health score and operating status data of the production equipment to allocate a number of components to the production equipment, thereby obtaining a number of components that need to be added to each production equipment;

[0032] Acquire historical maintenance data, identify historical operating status characteristics of production equipment in each maintenance cycle and the corresponding historical maintenance duration, bind the historical operating status characteristics with the historical maintenance duration to obtain maintenance characteristics, compare the maintenance characteristics of each maintenance cycle, and determine the impact coefficient φ of the operating status characteristics of production equipment on maintenance duration;

[0033] Identify the real-time operating status characteristics of the production equipment, search the database according to the operating status characteristics, retrieve the corresponding theoretical maintenance duration T0, calculate the actual maintenance duration of the production equipment according to the formula T1=φ×T0, and mark the actual maintenance duration as the first maintenance duration;

[0034] Obtain the real-time production speed V0 of the production equipment, retrieve the corresponding coefficient ε of the production speed of the production equipment from the database based on the real-time operation characteristics of the production equipment, and calculate the number of components missing from the production equipment during the maintenance period using the formula M3 = T1 × V0;

[0035] According to the real-time operating status characteristics and comprehensive health score retrieval database of the production equipment, the corresponding component quantity allocation coefficients λ and μ in the database are retrieved, and the number of components allocated to the production equipment is calculated by the formula M4 = λ×μ×M3, and the number of components produced by the production equipment is adjusted according to the component quantity M4.

[0036] According to the above technical solution, the production plan is formulated based on the current maintenance time, maintenance duration and load standard of the production equipment and the production and equipment maintenance is carried out, including the following steps:

[0037] Obtain the maintenance time, maintenance duration, and load of the last adjustment of the production equipment, mark the maintenance time, maintenance duration, and load of the last adjustment as the target maintenance time, target maintenance duration, and target load, generate a production plan corresponding to each production equipment according to the target maintenance time, target maintenance duration, and target load of the production equipment, and control the production equipment to perform production according to the production plan.

[0038] According to the above technical solution, the digital-based smart factory management system includes a data acquisition module, an equipment maintenance prediction module, a production adjustment module and an equipment maintenance module;

[0039] The data acquisition module is used to establish a production database, collect the operating status data of the production equipment in real time, and store the operating status data in the production database, and enter the historical production data and historical maintenance data of the production equipment into the production database;

[0040] The equipment maintenance prediction module is used to evaluate the comprehensive health score of the production equipment at the target time based on the pre-trained equipment maintenance prediction model, and determine the first maintenance time of the production equipment according to the comprehensive health score of the equipment;

[0041] The production adjustment module obtains a first maintenance duration for the production equipment based on the difference between the real-time operating status and the ideal operating status of the production equipment, analyzes the number of components that were not produced as planned by the production equipment during the first maintenance duration, and distributes the number of components to each production equipment in a weighted manner based on the real-time operating status and the comprehensive health score of the production equipment;

[0042] Obtaining an adjusted load of the production equipment, obtaining a damage coefficient for each component of the production equipment based on the adjusted load, adjusting the first maintenance time to the second maintenance time, and adjusting the first maintenance duration to the second maintenance duration based on the damage coefficient, identifying a difference between the second maintenance times of production equipment with adjacent second maintenance times, determining whether the equipment to be maintained first can be maintained within the difference, analyzing the difference between the second maintenance time of the equipment and the expected maintenance time if the maintenance cannot be completed, analyzing the number of components that need to be adjusted based on the difference, and adjusting the equipment based on the number of components;

[0043] The equipment maintenance module is used to formulate a production plan and perform production and equipment maintenance based on the current maintenance time, maintenance duration and load standard of the production equipment.

[0044] According to the above technical solution, the production adjustment module is also used to:

[0045] Analyze the damage impact of the adjusted load on each component of the production equipment, search the database to match the corresponding damage coefficient according to the damage impact, analyze the adjustment of the first maintenance time and the first maintenance duration under the damage coefficient, obtain the second maintenance time and the second maintenance duration, sort the production equipment based on the second maintenance time, identify the serial number of the equipment in the sorting, identify the difference between the second maintenance time of the first equipment and the second equipment based on the sequence number, judge whether the difference can meet the second maintenance duration of the first equipment, analyze the relationship between the load and maintenance time of the production equipment based on the judgment result, analyze the load adjustment coefficient based on the relationship, and adjust the load of the production equipment according to the load adjustment coefficient to obtain the first load.

[0046] According to the above technical solution, the production adjustment module is also used to:

[0047] Analyze the difference in maintenance time of production equipment, analyze the surplus of components that the production equipment can produce after maintenance in the difference, analyze the component demand in the assembly process, identify the surplus of components, weightedly distribute the surplus of components according to the difference in the second maintenance time and the first load of the production equipment, and identify the current load of the production equipment to obtain the second load.

