CN115860278B - Motor assembly production management method and system based on data analysis - Google Patents
Motor assembly production management method and system based on data analysis Download PDFInfo
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- CN115860278B CN115860278B CN202310165705.8A CN202310165705A CN115860278B CN 115860278 B CN115860278 B CN 115860278B CN 202310165705 A CN202310165705 A CN 202310165705A CN 115860278 B CN115860278 B CN 115860278B
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Abstract
The invention relates to a motor assembly production management method and system based on data analysis, which belong to the technical field of production management. The method is used for distributing tasks to the current motor assembly processing equipment according to the fault information of the actual equipment, fully considers the running condition of the equipment, can distribute tasks to the motor assembly processing equipment according to the actual condition, can effectively rationally distribute production tasks in the motor assembly process, ensures that the distribution of the production tasks is more accurate, and ensures that the production of motor assembly is more reasonable.
Description
Technical Field
The invention relates to the technical field of production management, in particular to a motor assembly production management method and system based on data analysis.
Background
The motor assembly requires risk assessment of the product and manufacturing process prior to mass production, particularly during the design phase, in order to prevent greater losses during the mass production phase, which requires a significant amount of time and effort to find the risk and minimize the risk.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a motor assembly production management method and system based on data analysis.
In order to achieve the above purpose, the invention adopts the following technical scheme:
the first aspect of the invention provides a motor assembly production management method based on data analysis, which comprises the following steps:
acquiring information to be assembled of motor assembly in a current production batch, and obtaining estimated time information corresponding to the information to be assembled of motor assembly by estimating the information to be assembled and counting the estimated result;
acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment;
Acquiring processing time information of motor assembly processing equipment in each production area based on estimated time information corresponding to the information to be assembled of the motor assembly and estimated fault time information of the motor assembly processing equipment;
and performing task distribution according to the processing time information of the motor assembly processing equipment to obtain a distribution result, generating a corresponding distribution report based on the distribution result, and outputting the distribution report.
Further, in a preferred embodiment of the present invention, information to be assembled of a motor in a current production lot is obtained, and the estimated time information corresponding to the information to be assembled of the motor is obtained by estimating the information to be assembled and counting the estimated result, which specifically includes the following steps:
acquiring information to be assembled of motor assembly in a current production batch, and extracting characteristics of the information to be assembled of motor assembly in the current production batch to acquire the quantity information of motor assembly in the current production batch;
acquiring assembly efficiency information and quantity information of each specification of motor assembly processing equipment in each current production area;
the assembly efficiency information and the quantity information of each specification of motor assembly processing equipment in the current production areas are converged and counted to obtain the statistical information of each motor assembly processing equipment;
And calculating estimated time information corresponding to the information to be assembled of the motor assembly according to the information of the number of motor assemblies in the current production batch and the statistical information of each motor assembly processing device.
Further, in a preferred embodiment of the present invention, operation information of a motor assembly processing device in each current production area is obtained, and estimated failure time information of the motor assembly processing device is obtained according to the operation information of the motor assembly processing device, which specifically includes the following steps:
acquiring historical operation information of motor assembly processing equipment in each current production area, and extracting characteristics of the historical operation information to acquire fault information under each operation condition;
inputting the fault information under each operation condition into a Bayesian network for training until the Bayesian network meets the preset requirement, so as to output the Bayesian network after the training is completed;
inputting the operation information of the motor assembly processing equipment in each current production area into the Bayesian network to obtain the fault probability of the motor assembly processing equipment within the preset time;
if the fault probability is larger than the preset fault probability, obtaining estimated fault time information of the motor assembly processing equipment with the fault probability larger than the preset fault probability.
Further, in a preferred embodiment of the present invention, the processing time information of the motor assembly processing device in each production area is obtained based on the estimated time information corresponding to the information to be assembled of the motor assembly and the estimated failure time information of the motor assembly processing device, and specifically includes the following steps:
acquiring a fault type corresponding to current motor assembly processing equipment, if the fault type is a restorative maintenance fault type, acquiring estimated maintenance time information of the restorative maintenance fault type corresponding to the current motor assembly processing equipment through a big data network, and calculating processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type according to the estimated maintenance time information of the restorative maintenance fault type and the estimated time information corresponding to information to be assembled of motor assembly;
if the fault type is a preventive maintenance fault type, acquiring estimated maintenance time information of the preventive maintenance fault type corresponding to the current motor assembly processing equipment through big data, and calculating processing time information of the motor assembly processing equipment corresponding to the current preventive maintenance fault type according to the estimated maintenance time information of the preventive maintenance fault type and the estimated time information corresponding to the information to be assembled of the motor assembly;
If the motor assembly processing equipment does not have any fault type, outputting estimated time information corresponding to the information to be assembled of the motor assembly as processing time information of the normal motor assembly processing equipment;
and generating and outputting the processing time information of the motor assembly processing equipment in each production area according to the processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type, the processing time information of the motor assembly processing equipment corresponding to the current preventative maintenance fault type and the processing time information of the normal motor assembly processing equipment.
