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Disturbances in terms of major crises such as pandemics, fluctuations in demand and oil price, energy consumption and supply chain can significantly impair the maintenance programs effectiveness and efficiency. Hence, there is an urgent need for an agile asset performance management (AAPM) framework.

This paper's main objective is to design a comprehensive framework for an AAPM system that sustains the desired asset performance by reacting efficiently, quickly and intelligently to the changes in the operating context parameters and asset health conditions. Such a framework is adaptive to changes in scenarios and aims to systematise the decision support process, considering different objectives.

The development of the proposed framework has led to identifying an innovative way of seamless integration between crucial reliability and asset management tools. Also, the methodology implementation is expected to promote the practical use of its reliability tools and enable asset stakeholders to break silo working for clear communication around asset performance.

The implementation of the AAPM framework follows a new approach developed during this research and coined by the authors as the “8S approach.”

The main purpose is to provide a demonstration of the utility of the DMG as a streamlined approach of a prescriptive-type model that can facilitate strategic and dynamic methodology to the decision-maker with respect to what policies, strategies or actions should be carried out.

This paper proposes a framework for an agile criticality assessment process using decision-making grid (DMG) to accommodate the needs of this dynamic environment.

The proposed new approach has delivered better results with more consistency when applied by different teams and achieved better distribution of assets over the criticality scale.

The proposed approach has been validated through an industrial case study related to a steam generation system (SGS).

The implementation of the proposed approach in a petroleum refinery to assess the criticality of steam generation system (SGS) has shown positive results in terms of time and effort optimization. This research contributes to production planning and control literature with respect to one of its core activities of maintenance, through an innovative, systematic and practical approach.