Asset management optimization through integrated systems thinking and N-1 contingency capability for refurbishment.

Abstract

This paper presents a systems view of refurbishment systems to evaluate root causes of suboptimal refurbishment. Case studies from ten selected South African and Malawian firms from largest electric power utilities, mining, petrochemical, and processing industries were used to establish causal relationships. Sample surveys of thirty four Malawian firms were used as part of a multimethod or triangulation approach to provide generalizations, validation and reliability. Of the surveyed firms, 66.7%, and of case studied firms 100%, showed that deferred refurbishment was a result of constrained capacity which led to components operating at higher loads, to lack of maintenance windows and to increased failure rates; there was no formal refurbishment model and technical skills base was the weakest asset management link. The study advances a novel way of depicting root causes of suboptimal refurbishment in typically complex dynamic structures using integrated systems thinking approach and applies analytical optimization tools, namely: Linear Programming (LP), metrics and N-1 contingency capability for refurbishment model for drilling deeper into causal typologies portrayed by systems thinking in order to solve optimization problems. A Total Refur-bishment Process model is advanced to replicate refurbishment decision structures for long term sustainability of industries as validated by industries studied.