Advances in Manufacturing ›› 2013, Vol. 1 ›› Issue (1): 62-74.doi: 10.1007/s40436-013-0010-9

• • 上一篇    下一篇

Towards zero-defect manufacturing (ZDM)—a data mining approach

Ke-Sheng Wang   

  1. Knowledge Discovery Laboratory, Department of Production and Quality Engineering, Norwegian University of Science and Technology, Trondheim, Norway
  • 收稿日期:2012-08-10 出版日期:2012-03-01 发布日期:2012-03-01

Towards zero-defect manufacturing (ZDM)—a data mining approach

Ke-Sheng Wang   

  1. Knowledge Discovery Laboratory, Department of Production and Quality Engineering, Norwegian University of Science and Technology, Trondheim, Norway
  • Received:2012-08-10 Online:2012-03-01 Published:2012-03-01

摘要: The quality of a product is dependent on both facilities/equipment and manufacturing processes. Any error or disorder in facilities and processes can cause a catastrophic failure. To avoid such failures, a zero- defect manufacturing (ZDM) system is necessary in order to increase the reliability and safety of manufacturing systems and reach zero-defect quality of products. One of the major challenges for ZDM is the analysis of massive raw datasets. This type of analysis needs an automated and self-organized decision making system. Data mining (DM) is an effective methodology for discovering interesting knowledge within a huge datasets. It plays an important role in developing a ZDM system. The paper presents a general framework of ZDM and explains how to apply DM approaches to manufacture the products with zero-defect. This paper also discusses 3 ongoing projects demonstrating the practice of using DM approaches for reaching the goal of ZDM.

关键词: Data mining (DM) , Quality of product , Zero- defect manufacturing (ZDM) , Knowledge discovery

Abstract: The quality of a product is dependent on both facilities/equipment and manufacturing processes. Any error or disorder in facilities and processes can cause a catastrophic failure. To avoid such failures, a zero- defect manufacturing (ZDM) system is necessary in order to increase the reliability and safety of manufacturing systems and reach zero-defect quality of products. One of the major challenges for ZDM is the analysis of massive raw datasets. This type of analysis needs an automated and self-organized decision making system. Data mining (DM) is an effective methodology for discovering interesting knowledge within a huge datasets. It plays an important role in developing a ZDM system. The paper presents a general framework of ZDM and explains how to apply DM approaches to manufacture the products with zero-defect. This paper also discusses 3 ongoing projects demonstrating the practice of using DM approaches for reaching the goal of ZDM.

Key words: Data mining (DM) , Quality of product , Zero- defect manufacturing (ZDM) , Knowledge discovery