[0048] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention can accurately calculate the comprehensive health score of the production equipment at the target time by analyzing the operating status of the production equipment, the health value attenuation of the components and the mutual influence relationship between the various components, and thus can accurately judge the maintenance time of the production equipment, and can provide accurate data support for the subsequent adjustment of the load of the production equipment, thereby greatly improving the accuracy of production adjustment, and by analyzing the impact of the operating status of the production equipment on the maintenance time, and then accurately calculating the maintenance time of the production equipment, and further accurately obtaining the number of components missing from the production equipment, and analyzing the real-time operating status characteristics and comprehensive health score of the production equipment to distribute the number of missing components to each production equipment, thereby ensuring that the production equipment has a sufficient number of components during the maintenance period to ensure the component requirements of the assembly link, so that the production efficiency of the assembly link is guaranteed, This will greatly improve the production efficiency of the assembly process. By analyzing the impact of the production equipment on the maintenance time and maintenance duration after the load is adjusted, the second maintenance time and the second maintenance duration can be accurately obtained, and it can be further judged whether the equipment will have a conflict during the maintenance process. At the same time, when it is judged that a maintenance conflict will occur, the load of the production equipment is adjusted again to avoid maintenance conflicts and ensure the production quantity of components. This can avoid the number of components produced due to equipment maintenance conflicts not being able to meet the needs of the assembly process, thereby greatly improving the accuracy of the system and ensuring production efficiency. By analyzing the output that can be increased by the production equipment after maintenance, the load of the production equipment is adjusted, that is, the pre-load of each device is adjusted to reduce the load of the production equipment. At the same time, it can also ensure that the assembly process has enough components for assembly, greatly improving the load adjustment accuracy of the system and the production efficiency of the assembly process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0050] Figure 1 It is a flow chart of the method steps of the present invention.

[0051] Figure 2 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] See also Figure 1 The present invention provides a technical solution: a digital-based smart factory management method, comprising:

[0054] Step S1: Establish a production database, collect the operating status data of the production equipment in real time, store the operating status data in the production database, and enter the historical production data and historical maintenance data of the production equipment into the production database;

[0055] Step S2: Acquire historical production data and historical maintenance data, analyze damage data of various components of the production equipment and the impact of production load on the components of the production equipment, train an equipment maintenance prediction model based on the damage data and the impact, evaluate the health score of the production equipment at the target time based on the equipment maintenance prediction model, and determine the first maintenance time of the production equipment based on the health score;

[0056] Step S3: obtaining a first maintenance duration for the production equipment based on the difference between the real-time operating status of the production equipment and the ideal operating status, analyzing the number of components that failed to be produced as planned due to the production equipment during the first maintenance duration, and weighting and allocating the number of components to each production equipment based on the real-time operating status of the production equipment and the comprehensive health score of the equipment;

[0057] Obtain an adjusted load for the production equipment, obtain a damage coefficient for each component of the production equipment based on the adjusted load, adjust the first maintenance time to the second maintenance time, and adjust the first maintenance duration to the second maintenance duration based on the damage coefficient, identify the difference between the second maintenance times of production equipment with adjacent second maintenance times, determine whether the equipment to be maintained first can complete maintenance within the difference, analyze the difference between the second maintenance time of the equipment and the expected maintenance time when the maintenance cannot be completed, analyze the number of components that need to be adjusted based on the difference, and adjust the equipment according to the number of components.

[0058] Step S4: Formulate a production plan and perform production and equipment maintenance based on the current maintenance time, maintenance duration, and load standard of the production equipment.

[0059] In the present invention, by analyzing the impact of the operating status of production equipment on maintenance duration, the maintenance duration of production equipment is accurately calculated, and the number of missing components of the production equipment can be accurately obtained. The real-time operating status characteristics and comprehensive health scores of the production equipment are analyzed to allocate the missing component numbers to each production equipment, thereby ensuring that the production equipment has sufficient components during maintenance to meet the component requirements of the assembly process, ensuring the production efficiency of the assembly process, and thus greatly improving the production efficiency of the assembly process. By analyzing the impact of the production equipment on the maintenance time and maintenance duration after load adjustment, the second maintenance time and second maintenance duration can be accurately obtained, and further judgment is made on whether a conflict will occur during the maintenance process of the equipment. When it is determined that a maintenance conflict will occur, the load of the production equipment is adjusted to avoid maintenance conflicts and ensure the production quantity of components. This can avoid the production quantity of components that cannot meet the requirements of the assembly process due to equipment maintenance conflicts, thereby greatly improving the accuracy of the system and ensuring production efficiency. By analyzing the increase in production output of the production equipment after maintenance, the load of the production equipment is adjusted, that is, the preload of each equipment is adjusted to reduce the load of the production equipment, and at the same time, it can ensure that the assembly process has sufficient components for assembly, greatly improving the load adjustment accuracy of the system and the production efficiency of the assembly process.

