Paper Info
Title
A fuzzy reasoning based diagnosis system for X control charts
Abstract
This paper describes a new diagnosis system, which is based on fuzzy reasoning to monitor the performance of a discrete manufacturing process and to justify the possible causes. The diagnosis system consists chiefly of a knowledge bank and a reasoning mechanism. The knowledge bank provides knowledge of the membership functions of unnatural symptoms that are described by Nelson's rules on X control charts and knowledge of cause-symptom relations. We develop an approach called maximal similarity method (MSM) for knowledge acquisition to construct the fuzzy cause-symptom relation matrix. Through the knowledge bank, the diagnosis system can first determine the degrees of an observation fitting each unnatural symptom. Then, using the fuzzy cause-symptom relation matrix, we can diagnose the causes of process instability. In conclusion we provide a numerical example to illustrate the system.
Year
DOI
Venue
2001
10.1023/A:1008903614042
J. Intelligent Manufacturing
Keywords
DocType
Volume
Fuzzy reasoning,knowledge acquisition,diagnosis system,process control,X control chart
Journal
12
Issue
ISSN
Citations 
1
1572-8145
9
PageRank 
References 
Authors
1.54
2
2
Name
Order
Citations
PageRank
Hsi-Mei Hsu119932.69
Yan-kwang Chen29211.96