Further, in a preferred embodiment of the present invention, task allocation is performed according to processing time information of the motor assembly processing device to obtain an allocation result, which specifically includes the following steps:
processing precision information of information to be assembled is obtained, fault priority allocation grades are formulated according to fault types, and the fault priority allocation grades are ordered, so that a priority allocation grade ordering result of production preset completion time information of a current motor assembly order is obtained;
performing task allocation on motor assembly processing equipment in a current production area according to a priority allocation level sequencing result of the production preset completion time information of the current motor assembly order so as to obtain a preselected allocation result and obtain motor assembly processing precision information in the preselected allocation result;
Judging whether the motor assembly machining precision information is within the machining precision information range of the information to be assembled, and if the motor assembly machining precision information is within the machining precision information range of the information to be assembled, outputting a current preselected distribution result as a final distribution result;
and if the motor assembly machining precision information is not in the machining precision information range of the information to be assembled, retrieving motor assembly machining equipment which accords with the machining precision information from a priority distribution grade sequencing result of production preset finishing time information of the current motor assembly order, performing secondary task distribution according to the priority distribution grade sequencing result of the motor assembly machining equipment, generating a secondary task distribution result, and outputting the secondary task distribution result as a distribution result.
Further, in a preferred embodiment of the present invention, the method further comprises the steps of:
calculating estimated processing time information of the current secondary task distribution result according to the secondary task distribution result, and acquiring preset finishing time information of motor assembly in the current production batch;
judging whether the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, and if the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, outputting the secondary task allocation result as an allocation result;
If the estimated processing time information of the current secondary task allocation result is larger than the preset finishing time information of the motor assembly in the current production batch, making a processing time priority allocation grade according to the processing time information of the motor assembly processing equipment, and sequencing the processing time information of the motor assembly processing equipment according to the processing time priority allocation grade;
and performing task allocation on the motor assembly processing equipment according to the sequencing result of the processing time information of the motor assembly processing equipment and the motor assembly processing precision information so as to generate a corresponding allocation result, and outputting the allocation result as a final allocation result.
The second aspect of the present invention provides a motor assembly production management system based on data analysis, the production management system includes a memory and a processor, the memory contains a motor assembly production management method program based on data analysis, and when the production management method program is executed by the processor, the following steps are implemented:
acquiring information to be assembled of motor assembly in a current production batch, and obtaining estimated time information corresponding to the information to be assembled of motor assembly by estimating the information to be assembled and counting the estimated result;
Acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment;
acquiring processing time information of motor assembly processing equipment in each production area based on estimated time information corresponding to the information to be assembled of the motor assembly and estimated fault time information of the motor assembly processing equipment;
and performing task distribution according to the processing time information of the motor assembly processing equipment to obtain a distribution result, generating a corresponding distribution report based on the distribution result, and outputting the distribution report.
In this embodiment, processing time information of the motor assembly processing equipment in each production area is obtained based on estimated time information corresponding to information to be assembled of the motor assembly and estimated fault time information of the motor assembly processing equipment, and specifically includes the following steps:
acquiring a fault type corresponding to current motor assembly processing equipment, if the fault type is a restorative maintenance fault type, acquiring estimated maintenance time information of the restorative maintenance fault type corresponding to the current motor assembly processing equipment through a big data network, and calculating processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type according to the estimated maintenance time information of the restorative maintenance fault type and the estimated time information corresponding to information to be assembled of motor assembly;
If the fault type is a preventive maintenance fault type, acquiring estimated maintenance time information of the preventive maintenance fault type corresponding to the current motor assembly processing equipment through big data, and calculating processing time information of the motor assembly processing equipment corresponding to the current preventive maintenance fault type according to the estimated maintenance time information of the preventive maintenance fault type and the estimated time information corresponding to the information to be assembled of the motor assembly;
if the motor assembly processing equipment does not have any fault type, outputting estimated time information corresponding to the information to be assembled of the motor assembly as processing time information of the normal motor assembly processing equipment;
and generating and outputting the processing time information of the motor assembly processing equipment in each production area according to the processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type, the processing time information of the motor assembly processing equipment corresponding to the current preventative maintenance fault type and the processing time information of the normal motor assembly processing equipment.
In this embodiment, task allocation is performed according to the processing time information of the motor assembly processing device, so as to obtain an allocation result, and specifically includes the following steps:
Processing precision information of information to be assembled is obtained, fault priority allocation grades are formulated according to fault types, and the fault priority allocation grades are ordered, so that a priority allocation grade ordering result of production preset completion time information of a current motor assembly order is obtained;
task allocation is carried out on motor assembly processing equipment in the current production area according to the priority allocation level sequencing result of the production preset completion time information of the current motor assembly order so as to obtain a preselected allocation result, and motor assembly processing precision information in the preselected allocation result is obtained
Judging whether the motor assembly machining precision information is within the machining precision information range of the information to be assembled, and if the motor assembly machining precision information is within the machining precision information range of the information to be assembled, outputting a current preselected distribution result as a final distribution result;
and if the motor assembly machining precision information is not in the machining precision information range of the information to be assembled, retrieving motor assembly machining equipment which accords with the machining precision information from a priority distribution grade sequencing result of production preset finishing time information of the current motor assembly order, performing secondary task distribution according to the priority distribution grade sequencing result of the motor assembly machining equipment, generating a secondary task distribution result, and outputting the secondary task distribution result as a distribution result.
