Study On Production Process Quality Control And Evaluation In Vehicle Manufacturing Enterprise

Quality is the most powerful strategetic weapon of enterprise occupying market, which is very important to existence and development of enterprise. The production mode and management method of vehicle manufacturing enterprise is undergoing tremendous changes at the background of the rapid development of computer technology, network technology and artificial intelligence technology. Facing to the new changes of product quality management, conventional quality control method has not adapted to them. So, studying advanced method of quality management and quality control technology is especial and important significance to development vehicle manufacturing in china. In the background of vehicle manufacturing enterprise production process quality management, the problems of production process quality control and intelligent diagnosis technology are studied. The main tasks are as follows:(1) Combined with auto production pattern characteristics, process quality control model for vehicle manufacturing enterprise is put forward, system framework is constructed, function and architecture are determined on the basis.(2) The deficiencies of the existing process quality control methods in the production management of vehicle manufacturing enterprise are discussed. A process quality intelligent forecasting method combining Extreme Learning Machine (ELM) and Particle Swarm Optimization (PSO) is presented. Finally, a case study is given.(3) A production process quality data mining model based on knowledge extraction is presented. The quality data warehouse of production process is set up and a relevant decision-making knowledge extraction algorithm combining genetic algorithm (GA) and association rule (AR) mining is proposed.(4) To realize continual quality improvement, the process quality performance assessment model and indicators of vehicle manufacturing enterprise are set up and the evaluation and diagnosis models of quality performance efficiency are proposed by the use of Data Envelopment Analysis (DEA). The models and methods given by this paper are further illustrated by means of case study.(5) Finally, based on the instance validation study, especially for the process quality management in vehicle manufacturing enterprise, the requirement and objective for prototype system are analyzed, and then the overall framework and development environment are given. Furthermore, the prototype system is developed and used in a vehicle manufacturing company.