Title: Decision support system for maximum availability of series-parallel system using particle swarm optimisation

Authors: Ajay Kumar; Ramesh Kumar Garg

Addresses: Department of Mechanical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, 131 039, Haryana, India ' Department of Mechanical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, 131 039, Haryana, India

Abstract: The scope of the present study is to compute optimal availability of various systems of an existing brewery plant using particle swarm optimisation technique. The aim of research paper is focused towards development of structural and mathematical modelling of concerned systems using Markov method in order to examine the criticality of various sub-systems/components and to devise maintenance plans and strategies. In order to achieve the major objectives, the research work is limited to a case study of an existing brewery plant located in the nearby region and repairable systems only. Exponential distribution is used to define the availability importance measures assuming that the failure and repair rates are constant for steady state analysis. In order to explore various possible combinations of random failure and repair rate to achieve optimal availability of a system, an evolutionary optimisation technique, i.e., particle swarm optimisation (PSO) is applied for the first time. The technique is validated by comparing the results obtained for optimal availability with that of existing optimising technique, i.e., genetic algorithm and Markov method. It is established that the results are useful for plant personnel for analysing system behaviour and thereby to improve the system performance by adopting suitable maintenance schedule and strategies.

Keywords: performance evaluation; Wort Kettle; failure rate; repair rate; brewery plant; particle swarm optimisation; PSO; decision support systems; DSS; maximum availability; series-parallel systems; structural modelling; mathematical modelling; case study; maintenance scheduling; maintenance strategies.

DOI: 10.1504/IJIE.2016.076042

International Journal of Intelligent Enterprise, 2016 Vol.3 No.2, pp.148 - 169

Received: 01 Jul 2015
Accepted: 06 Oct 2015
Published online: 22 Apr 2016 *

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