Research On Improvement Of Intelligent Quality Control In Manufacturing Process Of A Company

In recent ten years,the manufacturing industry in China has developed rapidly,and it is moving towards a manufacturing power.The quality control of manufacturing process is an important content to ensure the transformation.At present,with the intelligent improvement in the production process,the digitalization degree of production equipment is strengthened,the data transmission process optimization of network information is optimized,the quality control ability of manufacturing process is constantly improved,the intelligent level of quality control is improved,and the quality is fully monitored and monitored in real time,intelligent control and quality early warning can be realized.Therefore,how to use digital equipment,simulation model,etc Intelligent tools such as intelligent algorithm,self-adaptive,self-optimization and self-learning closed-loop quality intelligent control system are the necessary objectives for the development of quality control in the future.This paper analyzes the three problems of manufacturing process quality intelligent control,such as the low automation of data collection,the failure to construct the early warning and visual diagnosis of manufacturing process quality data and the failure to establish an effective iterative process of quality intelligent control,According to the analysis results,the quality control process and intelligent control framework of manufacturing process quality are constructed;In view of the problem that the quality data of company a is not effectively used,the collection process of 5M1E status data,the quality data collection process and the quality data processing process are constructed;Aiming at the problem that company a has not established the timely intelligent quality control process,the product quality data early warning model based on the extreme learning machine model is constructed according to the improvement scheme.Through the application of the process quality control visualization scheme,the frame and function of the visualization scheme are discussed.According to the requirements of intelligent iteration of process quality,the system adopts self-adaptive The three processes of self-learning and self optimization are used to construct the intelligent iterative process of manufacturing process quality of company A.Compared with the existing research,this paper has a significant innovation in the intelligent control of manufacturing process quality,especially in the improvement of intelligent iteration of manufacturing process quality.In the past,the research on quality control seldom discusses the iterative process of quality intelligence,and analyzes the process of self-adaptive,self-learning and self optimization in the process of quality intelligent control.This paper proposes the overall process scheme and overall framework based on the quality intelligent control,constructs the intelligent quality early warning model and the process quality control visualization framework based on the extreme learning machine.Through the self-adaptive,self-optimization and self-learning process of intelligent iterative process quality,the quality closed-loop control system without artificial intervention is constructed,It solves the problems of less research in the past,and has some practical application.