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Advances in Manufacturing
Erschienen in: Advances in Manufacturing 1/2013

01.03.2013

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

verfasst von: Ke-Sheng Wang

Erschienen in: Advances in Manufacturing | Ausgabe 1/2013

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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.
Vorheriger Artikel Thermal plasma synthesis of SiC
Nächster Artikel Advances of physics-based precision modeling and simulation for manufacturing processes

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Metadaten
Titel
Towards zero-defect manufacturing (ZDM)—a data mining approach
verfasst von
Ke-Sheng Wang
Publikationsdatum
01.03.2013
Verlag
Shanghai University
Erschienen in
Advances in Manufacturing / Ausgabe 1/2013
Print ISSN: 2095-3127
Elektronische ISSN: 2195-3597
DOI
https://doi.org/10.1007/s40436-013-0010-9

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