[0060] In some preferred embodiments, step S2 further comprises the following steps:

[0061] Step S21: Obtain historical production data and historical maintenance data, identify the interval time period between production equipment maintenance in the historical maintenance data to obtain the maintenance cycle, anchor the corresponding historical production data segment according to the maintenance cycle, bind it, identify the component output M1 of the production equipment in the historical production data segment, obtain the theoretical component output M2 of the production equipment, and calculate the production efficiency of the production equipment through the formula The production efficiency is converted into the load of the production equipment F = δ × Q, where δ represents the conversion coefficient;

[0062] Step S22: Identify the operating status data of each component of the production equipment during the maintenance cycle in the historical maintenance data, retrieve the load F of the corresponding production equipment from the database according to the maintenance cycle, bind the load F with the operating status data of each component to construct a sample data set, retrieve the algorithm from the database, use the algorithm to build a model, inject the sample data set into the model for model training to obtain a state prediction model;

[0063] Step S23: Obtain the type of component and the usage time t1, retrieve the corresponding health score attenuation model in the database according to the type of component, inject the usage time t1 into the attenuation model to obtain the attenuation coefficient α,

[0064] Predicting the operating status data of the production equipment at the target time according to the state prediction model, identifying the operating status characteristics of the production equipment, and retrieving the corresponding influence coefficient β on the component health score in the database according to the operating characteristics;

[0065] Acquire real-time operating status data of the production equipment, retrieve the basic health value score P0 set in the database based on the real-time operating status data, and calculate the actual health score of the production equipment parts at the target time using the formula P = α × β × P0;

[0066] Identify the type of parts of the production equipment, search the database according to the type of parts, retrieve the corresponding mutual influence relationship of parts, and retrieve the actual health score fusion weight of the corresponding parts in the database according to the influence relationship Calculate the comprehensive health score of production equipment at the target time through the formula Among them, i=1,2,3...n, identifies the health score of the production equipment at the target time. When the comprehensive health score is less than the minimum threshold at the target time, it means that the production equipment needs maintenance at the target time, and the target time is marked as the first maintenance time t1 of the production equipment. By analyzing the operating status of the production equipment, the health value decay of the components and the mutual influence relationship between the components, the comprehensive health score of the production equipment at the target time can be accurately calculated, and then the maintenance time of the production equipment can be accurately judged, which can provide accurate data support for the subsequent adjustment of the load of the production equipment, greatly improving the accuracy of production adjustment.

[0067] In some preferred embodiments, step S3 further comprises the following steps:

[0068] Step S31: Analyze the real-time operating status data of the production equipment, analyze the impact of the status data on the maintenance duration to obtain a first maintenance duration for the production equipment, analyze the impact of the real-time status data of the production equipment on the production volume of the production equipment to obtain the production speed of the production equipment, obtain the number of missing components based on the maintenance duration and the production speed, analyze the health score and operating status data of the production equipment to allocate the number of components to the production equipment, and obtain the number of components that need to be added to each production equipment;

[0069] Exemplarily, historical maintenance data is obtained, historical operating status characteristics of production equipment in each maintenance cycle and corresponding historical maintenance duration are identified, the historical operating status characteristics are bound to the historical maintenance duration to obtain maintenance characteristics, the maintenance characteristics of each maintenance cycle are compared, and an influence coefficient φ of the operating status characteristics of the production equipment on the maintenance duration is obtained;

[0070] Identify the real-time operating status characteristics of the production equipment, search the database according to the operating status characteristics, retrieve the corresponding theoretical maintenance duration T0, calculate the actual maintenance duration of the production equipment according to the formula T1=φ×T0, and mark the actual maintenance duration as the first maintenance duration;

[0071] Obtain the real-time production speed V0 of the production equipment, retrieve the corresponding coefficient ε of the production speed of the production equipment from the database based on the real-time operation characteristics of the production equipment, and calculate the number of components missing from the production equipment during the maintenance period using the formula M3 = T1 × V0;

[0072] According to the real-time operating status characteristics and comprehensive health score of the production equipment, the database is retrieved, and the corresponding component quantity allocation coefficients λ and μ in the database are retrieved. The component quantity M4 = λ×μ×M3 allocated to the production equipment is calculated by the formula, and the number of components produced by the production equipment is adjusted according to the component quantity M4, that is, the load of the production equipment is increased. By analyzing the impact of the operating status of the production equipment on the maintenance time, the maintenance time of the production equipment can be accurately calculated, and the number of components missing from the production equipment can be accurately obtained. The real-time operating status characteristics and comprehensive health score of the production equipment are analyzed to allocate the missing component quantity to each production equipment, thereby ensuring that the production equipment has a sufficient number of components during the maintenance period to ensure the component requirements of the assembly link, so that the production efficiency of the component link is guaranteed, thereby greatly improving the production efficiency of the assembly link.

