Title: Decision support system for maintenance order priority of multistate coal handling system with hot redundancy

Authors: Sudhir Kumar; P.C. Tewari; Anish Kumar Sachdeva

Addresses: Department of Production and Industrial Engineering, National Institute of Technology, Kurukshetra, Haryana, India ' Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, Haryana, India ' Department of Industrial and Production Engineering, Dr. B.R. Ambedkar National Institute of Technology Jalandhar, India

Abstract: This paper describes newly developed decision support system for maintenance order priority which is an essential requirement to maintain excellent maintenance operations. It also discusses the performability evaluation of coal handling system of a coal-based thermal power plant using the stochastic petri nets (SPN) technique. A licensed version of petri GRIF-predicates software was used for the modelling purpose. The performability in long-term availabilities of the different subsystems is obtained by varying failure and repair rates (FRR) in permissible ranges during performance modelling of plant. Based upon the performability matrices the maintenance order priorities of subsystems were predicted. The present paper examines the impact of varying failure and repair rates of subsystems on the performance behaviour and performability of coal handling system. Further, the effect of varying the repair facilities available on the performability of whole system is also evaluated. From the performability matrices, it has been observed that crushers are the most critical subsystems which drastically affect the overall performability of system. The critical study would help the maintenance engineers to plan for allocation of repair facilities for the different subsystems in advance based upon the severity of their failure.

Keywords: performability analysis; decision support system; DSS; Petri-Nets; coal handling system; stochastic petri nets; SPN; failure and repair rates; FRR.

DOI: 10.1504/IJIE.2024.137672

International Journal of Intelligent Enterprise, 2024 Vol.11 No.2, pp.103 - 119

Received: 10 Oct 2022
Accepted: 24 Jul 2023
Published online: 02 Apr 2024 *

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