Intelligent production line product quality control method and system based on machine learning
A technology of machine learning and product quality, applied in general control systems, control/adjustment systems, instruments, etc., can solve problems such as failure to achieve efficient product quality control in intelligent workshops, lack of relationship between product quality and manufacturing big data in intelligent manufacturing units, etc. , to achieve the effect of improving the error traceability efficiency, improving product quality and production efficiency, and high quality level
Inactive Publication Date: 2021-08-27
CHANGAN UNIV
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[0005] The purpose of the present invention is to provide a machine learning-based intelligent production line product processing quality control method and system, which solves the existing lack of exploring the relationship between the product quality of intelligent manufacturing units and manufacturing big data, and applies machine learning to product processing In the case of quality control, the overall implementation effect did not meet the requirements of efficient product quality control for smart workshops
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[0063] The present invention will be described in further detail below in conjunction with the accompanying drawings. The accompanying drawings described here are a part of the present application, and are used to further explain the present invention, but do not constitute a limitation to the present invention.
[0064] The invention provides a machine learning-based intelligent production line product processing quality control method, such as figure 1 shown, including the following steps:
[0065] S1. According to the process flow of the product, determine the key dimensions of the product that need to be traced and the key factors that affect the dimensional error. The key factors include equipment status data, tool status data, fixture status data, and environmental status data;
[0066] According to the determined key dimensions and several key factors affecting dimensional errors, the mapping relationship between product processing errors and complex working conditions...
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The invention provides an intelligent production line product processing quality control method and system based on machine learning. The method comprises the steps of: building a mapping relation between product processing error and complex working condition factors, building an error tracing model, outputting primary and secondary factors which affect errors, and giving an error compensation suggestion. A complex non-linear relation exists between the out-of-tolerance size and an error source, the error source is complex, and an error traceability model is difficult to establish and the practical application effect is poor when a traditional mathematical method is adopted. The BP neural network has a non-linear mapping function, and can approach any complex non-linear mapping at any precision if designed reasonably. Model establishment steps based on the method are simple, and the error tracing precision is greatly improved.
Description
technical field [0001] The invention relates to the field of intelligent manufacturing, in particular to a method and system for controlling the processing quality of intelligent production line products based on machine learning. Background technique [0002] At present, a new round of scientific and technological revolution and industrial transformation is accelerating development. The new generation of information technology is being deeply integrated with the manufacturing industry. Digitalization, networking, and intelligence have become important directions for the development of the global manufacturing industry. In the mass production process of products, the machining accuracy of products will be affected by various working conditions such as machining load, tool wear, equipment health status and machining process parameters. Therefore, in the intelligent manufacturing environment, the manufacturing workshop of the enterprise should have an intelligent control link ...
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IPC IPC(8): G05B19/418
CPCG05B19/41885G05B2219/32339Y02P90/02
Inventor 刘永生张心卉蔡世阳惠记庄朱斌张富强丁凯陈一馨徐志博户盼茹
Owner CHANGAN UNIV