[0073] Step S32: analyzing the damage effect of the adjusted load on each component of the production equipment, searching a database for a corresponding damage coefficient based on the damage effect, analyzing the adjustment of the first maintenance time and the first maintenance duration under the damage coefficient to obtain the second maintenance time and the second maintenance duration, sorting the production equipment based on the second maintenance time, identifying the sequence numbers of the equipment in the sorting, identifying the difference between the second maintenance time of the first equipment and the second equipment based on the sequence numbers, judging whether the difference can meet the second maintenance duration of the first equipment, analyzing the relationship between the load and the maintenance time of the production equipment based on the judgment result, analyzing the load adjustment coefficient based on the relationship, and adjusting the load of the production equipment according to the load adjustment coefficient to obtain the first load;

[0074] Exemplarily, the number of components M4 added to the production equipment is obtained, and the production efficiency before and after the increase in the number of components M4 is calculated using a formula. This is further converted to obtain the load F1 of the production equipment before the increase and the load F2 after the increase. The difference between the load F1 and the load F2 is calculated, i.e., the load increase. Based on the difference, a database is retrieved to retrieve the corresponding influence coefficient η of the load increase on the first maintenance time.

[0075] Retrieve the database according to the load F2, match the damage coefficient of the production equipment parts corresponding to the load F2, and retrieve the database according to the damage coefficient of the parts to obtain the influence weight γ of the corresponding influence coefficient η on the first maintenance time;

[0076] Obtain the first maintenance time t1, calculate the second maintenance time t2 = η×γ×t1 through the formula, sort the production equipment in descending order according to the second maintenance time to obtain the second maintenance schedule of the production equipment, and mark the corresponding production equipment according to the order in the second maintenance schedule. The order mark marks the production equipment as the first equipment, the second equipment, the third production equipment, etc.;

[0077] Retrieve the influence relationship of the load on the operation state of the production equipment matched by the knowledge graph set in the database according to the load F2, retrieve the database according to the influence relationship, and obtain the influence coefficient ε corresponding to the first maintenance duration. Obtain the first maintenance duration T1, and calculate the second maintenance duration T2 = ε×T1 through the formula;

[0078] Identify the mark in the production equipment and the corresponding second maintenance time, calculate the difference t3 between the second maintenance times of the first equipment and the second equipment. If t3 < T2, it means that there will be a conflict between the maintenance time of the first equipment and the maintenance time of the second maintenance equipment. Bind the first equipment and the second equipment and mark them as conflict equipment. Traverse the second maintenance schedule to determine all conflict equipment. Otherwise, bind the first equipment and the second equipment and mark them as normal equipment. Here, only the first equipment and the second equipment are used as examples, and it is not an operation on the first equipment and the second equipment twice. It can be understood that the adjacent equipment that conflicts is bound and marked as conflict equipment, and the adjacent equipment that does not conflict is bound and marked as normal equipment;

[0079] Identify the mark in the production equipment. When there is only a conflict equipment mark in the production equipment, retrieve the load adjustment coefficient ω set in the database according to the value of T2 - t3, and calculate the load F3 that the second equipment needs to adjust through the formula F3 = ω×F2, and allocate the load F3 to the first equipment;

[0080] When there are both conflicting device marks and normal device marks in the production equipment, it means that the device in the middle conflicts with one of the adjacent devices. Identify the sequence mark in the conflicting device. When the conflicting devices are the first device and the second device, it means that the second device and the third device will not conflict. After adjusting the load of the second device to the first device, identify the adjusted load F4 of the second device, calculate the third maintenance time and the third maintenance duration T3 of the second device under the load, obtain the second maintenance time and the second maintenance duration of the third device, calculate the difference t4 between the third maintenance time of the second device and the second maintenance time of the third device, and retrieve the corresponding value in the database based on the value of t4-T3. The influence weight σ of the load adjustment coefficient ω is calculated by the formula F4 = σ × ω × F2 that the second device needs to adjust, and the load F4 is distributed to the first device. The load after the production equipment is adjusted is marked as the first load. By analyzing the influence of the production equipment on the maintenance time and maintenance duration after the load is adjusted, the second maintenance time and the second maintenance duration can be accurately obtained, and it is further judged whether the equipment will conflict during the maintenance process. At the same time, when it is judged that a maintenance conflict will occur, the load of the production equipment is adjusted again to avoid maintenance conflicts and ensure the production quantity of components. This can avoid the inability of the number of components produced to meet the needs of the assembly link due to equipment maintenance conflicts, thereby greatly improving the accuracy of the system and ensuring production efficiency.

