Asset Management Optimisation Through Integrated Systems Thinking and N-1 Contingency Capability for Refurbishment

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 fourMalawian 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 Refurbishment
Process model is advanced to replicate refurbishment
decision structures for long term sustainability of industries as
validated by industries studied.
Index Terms—Integrated systems thinking, N-1 contingency
capability for refurbishment, metrics, asset management tools,
Malawi, South Africa.