Abstract:
Industrial facilities such as power plants often experience significant production losses due to unanticipated
failures, suboptimal maintenance, operational activities and challenges in spare parts logistics. Furthermore, they
portend loss of reputation, significant societal disruptions and poor manpower utilization. Critical performance
measures for power plants, notably availability of the equipment and repair time, directly affect plant economics
and reliability. Consequently, maintenance optimization is crucial and requires considering the effects of and
interaction between factors such as spares availability, diagnosis time, time between overhaul (TBO) and
accurate maintainability. To realistically model such complexities, a discrete simulation model of critical engine
subsystems in a thermal power plant is proposed, where various model parameters are derived from actual data
and expert input, to optimize diagnosis and repair times, TBO and spares availability, while considering engine
availability and total repair time as performance measures. The developed simulation model returns availability
of 90.001% and total repair time of 18,313 hours, while the turbocharger is identified as the critical subsystem.
Optimizing spares availability is observed to have highest impact on equipment availability with TBO having a
similar impact on the total repair time. Interaction of spares availability and TBO is observed to averagely
improve the system availability and reduce repair time of the equipment. Utilization and planning of manpower,
spares sourcing lead times and quality of repair diagnosis are other areas identified requiring attention. The study
quantitatively evaluates the effects and interactions and further enhances maintenance decision making towards
optimising the plants’ operational and maintenance related factors.