[0081] Step S33: Analyzing the difference in maintenance time of the production equipment, analyzing the surplus amount of components that can be produced by the production equipment that has completed maintenance within the time period of the difference, analyzing the surplus amount of components, weighting and allocating the surplus amount of components according to the second maintenance time difference and the first load of the production equipment, and identifying the current load of the production equipment to obtain a second load;

[0082] Exemplarily, the component output of the first device after maintenance is obtained, the increased component output M5 of the first device after maintenance is calculated, the time when the maintenance of the first device is completed is obtained, the difference t5 between the maintenance completion time of the first device and the third maintenance time of the second device is identified, the total component output increased after the maintenance of the first device is completed is calculated by the formula M6 = t5 × M5, the difference in maintenance time between adjacent production devices is obtained, the weight ψ of the component reduction amount in the database is retrieved according to the difference, the component reduction amount of the production equipment is calculated by the formula M7 = ψ × M6, the corresponding production equipment is adjusted according to the component reduction amount, the adjusted production equipment load is identified to obtain the second load, and the load of the production equipment is adjusted by analyzing the output that the production equipment can increase after maintenance, that is, the pre-load of each device is adjusted to reduce the load of the production equipment. At the same time, it can also ensure that there are enough components for assembly in the assembly link, greatly improving the load adjustment accuracy of the system and the production efficiency of the assembly link.

[0083] In some preferred embodiments, step S4 further comprises the following steps:

[0084] Obtain the maintenance time, maintenance duration and second load of the production equipment, generate a production plan corresponding to each production equipment according to the maintenance time, maintenance duration and second load of the production equipment, and control the production equipment to perform production according to the production plan.

[0085] Using the same inventive concept as the above embodiment, the present application also provides a digital-based smart factory management system, including a data acquisition module, an equipment maintenance prediction module, a production adjustment module, and an equipment maintenance module;

[0086] The data acquisition module is used to establish a production database, collect the operating status data of the production equipment in real time, store the operating status data in the production database, and enter the historical production data and historical maintenance data of the production equipment into the production database;

[0087] The equipment maintenance prediction module is used to obtain historical production data and historical maintenance data, analyze the damage data of various components of the production equipment and the impact of production load on the components of the production equipment, train an equipment maintenance prediction model based on the damage data and the impact, evaluate the health score of the production equipment at the target time based on the equipment maintenance prediction model, and determine the first maintenance time of the production equipment based on the health score;

[0088] The production adjustment module is used to analyze the real-time operating status of production equipment, estimate the first maintenance duration of the production equipment based on the difference between the real-time operating status and the ideal operating status, analyze the number of components missing from the production equipment during maintenance, and weight the number of components to each production equipment based on the operating status of the production equipment and the comprehensive health score of the equipment;

[0089] Obtaining a first maintenance duration for the production equipment based on the difference between the real-time operating status of the production equipment and the ideal operating status, analyzing the number of components that failed to be produced as planned due to the production equipment during the first maintenance duration, and allocating the number of components to each production equipment based on the real-time operating status of the production equipment and the comprehensive health score of the equipment;

[0090] Obtaining an adjusted load of the production equipment, obtaining a damage coefficient for each component of the production equipment based on the adjusted load, adjusting the first maintenance time to the second maintenance time, and adjusting the first maintenance duration to the second maintenance duration based on the damage coefficient, identifying a difference between the second maintenance times of production equipment with adjacent second maintenance times, determining whether the equipment to be maintained first can be maintained within the difference, analyzing the difference between the second maintenance time of the equipment and the expected maintenance time if the maintenance cannot be completed, analyzing the number of components that need to be adjusted based on the difference, and adjusting the equipment based on the number of components;

[0091] The equipment maintenance module is used to formulate production plans and perform production and equipment maintenance based on the current maintenance time, maintenance duration and load standards of production equipment.

[0092] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0093] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A digital-based smart factory management method, characterized by: The method comprises: Evaluate the comprehensive health score of the production equipment at the target time based on the pre-trained equipment maintenance prediction model, and determine the first maintenance time of the production equipment according to the comprehensive health score of the equipment; Obtaining a first maintenance duration for the production equipment based on a difference between the real-time operating status of the production equipment and the ideal operating status, analyzing the number of components that failed to be produced as planned due to the production equipment during the first maintenance duration, and weighting and allocating the number of components to each production equipment based on the real-time operating status of the production equipment and the comprehensive health score of the equipment; Obtaining an adjusted load of the production equipment, obtaining a damage coefficient for each component of the production equipment based on the adjusted load, adjusting the first maintenance time to the second maintenance time, and adjusting the first maintenance duration to the second maintenance duration based on the damage coefficient, identifying a difference between the second maintenance times of production equipment with adjacent second maintenance times, determining whether the equipment to be maintained first can be maintained within the difference, analyzing the difference between the second maintenance time of the equipment and the expected maintenance time if the maintenance cannot be completed, analyzing the number of components that need to be adjusted based on the difference, and adjusting the equipment based on the number of components; Develop production plans and perform production and equipment maintenance based on the current maintenance time, maintenance duration and load standards of production equipment.