In this embodiment, the present system also realizes the following functions:
calculating estimated processing time information of the current secondary task distribution result according to the secondary task distribution result, and acquiring preset finishing time information of motor assembly in the current production batch;
judging whether the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, and if the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, outputting the secondary task allocation result as an allocation result;
if the estimated processing time information of the current secondary task allocation result is larger than the preset finishing time information of the motor assembly in the current production batch, making a processing time priority allocation grade according to the processing time information of the motor assembly processing equipment, and sequencing the processing time information of the motor assembly processing equipment according to the processing time priority allocation grade;
and performing task allocation on the motor assembly processing equipment according to the sequencing result of the processing time information of the motor assembly processing equipment and the motor assembly processing precision information so as to generate a corresponding allocation result, and outputting the allocation result as a final allocation result.
The invention solves the defects existing in the background technology, and has the following beneficial effects:
according to the invention, the information to be assembled of the motor assembly in the current production batch is obtained, the estimated result is estimated, the estimated time information corresponding to the information to be assembled of the motor assembly is obtained, the operation information of the motor assembly processing equipment in each current production area is further obtained, the estimated fault time information of the motor assembly processing equipment is obtained according to the operation information of the motor assembly processing equipment, the processing time information of the motor assembly processing equipment in each production area is obtained based on the estimated time information corresponding to the information to be assembled of the motor assembly and the estimated fault time information of the motor assembly processing equipment, finally, task allocation is carried out according to the processing time information of the motor assembly processing equipment, so that an allocation result is obtained, a corresponding allocation report is generated based on the allocation result, and the allocation report is output. The method can distribute tasks to the current motor assembly processing equipment according to the fault information of the actual equipment, fully considers the running condition of the equipment, can distribute tasks to the motor assembly processing equipment according to the actual condition, can effectively rationally distribute production tasks in the motor assembly process, ensures that the distribution of the production tasks is more accurate, and ensures that the production of motor assembly is more reasonable.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other embodiments of the drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a specific method flow diagram of a motor assembly production management method based on data analysis;
FIG. 2 shows a first method flow diagram of a motor assembly production management method based on data analysis;
FIG. 3 shows a second method flow diagram of a motor assembly production management method based on data analysis;
fig. 4 shows a system block diagram of a motor assembly production management system based on data analysis.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
As shown in fig. 1, a first aspect of the present invention provides a motor assembly production management method based on data analysis, including the following steps:
s102, obtaining information to be assembled of motor assembly in a current production batch, estimating the information to be assembled, and counting the estimated result to obtain estimated time information corresponding to the information to be assembled of motor assembly;
s104, acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment;
s106, acquiring processing time information of motor assembly processing equipment in each production area based on estimated time information corresponding to information to be assembled of motor assembly and estimated fault time information of the motor assembly processing equipment;
and S108, performing task allocation according to the processing time information of the motor assembly processing equipment to obtain an allocation result, generating a corresponding allocation report based on the allocation result, and outputting the allocation report.
It is to be noted that, through the method, the current motor assembly processing equipment can be assigned tasks according to the fault information of the actual equipment, the running condition of the equipment is fully considered, the motor assembly processing equipment can be assigned tasks according to the actual condition, the production tasks in the motor assembly process can be effectively and reasonably assigned, the assignment of the production tasks is more accurate, and the production of motor assembly is more reasonable.
Further, in a preferred embodiment of the present invention, information to be assembled of motor assembly in a current production lot is obtained, and the estimated time information corresponding to the information to be assembled of motor assembly is obtained by estimating the information to be assembled and counting the estimated result, which specifically includes the following steps:
acquiring information to be assembled of motor assembly in a current production batch, and extracting characteristics of the information to be assembled of motor assembly in the current production batch to acquire the quantity information of motor assembly in the current production batch;
acquiring assembly efficiency information and quantity information of each specification of motor assembly processing equipment in each current production area;
the method comprises the steps of merging and counting assembly efficiency information and quantity information of motor assembly processing equipment of each specification in each current production area to obtain statistical information of each motor assembly processing equipment;
Calculating estimated time information corresponding to the information to be assembled of the motor assembly according to the number information of the motor assembly in the current production batch and the statistical information of each motor assembly processing device.
