Abstract
In this thesis, a maintenance evaluation and improvement methodology is presented, which makes use of maintenance data to determine failure characteristics of repairable systems and the effectiveness of maintenance policies being conducted on them. The objective is to provide a way in which maintenance data can be collected, organized, cleaned and formatted to provide information on component failures analytics, system availability and utilization so as to determine flaws in maintenance strategies. The methodology also provides context for the study of maintenance effectiveness, and synthesizes its importance within the grander scheme of maintenance optimization of repairable systems. We consider a repairable system whose failures follow a Non-Homogenous Poisson Process (NHPP) with the power law intensity function. The system is subject to corrective and multiple types of preventive maintenance. We assume the effects of different preventive maintenance on the system are not identical, and estimate the parameters of the failure process as well as the effects of preventive maintenance. Ultimately, the methodology serves to guide maintenance designers in measuring the effectiveness of current maintenance policies and providing granular analysis on current failure trends to arrive at data-driven options for maintenance improvement. The proposed methodology was applied to a real case study of four AC-powered dump trucks used at an underground mine in Sudbury, Canada.
Highlights
The progress of technological developments namely high-speed computing and increased data storage capacity makes the improvement of day-to-day production, logistics and maintenance operations possible
It is no doubt that high intensity production rates entails the possibility of equipment failures, system downtime and heavy production losses incurred which are unrecoverable in most circumstances [1]
The improvement factor ρ, in addition to the shape parameter β and characteristic age α are sufficient to model the rate of failure occurrence of a repairable system with respect to its ‘operating time’ as it is influenced by its repair policy
Summary
A repairable system subject to corrective and multiple types of preventive maintenance. Conditional reliability over the period between two consecutive PMs for the mobile subsystem of Truck#3. Conditional reliability over the period between two consecutive PMs for the mobile subsystem of Truck#4 viii. The expected and observed numbers of failures over the period between two consecutive PMs for the Mobile subsystem of Truck #4 ix
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