2. The digital-based smart factory management method according to claim 1, characterized in that: The method includes obtaining an adjusted load of the production equipment, obtaining a damage coefficient for each component of the production equipment based on the adjusted load, adjusting the first maintenance time to the second maintenance time, adjusting the first maintenance duration to the second maintenance duration based on the damage coefficient, identifying a difference between the second maintenance times of production equipment with adjacent second maintenance times, determining whether the equipment maintained first can complete maintenance within the difference, analyzing the difference between the second maintenance time of the equipment and the expected maintenance time when maintenance cannot be completed, analyzing the number of components that need to be adjusted based on the difference, and adjusting the equipment based on the number of components, including the following steps: Analyze the damage effect of the adjusted load on each component of the production equipment, search a database for matching corresponding damage coefficients based on the damage effect, analyze and adjust the first maintenance time and the first maintenance duration under the damage coefficient to obtain the second maintenance time and the second maintenance duration, sort the production equipment based on the second maintenance time, identify the serial numbers of the equipment in the sort, identify the difference between the second maintenance time of the first equipment and the second equipment based on the serial numbers, determine whether the difference can meet the second maintenance duration of the first equipment, analyze the relationship between the load and the maintenance time of the production equipment based on the determination result, analyze the load adjustment coefficient based on the relationship, and adjust the load of the production equipment according to the load adjustment coefficient to obtain the first load; Analyze the difference in maintenance time of production equipment, analyze the surplus of components that can be produced by the production equipment that has completed maintenance within the time period of the difference, analyze the surplus of components, weightedly distribute the surplus of components according to the difference in the second maintenance time and the first load of the production equipment, and identify the current load of the production equipment to obtain the second load.

3. The digital-based smart factory management method according to claim 2, characterized in that: Analyze the damage impact of the adjusted load on each component of the production equipment, retrieve the corresponding damage coefficient from the database based on the damage impact, analyze and adjust the first maintenance time and the first maintenance duration under the damage coefficient to obtain the second maintenance time and the second maintenance duration, sort the production equipment based on the second maintenance time, identify the serial number of the equipment in the sorting, identify the difference in the second maintenance time between the first equipment and the second equipment based on the serial number, determine whether the difference can meet the second maintenance duration of the first equipment, analyze the relationship between the production equipment load and the maintenance time based on the judgment result, analyze the load adjustment coefficient based on the relationship, and adjust the load of the production equipment according to the load adjustment coefficient to obtain the first load, including the following steps; Obtain the number of additional components M4 of the production equipment, calculate the production efficiency before and after the increase in the number of components M4 of the production equipment through a formula, and further convert to obtain the load F1 before the increase in the production equipment and the load F2 after the increase. Calculate the difference between the load F1 and the load F2, that is, the load increase amount, and retrieve the influence coefficient η of the corresponding load increase amount on the first maintenance time from the database according to the difference; Retrieve the database according to the load F2, match the damage coefficient of the production equipment components corresponding to the load F2, and retrieve the influence weight γ of the corresponding influence coefficient η on the first maintenance time from the database according to the damage coefficient of the components; Obtain the first maintenance time t1, calculate the second maintenance time t2 = η×γ×t1 through a formula, sort the production equipment in descending order according to the second maintenance time to obtain the second maintenance time table of the production equipment, and mark the corresponding production equipment according to the ranking order in the second maintenance time table; Obtain the influence relationship of the load on the operation state of the production equipment corresponding to the load F2 retrieved from the database by matching the knowledge graph set in the database. Retrieve the database according to the influence relationship, retrieve the influence coefficient ε of the corresponding influence on the first maintenance duration from the database, obtain the first maintenance duration T1, and calculate the second maintenance duration T2 = ε×T1 through a formula; Identify the marks in the production equipment and the corresponding second maintenance time, calculate the difference t3 in the second maintenance time between the first equipment and the second equipment. If t3 < T2, bind the first equipment and the second equipment and mark them as conflict equipment, traverse the second maintenance time table to determine all conflict equipment, otherwise bind the first equipment and the second equipment and mark them as normal equipment; Identify the marks in the production equipment. When there are only conflict equipment marks in the production equipment, retrieve the load adjustment coefficient ω set in the database according to the value of T2 - t3, calculate the load F3 that the second equipment needs to adjust through a formula F3 = ω×F2, and allocate the load F3 to the first equipment When there are both conflicting equipment marks and normal equipment marks in the production equipment, the sequence mark in the conflicting equipment is identified. When the conflicting equipment is the first equipment and the second equipment, after adjusting the load of the second equipment to the first equipment, the adjusted load F4 of the second equipment is identified, the third maintenance time and the third maintenance duration T3 of the second equipment under the load are calculated, the second maintenance time and the second maintenance duration of the third equipment are obtained, the difference t4 between the third maintenance time of the second equipment and the second maintenance time of the third equipment is calculated, and the database is retrieved according to the value of t4-T3 to retrieve the corresponding influence weight σ on the load adjustment coefficient ω in the database, and the load F4 that needs to be adjusted for the second equipment is calculated by the formula F4=σ×ω×F2, the load F4 is allocated to the first equipment, and the adjusted load of the production equipment is marked as the first load.

