Research On Data-driven Product Quality Control Technology

The rapid development of China's economy has accelerated the progress of the manufacturing industry.As one of the leading industries supporting China's economy,the automobile industry has been ranking the first in the world in terms of its automobile production and sales volume for ten years.At the same time,the rapid development of the domestic automotive industry has brought about a sharp increase in the number of customers.According to the statistics of relevant institutions,the complaint rate of automotive quality problems in China has increased continuously in recent years,and the quality problems of automotive products have been further amplified.In recent years,the development of information industry has accelerated the transformation from "production-oriented" manufacturing to "serviceoriented" manufacturing in China's manufacturing industry.Many automobile manufacturers have gradually begun to attach importance to their own after-sales service market.Aiming at the quality problem of automobile products,this paper aims at the after-sales service process of automobile manufacturers.Based on the after-sales business data in the data space of the collaborative cloud platform of the automobile industry value chain,the product quality control technology is studied.The purpose is to transform the after-sales business data into valuable resources based on data-driven,strengthen the quality control of automobile manufacturing enterprises,and provide quality management-related decision support for vehicle manufacturers to improve vehicle quality.This paper first discusses the background and significance of the research,introduces the research status of product quality control,product quality evaluation methods at home and abroad,as well as the content and organization structure of the paper.Then,through the analysis of the current situation of product quality control,the existing problems in the research of product quality control technology are put forward.On this basis,the design of product quality control business model,demand analysis and business process design are carried out.Subsequently,the design of product quality management and control information system was completed.Based on the management of the cockpit,the system realizes the fine analysis of fault factors.The main analysis objects include models,fault parts,service stations and suppliers.Fault factors involved include location,age and mileage.Taking quality evaluation as the center,relevant evaluation indexes are extracted from the maintenance data,and the product quality evaluation index system and evaluation model are constructed.Combining the fuzzy comprehensive evaluation method with the entropy method,the whole vehicle quality of the manufacturing plant is evaluated.By realizing the functions of fine analysis of product failure factors and comprehensive evaluation of product quality,the causes and rules of product quality differences are excavated to achieve the purpose of quality control.Finally,using B/S mode and traditional three-tier architecture,using C# as the development language.The development and application verification of the system are completed on the basis of ASP.NET,and the visual display of foreground data analysis is realized through Echarts chart.