ABSTRACT Substantial economic investments are made by companies in the construction and other processing industries to own and operate heavy equipment fleets. Average total cost minimization models are used by equipment managers to perform a variety of tasks that are largely influenced by the economic performance of the fleet. An important aspect of these models is estimating maintenance and repair costs throughout machine life. The period cost-based (PCB) methodology can be used to model maintenance and repair costs from data collected over a period of time within the life of a machine. The objective of this research was to investigate the effect of the data collection period length on the resulting PCB models and develop recommendations regarding the minimum period length. Data collected from a fleet of excavator-type material handlers were used to construct cost records of varying period lengths, to which the PCB methodology was applied to construct marginal and cumulative cost models. The results show that increasing the period length increases the quality of the marginal cost model and the accuracy of the estimated cumulative costs. However, this is subject to the constraint that the amount of data available for model development does not significantly decrease.
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