The information to be assembled at least comprises information of the number of motor assemblies and information of the production completion time of the motor assemblies. The method can be used for firstly predicting the estimated time information corresponding to the information to be assembled of the motor assembly. In the process of calculating estimated time information corresponding to information to be assembled of motor assembly according to the number information of motor assembly in the current production batch and the statistical information of each motor assembly processing device, if no fault exists in the current motor assembly device, the current motor assembly device can be input into a particle swarm algorithm or an ant colony algorithm to reasonably plan processing tasks and estimate, so that optimal estimated time information corresponding to the information to be assembled of the corresponding motor assembly is calculated. For example, the historical processing efficiency information of the current motor assembly processing equipment can be obtained, so that a processing time prediction model is built based on a neural network, the historical processing completion information of the current motor assembly processing equipment is input into the processing time prediction model for training, and finally, the quantity information of motor assembly in the current production batch and the statistical information of each motor assembly processing equipment are input into the processing time prediction model for prediction, so that the estimated time information corresponding to the information to be assembled of the corresponding motor assembly is obtained. In this embodiment, the technical means for realizing the prediction of the estimated time information corresponding to the information to be assembled for assembling the corresponding motor is not limited.
Further, in a preferred embodiment of the present invention, operation information of the motor assembly processing device in each current production area is obtained, and estimated failure time information of the motor assembly processing device is obtained according to the operation information of the motor assembly processing device, which specifically includes the following steps:
acquiring historical operation information of motor assembly processing equipment in each current production area, and extracting characteristics of the historical operation information to acquire fault information under each operation condition;
inputting fault information under each operation condition into the Bayesian network for training until the Bayesian network meets the preset requirement, so as to output the Bayesian network after training;
inputting the operation information of the motor assembly processing equipment in each current production area into a Bayesian network to obtain the fault probability of the motor assembly processing equipment within the preset time;
if the fault probability is larger than the preset fault probability, estimated fault time information of the motor assembly processing equipment with the fault probability larger than the preset fault probability is obtained.
In practice, however, the device is prone to failure during processing, and the bayesian network is a probabilistic graphical network, and the bayesian formula is the basis of the probabilistic graphical network. The bayesian network is a mathematical model based on probabilistic reasoning, which is a process of acquiring other probability information through information of some variables, is proposed for solving the problems of uncertainty and incompleteness, has great advantages for solving the problems caused by uncertainty and relevance of complex equipment, and is widely applied in a plurality of fields. The method comprises the steps of inputting fault information under each operation condition in historical operation information of motor assembly processing equipment in each current production area into a Bayesian network for training, wherein the fault information under each operation condition can be the fault information under the use frequency of each motor assembly processing equipment and the fault information under each processing working condition; the method can effectively predict the estimated fault time information of the motor assembly processing equipment, thereby laying a theoretical foundation for the task rationalization allocation of the production processing equipment.
As shown in fig. 2, in a preferred embodiment of the present invention, the processing time information of the motor assembly processing device in each production area is obtained based on the estimated time information corresponding to the information to be assembled of the motor assembly and the estimated failure time information of the motor assembly processing device, and specifically includes the following steps:
s202, acquiring a fault type corresponding to current motor assembly processing equipment, if the fault type is a restorative maintenance fault type, acquiring estimated maintenance time information of the restorative maintenance fault type corresponding to the current motor assembly processing equipment through a big data network, and calculating processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type according to the estimated maintenance time information of the restorative maintenance fault type and the estimated time information corresponding to information to be assembled of motor assembly;
s204, if the fault type is a preventive maintenance fault type, acquiring estimated maintenance time information of the preventive maintenance fault type corresponding to the current motor assembly processing equipment through big data, and calculating processing time information of the motor assembly processing equipment corresponding to the current preventive maintenance fault type according to the estimated maintenance time information of the preventive maintenance fault type and the estimated time information corresponding to the information to be assembled of the motor assembly;
S206, if the motor assembly processing equipment does not have any fault type, outputting estimated time information corresponding to the information to be assembled of the motor assembly as processing time information of the normal motor assembly processing equipment;
and S208, generating and outputting the processing time information of the motor assembly processing equipment in each production area according to the processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type, the processing time information of the motor assembly processing equipment corresponding to the current preventive maintenance fault type and the processing time information of the normal motor assembly processing equipment.
In this embodiment, since the operation of the apparatus can be classified into three types, one is a restorative maintenance failure type, another is a preventive maintenance failure type, and the last is an electric motor assembly processing apparatus that operates normally at a predetermined time. For the restorative maintenance fault type and the preventive maintenance fault type, in practical application, when the motor assembly processing equipment processes the equipment in the current batch, the two faults exist, and due to the maintenance time required in the processing process, the practical motor assembly processing time can be corrected by the method, so that the current motor assembly processing equipment can be reasonably allocated according to the more accurate motor assembly processing time.
