Criticality assessment of steam turbine components in the sugar industry using the COPRAS-G MCDM approach

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Authors: Bahubali Balaso Farande, Hanumant Pandurang Jagtap
Cited by: 0
References: 23

Abstract

Purpose The purpose of this project is to improve the steam turbines’ reliability and continuity of operation in cogeneration facilities used in the sugar processing sector. The research focusses on identifying important components to assist optimal maintenance and risk management strategies because steam turbines are complicated and susceptible to various failure mechanisms. Design/methodology/approach By using the Complex Proportional Assessment with Grey Relations (COPRAS-G) method, a sophisticated Multi-Criteria Decision-Making (MCDM) technique, an enhanced Failure Mode and Effect Analysis (FMEA) framework is created. Seven essential criteria Severity, Occurrence, Detectability, Maintainability, Production Loss, Spare Parts Availability and Operator Skill are used to evaluate the criticality of 32 steam turbine components. The evaluation's robustness is increased by using grey relational analysis to address subjectivity and uncertainty in expert judgements. Findings The diaphragm, shaft and blades are the most important parts of steam turbines, according to the analysis. The diaphragm is placed first because of common and serious failure causes, such as erosion and misalignment. The findings offer a list of components ranked in order of importance, which directs resource allocation and maintenance scheduling. Originality/value In order to provide a more thorough and data-sensitive framework for failure mode prioritisation in complex mechanical systems, this study presents a novel integration of COPRAS-G with conventional FMEA. It is a useful resource for scholars and industry experts engaged in criticality analysis and steam turbine maintenance optimisation, and it offers practical insights for reliability engineering.

Fields of Study & Subjects

Reliability and Maintenance Optimization Multi-Criteria Decision Making Management and Optimization Techniques

Publication details

Journal / source
International Journal of Quality & Reliability Management
Volume
43
Issue
4
Pages
1135–1156
Publication date
27 February 2026
Language
EN