DocumentCode
2027304
Title
Fuzzy-Neural Networks for a piloted Quality Management System
Author
Dammak, H.B.M. ; Ketata, Raouf ; Ben Romdhane, Taieb ; Ben Ahmed, Samir
Author_Institution
Nat. Inst. of Appl. Sci. & Technol., Tunis, Tunisia
fYear
2012
fDate
25-28 March 2012
Firstpage
528
Lastpage
531
Abstract
The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management System (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for improving the efficiency of such system. The aim of this approach is to classify the objectives for a real-world case study which presents a major problem for controlling the quality levels of its production lines. This approach provided a significant improvement when the testing data are various or complex.
Keywords
fuzzy neural nets; quality management; decision support; fuzzy neural networks; piloted quality management system; quality level; testing data; Biological system modeling; Classification algorithms; Computational modeling; Fuzzy neural networks; Quality management; Unified modeling language; Fuzzy-Neural Networks; Quality Management System; fuzzy system; learning algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrotechnical Conference (MELECON), 2012 16th IEEE Mediterranean
Conference_Location
Yasmine Hammamet
ISSN
2158-8473
Print_ISBN
978-1-4673-0782-6
Type
conf
DOI
10.1109/MELCON.2012.6196488
Filename
6196488
Link To Document