Edwards, D J and Holt, G D (2001) Predicting construction plant maintenance expenditure. Building Research & Information, 29(6), pp. 417-427. ISSN 0961-3218
Abstract
Utilization of construction plant and equipment forms an essential part of construction contractors' efforts to augment productivity and reduce costs. However, efficient and effective management of plant and equipment is requisite to maximizing its potential benefits. A problem in this respect is now knowing when a maintenance event might occur, or its extent in terms of cost and time. This paper presents a stochastic mathematical modelling methodology (using random numbers) to predict the probable cost of 'the next' maintenance event for tracked hydraulic excavators; where a maintenance event includes both breakdown and scheduled maintenance. Information on a random sample of 33 360° tracked hydraulic excavators were obtained from contractors operating within the opencast mining industry. From these, 9473 maintenance event 'cost' observations were recorded and modelled. Validation of the model is achieved using a random 'hold out' sample of 50 maintenance cost observations taken from nine machines. Analyses reveal that overall model predictive performance is robust, having a mean percentage error (MPE) of 4.46 and a mean absolute percentage error (MAPE) of 23.63. Pearsons correlation coefficient (r) and a paired t-test are conducted to determine the accuracy and consistency of model predictions respectively. With an r of 0.76 and no significant difference being found between the mean of predicted/actual values, the model shows both accurate and consistent cost predictions. The random number technique shows potential for improved maintenance practice by providing a practical methodology for planning, scheduling and controlling future plant resource requirements. The paper concludes with direction for future research which includes: (1) the application of this research to plant items working in other operational environments (e.g. civil engineering and construction); and (2) prediction of the next breakdown event.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | construction plant; financial management; linear interpolation; maintenance; management; prediction; stochastic random numbers; UK |
| Index terms: | productivity, accuracy, financial management, construction plant, cost prediction, scheduling, construction contractor, plant and equipment, maintenance cost, mining, mathematical modelling, methodology, validation, hydraulic |
| Subjects: | practitioner, financial and cost management, analytical methods, fluid mechanics, economic analysis, operations research, construction equipment, professional development, research methods, financial management, manufacturing engineering, management, geotechnical engineering |
| Topics: | Time Control, Research Practice, Engineering Principles, Information Management, Business Strategy, Cost Management, Plant and Equipment, Roles and Professions |
| Descriptive scope: | 4 PCTA |
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