Extension data mining method for improving product manufacturing quality

It is more and more important to improve the market competitiveness of enterprises by providing high-quality products meeting the market demand. However, the product manufacturing process of most manufacturers is not perfect, and a variety of product quality management methods are mixed with each other, which leads to the urgent need to reduce the nonconforming product rate produced by many production lines and the inability to accurately capture the reasons why the good rate is not up to standard. Customer satisfaction gradually decreases with the development of personalized times. The rapid accumulation of big data in the Internet environment has brought new opportunities for the study of the details of the production process.Extenics uses formal models to describe the production situation and operation mode of each process in the manufacturing process.This paper uses the extension data mining method to determine the factors that affect the product's qualified rate by collecting the data on each process of the production line, and by extension transformation, the qualified rate of the product is obviously improved.The simulation results show that this kind of extension data mining method provides a new idea for enterprises to improve the product manufacturing quality and product qualification rate, which is helpful for enterprises to realize a more perfect quality management system. (C) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ne-nd/4.0/) Peer-review under responsibility of the scientific committee of the 7th International Conference on Information Technology and Quantitative Management (ITQM 2019)