As shown in fig. 3, in a preferred embodiment of the present invention, task allocation is performed according to processing time information of the motor assembly processing device to obtain allocation results, which specifically includes the following steps:
s302, acquiring processing precision information of information to be assembled, formulating fault priority allocation grades according to fault types, and sequencing the fault priority allocation grades to acquire a priority allocation grade sequencing result of production preset completion time information of a current motor assembly order;
s304, performing task allocation on motor assembly processing equipment in the current production area according to a priority allocation level sequencing result of production preset completion time information of the current motor assembly order so as to obtain a preselected allocation result and motor assembly processing precision information in the preselected allocation result;
s306, judging whether the motor assembly machining precision information is within the machining precision information range of the information to be assembled, and if the motor assembly machining precision information is within the machining precision information range of the information to be assembled, outputting the current preselected distribution result as a final distribution result;
and S308, if the motor assembly machining precision information is not in the machining precision information range of the information to be assembled, retrieving the motor assembly machining equipment which accords with the machining precision information from the priority distribution grade sequencing result of the production preset finishing time information of the current motor assembly order, performing secondary task distribution according to the priority distribution grade sequencing result of the motor assembly machining equipment, generating a secondary task distribution result, and outputting the secondary task distribution result as a distribution result.
It should be noted that, in the actual application scenario, the precision of motor assembly completed by motor assembly equipment with different models and specifications and the production efficiency of the motor assembly equipment are inconsistent, firstly, a pre-selected distribution result is determined according to the fault priority distribution level, so that distribution is performed on the priority distribution level sequencing result according to the processing precision of actual requirements and the production preset completion time information of the current motor assembly order, the time of other maintenance links can be reduced, the production efficiency within the preset time is improved, and the distribution rationality of the motor assembly equipment can be further improved by the method.
Further, in a preferred embodiment of the present invention, the method further comprises the steps of:
calculating estimated processing time information of a current secondary task distribution result according to the secondary task distribution result, and acquiring preset finishing time information of motor assembly in a current production batch;
judging whether the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, and if the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, outputting the secondary task allocation result as an allocation result;
If the estimated processing time information of the current secondary task allocation result is larger than the preset finishing time information of the motor assembly in the current production batch, making a processing time priority allocation grade according to the processing time information of the motor assembly processing equipment, and sequencing the processing time information of the motor assembly processing equipment according to the processing time priority allocation grade;
and performing task allocation on the motor assembly processing equipment according to the sequencing result of the processing time information of the motor assembly processing equipment and the motor assembly processing precision information so as to generate a corresponding allocation result, and outputting the allocation result as a final allocation result.
It should be noted that in an actual application scenario, the maintenance time required by the processing devices of different types with the same fault type may be inconsistent, and when the estimated processing time information of the secondary task allocation result is greater than the preset completion time information of the motor assembly in the current production batch, it is not preferable to indicate that the scheme is not enough, and the corresponding task cannot be completed within the preset time.
In addition, the method can further comprise the following steps:
acquiring historical processing defective rate information of current motor assembly equipment and product batch information of current motor assembly products, and constructing a processing defective rate information prediction model based on a machine learning technology;
inputting the historical processing defective rate information of the current motor assembly equipment into the processing defective rate information prediction model for training to obtain a trained construction processing defective rate information prediction model;
inputting the product batch information of the current motor assembly product into the processing defective rate information prediction model to obtain defective rate information of the current motor assembly product, and obtaining defective product to be assembled information of motor assembly according to the defective rate information;
and distributing the current battery assembly equipment according to the defective product to-be-assembled information to obtain a defective product distribution result, and correcting the distribution result according to the defective product distribution result.
In the actual production process, any equipment can generate a certain defective rate, and the final distribution result can be further corrected according to the defective distribution result by the method, so that the rationality of the distribution result is improved.
In addition, the method can further comprise the following steps:
acquiring battery assembly equipment with the defective rate lower than a preset threshold value;
calculating estimated time information required for estimating the number of products of the motor device to be detected according to the production efficiency of the battery assembly equipment with the defective rate lower than a preset threshold;
acquiring battery assembly equipment with the minimum defective rate in the current production area;
and when the estimated time information required by the product quantity of the motor device to be estimated is within the preset completion time information of the motor assembly in the current production batch, improving the priority of the battery assembly equipment with the defective rate lower than a preset threshold in the priority distribution level sequencing result.
When the estimated time information required by the product quantity of the motor device to be estimated is within the preset completion time information of the motor assembly in the current production batch, the method can improve the priority of the battery assembly equipment with the defective rate lower than the preset threshold in the priority distribution level sequencing result, so that the production rate of the genuine products in the battery assembly production process is improved, the production cost in the production process is reduced, and the strategy of battery assembly production is further optimized.
As shown in fig. 4, a second aspect of the present invention provides a motor assembly production management system based on data analysis, the production management system includes a memory 41 and a processor 62, the memory 41 contains a motor assembly production management method program based on data analysis, and when the production management method program is executed by the processor, the following steps are implemented:
obtaining information to be assembled of motor assembly in the current production batch, estimating the information to be assembled, and counting the estimated result to obtain estimated time information corresponding to the information to be assembled of motor assembly;
acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment;
acquiring processing time information of motor assembly processing equipment in each production area based on estimated time information corresponding to information to be assembled of motor assembly and estimated fault time information of motor assembly processing equipment;
and performing task allocation according to the processing time information of the motor assembly processing equipment to obtain an allocation result, generating a corresponding allocation report based on the allocation result, and outputting the allocation report.
