Integration of knowledge discovery techniques in the quality management model to achieve higher target quality

Authors:
Ch. Fazel Ansari;Christian Sassenberg;Madjid Fathi;Ralf Montino
Affiliations:
University of Siegen, Germany;University of Siegen, Germany;University of Siegen, Germany;ELMOS Central IT, Services GmbH & Co KG, Dortmund, Germany
Venue:
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Year:
2009

Citing 6
Cited 0

Floating search methods in feature selection

Pattern Recognition Letters
The KDD process for extracting useful knowledge from volumes of data

Communications of the ACM
Feature Selection for Knowledge Discovery and Data Mining

Feature Selection for Knowledge Discovery and Data Mining
Data mining for process and quality control in the semiconductor industry

Data mining for design and manufacturing
Introduction to Knowledge Management: KM in Business

Introduction to Knowledge Management: KM in Business
The Realization of Knowledge Discovery in Total Quality Management System

FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04

Quantified Score

Hi-index	0.00

Visualization

Abstract

Improving the quality of products is an important issue in the modern business world. Traditional approaches of Quality Management (QM) are not adequate to fulfil the demands on target quality of products. This study reveals that synergetic approaches based on the integration of Knowledge Management (KM) in Total Quality Management (TQM) have a direct impact on enhancing the quality of products. We also propose a management model to synthesize elements of both methodologies under an integrative framework. Furthermore, Knowledge Discovery in Databases (KDD) is introduced to realize the effectiveness of the proposed management model and to illustrate the influence of this synergetic approach taking the semiconductor industry as exemplary field of application.