Stochastic behavior analysis of the feeding system in a paper mill using NGABLT technique
International Journal of Quality & Reliability Management
ISSN: 0265-671X
Article publication date: 7 September 2010
Abstract
Purpose
The purpose of this paper is to present a hybridized technique for analyzing the stochastic behavior of an industrial system. The feeding system of a paper mill situated in North India producing 200 tons of paper per day has been considered for analysis and efforts have been made to incorporate vague, ambiguous, imprecise and conflicting information quantified by fuzzy numbers.
Design/methodology/approach
In this paper, three important tools namely, fuzzy analysis, neural network and genetic algorithms (GAs), are used to built a hybridized and more realistic technique herein named as, neural network and GAs‐based Lambda‐Tau (NGABLT). The technique will facilitate the maintenance personnel in making a better decision. This technique has been demonstrated by computing some of the reliability indices of the considered system.
Findings
The results indicate that NGABLT technique reduces the gap between crisp and existing Lambda‐Tau results, i.e. it may be a more useful tool to assess the current system condition and suggests to improve the system reliability and availability.
Originality/value
The authors have suggested a hybridized technique for analyzing the stochastic behavior of the feeding system in a paper mill by computing fuzzy reliability indices.
Keywords
Citation
Sharma, S.P., Kumar, D. and Komal (2010), "Stochastic behavior analysis of the feeding system in a paper mill using NGABLT technique", International Journal of Quality & Reliability Management, Vol. 27 No. 8, pp. 953-971. https://doi.org/10.1108/02656711011075134
Publisher
:Emerald Group Publishing Limited
Copyright © 2010, Emerald Group Publishing Limited