4. The digital-based smart factory management method according to claim 2, characterized in that: The analyzing the difference in maintenance time of the production equipment, analyzing the surplus of components that can be produced by the production equipment that has completed maintenance within the time period of the difference, analyzing the surplus of components, weightedly allocating the surplus of components according to the second maintenance time difference and the first load of the production equipment, and identifying the current load of the production equipment to obtain the second load includes the following steps: Obtain the component production of the first device after maintenance, calculate the increased component production M5 of the first device per unit time after maintenance, obtain the time when the maintenance of the first device is completed, identify the difference t5 between the maintenance completion time of the first device and the third maintenance time of the second device, calculate the total component production increased after the maintenance of the first device is completed by the formula M6 = t5 × M5, obtain the difference in maintenance time between adjacent production equipment, retrieve the allocation weight ψ for the increased total component production in the database based on the difference, obtain the first load of each production equipment, retrieve the database based on the first load, and retrieve the allocation weight for the increased total component production set in the database Calculate component reduction in production equipment using the formula The number of components produced by the corresponding production equipment is adjusted according to the component reduction amount, and the adjusted production equipment load is identified to obtain a second load.

5. The digital-based smart factory management method according to claim 1, characterized in that: The method of evaluating the comprehensive health score of the production equipment at the target time based on the pre-trained equipment maintenance prediction model and determining the first maintenance time of the production equipment according to the comprehensive health score of the equipment includes the following steps: Obtain historical production data and historical maintenance data, identify the interval time period between production equipment maintenance in the historical maintenance data to obtain the maintenance cycle, anchor the corresponding historical production data segment according to the maintenance cycle, bind it, identify the component output M1 of the production equipment in the historical production data segment, obtain the theoretical component output M2 of the production equipment, and calculate the production efficiency of the production equipment through the formula The production efficiency is converted into the load of the production equipment F = δ × Q, where δ represents the conversion coefficient; Identify the operating status data of each component of the production equipment in the maintenance cycle in the historical maintenance data, retrieve the load F of the corresponding production equipment from the database according to the maintenance cycle, bind the load F with the operating status data of each component to construct a sample data set, retrieve the algorithm from the database, use the algorithm to build a model, inject the sample data set into the model for model training to obtain a state prediction model; Obtain the type of component and its usage time t1, retrieve the corresponding health score attenuation model in the database according to the type of component, inject the usage time t1 into the attenuation model to obtain the attenuation coefficient α, Predicting the operating status data of the production equipment at the target time according to the state prediction model, identifying the operating status characteristics of the production equipment, and retrieving the corresponding influence coefficient β on the component health score in the database according to the operating characteristics; Acquire real-time operating status data of the production equipment, retrieve the basic health value score P0 set in the database based on the real-time operating status data, and calculate the actual health score of the production equipment parts at the target time using the formula P = α × β × P0; Identify the type of parts of the production equipment, search the database according to the type of the parts, retrieve the corresponding mutual influence relationship of the parts, and retrieve the actual health score fusion weight θ of the corresponding parts in the database according to the influence relationship i , calculate the comprehensive health score of production equipment at the target time through the formula Wherein, i=1, 2, 3...n, identifies the health score of the production equipment at the target time. When the comprehensive health score is less than the minimum threshold at the target time, the target time is marked as the first maintenance time t1 of the production equipment.

