Maximising availability of complex repairable systems and flexible selection of performance parameter using PSO
by Ajay Kumar
International Journal of Productivity and Quality Management (IJPQM), Vol. 33, No. 4, 2021

Abstract: In this research study, particle swarm optimisation (PSO) has been implemented for availability analysis of a complex repairable industrial system namely mash kettle of an existing brewery plant. PSO algorithm is computationally simple and efficient. The mash kettle system is modelled structurally representing its various constituent elements/components and their interconnections. Probability relationship of different feasible state are generated using the transition diagram. Performance analysis is done to observe the criticality of the constituent elements/components. The particle swarm optimisation algorithm provides a varied and wide range of performance measures of various elements/components for a predetermined optimised value of the availability of the system. PSO algorithm is validated by comparing with genetic algorithm and Markov methods for the results of optimal availability. The consequences of this paper will be beneficial for the maintenance engineer and plant staff to accomplish best attainable system performance/availability and to plan appropriate maintenance strategies.

Online publication date: Wed, 25-Aug-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Productivity and Quality Management (IJPQM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com