In this embodiment, processing time information of the motor assembly processing equipment in each production area is obtained based on estimated time information corresponding to information to be assembled of motor assembly and estimated fault time information of the motor assembly processing equipment, and specifically includes the following steps:
acquiring a fault type corresponding to current motor assembly processing equipment, if the fault type is a restorative maintenance fault type, acquiring estimated maintenance time information of the restorative maintenance fault type corresponding to the current motor assembly processing equipment through a big data network, and calculating processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type according to the estimated maintenance time information of the restorative maintenance fault type and the estimated time information corresponding to information to be assembled of motor assembly;
if the fault type is a preventive maintenance fault type, acquiring estimated maintenance time information of the preventive maintenance fault type corresponding to the current motor assembly processing equipment through big data, and calculating processing time information of the motor assembly processing equipment corresponding to the current preventive maintenance fault type according to the estimated maintenance time information of the preventive maintenance fault type and the estimated time information corresponding to the information to be assembled of the motor assembly;
If the motor assembly processing equipment does not have any fault type, outputting estimated time information corresponding to the information to be assembled of the motor assembly as processing time information of the normal motor assembly processing equipment;
and generating and outputting the processing time information of the motor assembly processing equipment in each production area according to the processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type, the processing time information of the motor assembly processing equipment corresponding to the current preventative maintenance fault type and the processing time information of the normal motor assembly processing equipment.
In this embodiment, task allocation is performed according to processing time information of the motor assembly processing device to obtain an allocation result, and specifically includes the following steps:
processing precision information of the information to be assembled is obtained, fault priority allocation grades are formulated according to fault types, and the fault priority allocation grades are ordered, so that a priority allocation grade ordering result of production preset completion time information of a current motor assembly order is obtained;
task allocation is carried out on motor assembly processing equipment in the current production area according to a priority allocation level sequencing result of production preset completion time information of the current motor assembly order so as to obtain a preselected allocation result and motor assembly processing precision information in the preselected allocation result;
Judging whether the motor assembly machining precision information is within the machining precision information range of the information to be assembled, and if the motor assembly machining precision information is within the machining precision information range of the information to be assembled, outputting the current preselected distribution result as a final distribution result;
if the motor assembly machining precision information is not in the machining precision information range of the information to be assembled, the motor assembly machining equipment which accords with the machining precision information is searched in the priority distribution grade sequencing result of the production preset finishing time information of the current motor assembly order, secondary task distribution is carried out according to the priority distribution grade sequencing result of the motor assembly machining equipment, a secondary task distribution result is generated, and the secondary task distribution result is output as a distribution result.
In this embodiment, the present system also realizes the following functions:
calculating estimated processing time information of a current secondary task distribution result according to the secondary task distribution result, and acquiring preset finishing time information of motor assembly in a current production batch;
judging whether the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, and if the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, outputting the secondary task allocation result as an allocation result;
If the estimated processing time information of the current secondary task allocation result is larger than the preset finishing time information of the motor assembly in the current production batch, making a processing time priority allocation grade according to the processing time information of the motor assembly processing equipment, and sequencing the processing time information of the motor assembly processing equipment according to the processing time priority allocation grade;
and performing task allocation on the motor assembly processing equipment according to the sequencing result of the processing time information of the motor assembly processing equipment and the motor assembly processing precision information so as to generate a corresponding allocation result, and outputting the allocation result as a final allocation result.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
The foregoing is merely illustrative embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the technical scope of the present invention, and the invention should be covered. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (6)
1. The motor assembly production management method based on data analysis is characterized by comprising the following steps of:
acquiring information to be assembled of motor assembly in a current production batch, and obtaining estimated time information corresponding to the information to be assembled of motor assembly by estimating the information to be assembled and counting the estimated result;
acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment;
acquiring processing time information of motor assembly processing equipment in each production area based on estimated time information corresponding to the information to be assembled of the motor assembly and estimated fault time information of the motor assembly processing equipment;
task distribution is carried out according to the processing time information of the motor assembly processing equipment so as to obtain a distribution result, a corresponding distribution report is generated based on the distribution result, and the distribution report is output;
obtaining information to be assembled of motor assembly in a current production batch, and obtaining estimated time information corresponding to the information to be assembled of motor assembly by estimating the information to be assembled and counting estimated results, wherein the method specifically comprises the following steps:
Acquiring information to be assembled of motor assembly in a current production batch, and extracting characteristics of the information to be assembled of motor assembly in the current production batch to acquire the quantity information of motor assembly in the current production batch;
