A unified framework for asset ranking based on their criticality through case studies

Purpose – Effective asset management is grounded in a strategic framework prioritising assets according to their criticality to minimise downtime, reduce maintenance costs and maintain operational efficiency. This paper introduces a unified framework for asset ranking that integrates expert insights, criteria weighting and risk assessment techniques. Unlike standalone approaches, this framework addresses biases and inaccuracies by harnessing the strengths of each method while mitigating their limitations.
Design/methodology/approach – The framework starts with an asset audit that examines field and historical performance data, followed by data cleaning and expert validation through questionnaires to ensure the criteria’s relevance. A pairwise comparison matrix is used to weight the criteria, while risk elements are assessed using failure mode, effects and criticality analysis. This process leads to calculating the risk priority index, which ranks the critical assets.
Findings – The framework is demonstrated through a case study of two 500 kW wind turbine models: geared and direct-drive. The findings reveal that direct-drive turbines are generally more critical, informing their maintenance priorities.
Research limitations/implications – This paper illustrates the framework’s potential for effective resource allocation and risk mitigation, offering flexibility for application across diverse industries. Nevertheless, its reliance on historical data and expert input may need enhancement.
Originality/value – This comprehensive approach ensures a structured method for asset prioritisation that addresses the real-world challenges inherent in asset management by leveraging the strengths of multiple methodologies and mitigating their limitations.