6. The digital-based smart factory management method according to claim 1, characterized in that: The first maintenance duration of the production equipment is obtained based on the difference between the real-time operating status of the production equipment and the ideal operating status, the number of components that cannot be produced as planned due to the production equipment during the first maintenance duration is analyzed, and the number of components is weightedly allocated to each production equipment based on the real-time operating status of the production equipment and the comprehensive health score of the equipment. The following steps are included: analyzing the real-time operating status data of the production equipment, analyzing the impact of the status data on the maintenance duration to obtain a first maintenance duration for the production equipment, analyzing the impact of the real-time status data of the production equipment on the production volume of the production equipment to obtain a production speed for the production equipment, obtaining a number of missing components based on the maintenance duration and the production speed, and analyzing the health score and operating status data of the production equipment to allocate a number of components to the production equipment, thereby obtaining a number of components that need to be added to each production equipment; Acquire historical maintenance data, identify historical operating status characteristics of production equipment in each maintenance cycle and the corresponding historical maintenance duration, bind the historical operating status characteristics with the historical maintenance duration to obtain maintenance characteristics, compare the maintenance characteristics of each maintenance cycle, and determine the impact coefficient φ of the operating status characteristics of production equipment on maintenance duration; Identify the real-time operating status characteristics of the production equipment, search the database according to the operating status characteristics, retrieve the corresponding theoretical maintenance duration T0, calculate the actual maintenance duration of the production equipment according to the formula T1=φ×T0, and mark the actual maintenance duration as the first maintenance duration; Obtain the real-time production speed V0 of the production equipment, retrieve the corresponding coefficient ε of the production speed of the production equipment from the database based on the real-time operation characteristics of the production equipment, and calculate the number of components missing from the production equipment during the maintenance period using the formula M3 = T1 × V0; According to the real-time operating status characteristics and comprehensive health score retrieval database of the production equipment, the corresponding component quantity allocation coefficients λ and μ in the database are retrieved, and the number of components allocated to the production equipment is calculated by the formula M4 = λ×μ×M3, and the number of components produced by the production equipment is adjusted according to the component quantity M4.

7. The digital-based smart factory management method according to claim 1, characterized in that: The method of formulating a production plan and performing production and equipment maintenance based on the current maintenance time, maintenance duration, and load standard of the production equipment includes the following steps: Obtain the maintenance time, maintenance duration, and load of the last adjustment of the production equipment, mark the maintenance time, maintenance duration, and load of the last adjustment as the target maintenance time, target maintenance duration, and target load, generate a production plan corresponding to each production equipment according to the target maintenance time, target maintenance duration, and target load of the production equipment, and control the production equipment to perform production according to the production plan.

8. A digital-based smart factory management system, characterized by: The system includes a data acquisition module, an equipment maintenance prediction module, a production adjustment module and an equipment maintenance module; The data acquisition module is used to establish a production database, collect the operating status data of the production equipment in real time, and store the operating status data in the production database, and enter the historical production data and historical maintenance data of the production equipment into the production database; The equipment maintenance prediction module is used to evaluate the comprehensive health score of the production equipment at the target time based on the pre-trained equipment maintenance prediction model, and determine the first maintenance time of the production equipment according to the comprehensive health score of the equipment; The production adjustment module is configured to obtain a first maintenance duration for the production equipment based on a difference between the real-time operating status of the production equipment and the ideal operating status, analyze the number of components that were not produced as planned due to the production equipment during the first maintenance duration, and weightedly allocate the number of components to each production equipment based on the real-time operating status of the production equipment and the comprehensive health score of the equipment; Obtaining an adjusted load of the production equipment, obtaining a damage coefficient for each component of the production equipment based on the adjusted load, adjusting the first maintenance time to the second maintenance time, and adjusting the first maintenance duration to the second maintenance duration based on the damage coefficient, identifying a difference between the second maintenance times of production equipment with adjacent second maintenance times, determining whether the equipment to be maintained first can be maintained within the difference, analyzing the difference between the second maintenance time of the equipment and the expected maintenance time if the maintenance cannot be completed, analyzing the number of components that need to be adjusted based on the difference, and adjusting the equipment based on the number of components; The equipment maintenance module is used to formulate a production plan and perform production and equipment maintenance based on the current maintenance time, maintenance duration and load standard of the production equipment.

9. The digital-based smart factory management system according to claim 8, characterized in that: The production adjustment module is also used to: Analyze the damage impact of the adjusted load on each component of the production equipment, search the database to match the corresponding damage coefficient according to the damage impact, analyze the adjustment of the first maintenance time and the first maintenance duration under the damage coefficient, obtain the second maintenance time and the second maintenance duration, sort the production equipment based on the second maintenance time, identify the serial number of the equipment in the sorting, identify the difference between the second maintenance time of the first equipment and the second equipment based on the sequence number, judge whether the difference can meet the second maintenance duration of the first equipment, analyze the relationship between the load and maintenance time of the production equipment based on the judgment result, analyze the load adjustment coefficient based on the relationship, and adjust the load of the production equipment according to the load adjustment coefficient to obtain the first load.

10. The digital-based smart factory management system according to claim 9, characterized in that: The production adjustment module is also used to: Analyze the difference in maintenance time of production equipment, analyze the surplus of components that can be produced by the production equipment that has completed maintenance within the time period of the difference, analyze the surplus of components, weightedly distribute the surplus of components according to the difference in the second maintenance time and the first load of the production equipment, and identify the current load of the production equipment to obtain the second load.

Images