acquiring assembly efficiency information and quantity information of each specification of motor assembly processing equipment in each current production area;
the assembly efficiency information and the quantity information of each specification of motor assembly processing equipment in the current production areas are converged and counted to obtain the statistical information of each motor assembly processing equipment;
calculating estimated time information corresponding to the information to be assembled of the motor assembly according to the information of the number of motor assemblies in the current production batch and the statistical information of each motor assembly processing device
Acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment, wherein the method specifically comprises the following steps:
acquiring historical operation information of motor assembly processing equipment in each current production area, and extracting characteristics of the historical operation information to acquire fault information under each operation condition;
Inputting the fault information under each operation condition into a Bayesian network for training until the Bayesian network meets the preset requirement, so as to output the Bayesian network after the training is completed;
inputting the operation information of the motor assembly processing equipment in each current production area into the Bayesian network to obtain the fault probability of the motor assembly processing equipment within the preset time;
if the fault probability is larger than a preset fault probability, acquiring estimated fault time information of motor assembly processing equipment with the fault probability larger than the preset fault probability;
task allocation is carried out according to the processing time information of the motor assembly processing equipment so as to obtain an allocation result, and the method specifically comprises the following steps of:
processing precision information of information to be assembled is obtained, fault priority allocation grades are formulated according to fault types, and the fault priority allocation grades are ordered, so that a priority allocation grade ordering result of production preset completion time information of a current motor assembly order is obtained;
performing task allocation on motor assembly processing equipment in a current production area according to a priority allocation level sequencing result of the production preset completion time information of the current motor assembly order so as to obtain a preselected allocation result and obtain motor assembly processing precision information in the preselected allocation result;
Judging whether the motor assembly machining precision information is within the machining precision information range of the information to be assembled, and if the motor assembly machining precision information is within the machining precision information range of the information to be assembled, outputting a current preselected distribution result as a final distribution result;
and if the motor assembly machining precision information is not in the machining precision information range of the information to be assembled, retrieving motor assembly machining equipment which accords with the machining precision information from a priority distribution grade sequencing result of production preset finishing time information of the current motor assembly order, performing secondary task distribution according to the priority distribution grade sequencing result of the motor assembly machining equipment, generating a secondary task distribution result, and outputting the secondary task distribution result as a distribution result.
2. The method for managing motor assembly and production based on data analysis according to claim 1, wherein the processing time information of the motor assembly and processing equipment in each production area is obtained based on the estimated time information corresponding to the information to be assembled of the motor assembly and the estimated fault time information of the motor assembly and processing equipment, specifically comprising the following steps:
Acquiring a fault type corresponding to current motor assembly processing equipment, if the fault type is a restorative maintenance fault type, acquiring estimated maintenance time information of the restorative maintenance fault type corresponding to the current motor assembly processing equipment through a big data network, and calculating processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type according to the estimated maintenance time information of the restorative maintenance fault type and the estimated time information corresponding to information to be assembled of motor assembly;
if the fault type is a preventive maintenance fault type, acquiring estimated maintenance time information of the preventive maintenance fault type corresponding to the current motor assembly processing equipment through big data, and calculating processing time information of the motor assembly processing equipment corresponding to the current preventive maintenance fault type according to the estimated maintenance time information of the preventive maintenance fault type and the estimated time information corresponding to the information to be assembled of the motor assembly;
if the motor assembly processing equipment does not have any fault type, outputting estimated time information corresponding to the information to be assembled of the motor assembly as processing time information of the normal motor assembly processing equipment;
And generating and outputting the processing time information of the motor assembly processing equipment in each production area according to the processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type, the processing time information of the motor assembly processing equipment corresponding to the current preventative maintenance fault type and the processing time information of the normal motor assembly processing equipment.
3. The motor assembly production management method based on data analysis of claim 1, further comprising the steps of:
calculating estimated processing time information of the current secondary task distribution result according to the secondary task distribution result, and acquiring preset finishing time information of motor assembly in the current production batch;
judging whether the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, and if the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, outputting the secondary task allocation result as an allocation result;
if the estimated processing time information of the current secondary task allocation result is larger than the preset finishing time information of the motor assembly in the current production batch, making a processing time priority allocation grade according to the processing time information of the motor assembly processing equipment, and sequencing the processing time information of the motor assembly processing equipment according to the processing time priority allocation grade;
And performing task allocation on the motor assembly processing equipment according to the sequencing result of the processing time information of the motor assembly processing equipment and the motor assembly processing precision information so as to generate a corresponding allocation result, and outputting the allocation result as a final allocation result.
