Abstract
As a typical manufacturing industry, the automobile industry has high requirements for quality management. Today, with the rapid development of information technology, it is important to consider the characteristics of quality management in the industry and the whole life cycle of automobile products. Based on this perspective, an evaluation index system of quality management data and a big data platform of quality management for the automobile industry were established. This research has guiding significance for governments to serve the development of the automobile industry and for enterprises to improve their quality capability.
Highlights
Introduction1.1 Automobile Industry After the reform and opening-up, China's automobile industry has developed rapidly and has become the world's largest automobile producer and new car consumer market
Influenced by information technology, big data has been used in the entire life cycle like industrial R&D and design, production and supply chain management as well as operation and maintenance and service
This paper aims to release the valuable information contained in automobile big data through data acquisition, transmission, storage, mining, and visualization so as to analyze the status quo of the quality of the industry and master the latest industrial trends; the paper provides methods for enterprises to make annual summaries of quality management to meet the goal of making a comprehensive analysis and benchmarking, optimizing the quality management capability of the enterprises and creating a benchmark of quality management
Summary
1.1 Automobile Industry After the reform and opening-up, China's automobile industry has developed rapidly and has become the world's largest automobile producer and new car consumer market. The severe recalling situation of the industry reflects the supervision intensity of governments and consumers’ higher pursuit for quality automobile products. Influenced by information technology, big data has been used in the entire life cycle like industrial R&D and design, production and supply chain management as well as operation and maintenance and service. Influenced by modern science and technology, the complexity and dynamics of the production process have appeared and the big data generated in the entire life cycle can no longer be managed and maintained by traditional information technology. A massive amount of data has been accumulated, but most of them are applied at the technology level and haven’t combined well with quality management. Application of big data in the whole life cycle from a higher level has not been explored
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