Int. J. of Industrial and Systems Engineering   »   2010 Vol.6, No.1

 

 

Title: Stochastic behaviour and performance analysis of an industrial system using GABLT technique

 

Author: Komal, S.P. Sharma, Dinesh Kumar

 

Addresses:
Department of Mathematics, Indian Institute of Technology Roorkee (IITR), Roorkee 247667, Uttarakhand, India.
Department of Mathematics, Indian Institute of Technology Roorkee (IITR), Roorkee 247667, Uttarakhand, India.
Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee (IITR), Roorkee 247667, Uttarakhand, India

 

Abstract: Stochastic behaviour of an industrial system will help to analyse the system's performance and to carry out design modifications to achieve the desired industrial goals. In the present study, genetic algorithms based Lambda-Tau, a hybridised technique is used to analyse the system's behaviour up to a desired degree of accuracy utilising imprecise data. Six reliability indices, namely, failure rate, repair time, mean time between failures, expected number of failures, availability and reliability of the system are used for system's behaviour analysis. A composite measure of these reliability indices as a performance index has been introduced in this paper to predict the system's performance at different preferences. The washing unit of a medium size paper mill has been considered to demonstrate the approach. The observed results show reduced uncertainty from traditional analysis and will be very helpful for plant personnel to improve the system's performance by adopting suitable maintenance strategies.

 

Keywords: complex engineering; Lambda-Tau; genetic algorithms; membership functions; stochastic behaviour; performance index; performance analysis; industrial systems; GABLT technique; design modifications; accuracy; imprecise data; reliability indices; failure rates; repair times; mean time; expected failures; system availability; behaviour analysis; composite measures; washing units; paper mills; maintenance strategies; hybridised techniques; industrial engineering; systems engineering.

 

DOI: 10.1504/IJISE.2010.033994

 

Int. J. of Industrial and Systems Engineering, 2010 Vol.6, No.1, pp.1 - 23

 

Available online: 06 Jul 2010

 

 

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