4. The motor assembly production management system based on data analysis is characterized by comprising a memory and a processor, wherein the memory contains a motor assembly production management method program based on data analysis, and the production management method program realizes the following steps when being executed by the processor:
acquiring information to be assembled of motor assembly in a current production batch, and obtaining estimated time information corresponding to the information to be assembled of motor assembly by estimating the information to be assembled and counting the estimated result;
acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment;
acquiring processing time information of motor assembly processing equipment in each production area based on estimated time information corresponding to the information to be assembled of the motor assembly and estimated fault time information of the motor assembly processing equipment;
Task distribution is carried out according to the processing time information of the motor assembly processing equipment so as to obtain a distribution result, a corresponding distribution report is generated based on the distribution result, and the distribution report is output;
obtaining information to be assembled of motor assembly in a current production batch, and obtaining estimated time information corresponding to the information to be assembled of motor assembly by estimating the information to be assembled and counting estimated results, wherein the method specifically comprises the following steps:
acquiring information to be assembled of motor assembly in a current production batch, and extracting characteristics of the information to be assembled of motor assembly in the current production batch to acquire the quantity information of motor assembly in the current production batch;
acquiring assembly efficiency information and quantity information of each specification of motor assembly processing equipment in each current production area;
the assembly efficiency information and the quantity information of each specification of motor assembly processing equipment in the current production areas are converged and counted to obtain the statistical information of each motor assembly processing equipment;
calculating estimated time information corresponding to the information to be assembled of the motor assembly according to the information of the number of motor assemblies in the current production batch and the statistical information of each motor assembly processing device
Acquiring operation information of motor assembly processing equipment in each current production area, and acquiring estimated fault time information of the motor assembly processing equipment according to the operation information of the motor assembly processing equipment, wherein the method specifically comprises the following steps:
acquiring historical operation information of motor assembly processing equipment in each current production area, and extracting characteristics of the historical operation information to acquire fault information under each operation condition;
inputting the fault information under each operation condition into a Bayesian network for training until the Bayesian network meets the preset requirement, so as to output the Bayesian network after the training is completed;
inputting the operation information of the motor assembly processing equipment in each current production area into the Bayesian network to obtain the fault probability of the motor assembly processing equipment within the preset time;
if the fault probability is larger than a preset fault probability, acquiring estimated fault time information of motor assembly processing equipment with the fault probability larger than the preset fault probability;
task allocation is carried out according to the processing time information of the motor assembly processing equipment so as to obtain an allocation result, and the method specifically comprises the following steps of:
Processing precision information of information to be assembled is obtained, fault priority allocation grades are formulated according to fault types, and the fault priority allocation grades are ordered, so that a priority allocation grade ordering result of production preset completion time information of a current motor assembly order is obtained;
performing task allocation on motor assembly processing equipment in a current production area according to a priority allocation level sequencing result of the production preset completion time information of the current motor assembly order so as to obtain a preselected allocation result and obtain motor assembly processing precision information in the preselected allocation result;
judging whether the motor assembly machining precision information is within the machining precision information range of the information to be assembled, and if the motor assembly machining precision information is within the machining precision information range of the information to be assembled, outputting a current preselected distribution result as a final distribution result;
and if the motor assembly machining precision information is not in the machining precision information range of the information to be assembled, retrieving motor assembly machining equipment which accords with the machining precision information from a priority distribution grade sequencing result of production preset finishing time information of the current motor assembly order, performing secondary task distribution according to the priority distribution grade sequencing result of the motor assembly machining equipment, generating a secondary task distribution result, and outputting the secondary task distribution result as a distribution result.
5. The motor assembly production management system based on data analysis according to claim 4, wherein the processing time information of the motor assembly processing equipment in each production area is obtained based on the estimated time information corresponding to the information to be assembled of the motor assembly and the estimated fault time information of the motor assembly processing equipment, and specifically comprises the following steps:
acquiring a fault type corresponding to current motor assembly processing equipment, if the fault type is a restorative maintenance fault type, acquiring estimated maintenance time information of the restorative maintenance fault type corresponding to the current motor assembly processing equipment through a big data network, and calculating processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type according to the estimated maintenance time information of the restorative maintenance fault type and the estimated time information corresponding to information to be assembled of motor assembly;
if the fault type is a preventive maintenance fault type, acquiring estimated maintenance time information of the preventive maintenance fault type corresponding to the current motor assembly processing equipment through big data, and calculating processing time information of the motor assembly processing equipment corresponding to the current preventive maintenance fault type according to the estimated maintenance time information of the preventive maintenance fault type and the estimated time information corresponding to the information to be assembled of the motor assembly;
If the motor assembly processing equipment does not have any fault type, outputting estimated time information corresponding to the information to be assembled of the motor assembly as processing time information of the normal motor assembly processing equipment;
and generating and outputting the processing time information of the motor assembly processing equipment in each production area according to the processing time information of the motor assembly processing equipment corresponding to the current restorative maintenance fault type, the processing time information of the motor assembly processing equipment corresponding to the current preventative maintenance fault type and the processing time information of the normal motor assembly processing equipment.
6. The motor assembly production management system based on data analysis of claim 4, further comprising the steps of:
calculating estimated processing time information of the current secondary task distribution result according to the secondary task distribution result, and acquiring preset finishing time information of motor assembly in the current production batch;
judging whether the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, and if the estimated processing time information of the current secondary task allocation result is not more than the preset completion time information of the motor assembly in the current production batch, outputting the secondary task allocation result as an allocation result;
If the estimated processing time information of the current secondary task allocation result is larger than the preset finishing time information of the motor assembly in the current production batch, making a processing time priority allocation grade according to the processing time information of the motor assembly processing equipment, and sequencing the processing time information of the motor assembly processing equipment according to the processing time priority allocation grade;
and performing task allocation on the motor assembly processing equipment according to the sequencing result of the processing time information of the motor assembly processing equipment and the motor assembly processing precision information so as to generate a corresponding allocation result, and outputting the allocation result as a final allocation result.
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