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Scheduling preventive maintenance of oil pumps using generalised proportional intensities models

Percy, D. and Alkali, B. (2007) Scheduling preventive maintenance of oil pumps using generalised proportional intensities models. International Transactions in Operational Research, 14 (issue: 6). pp. 547-563. ISSN Print ISSN: 0969-6016; Online ISSN: 1475-3995

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Abstract

Percy and Alkali presented generalizations of the proportional intensities model introduced by Cox. They identified several features of these models that are particularly relevant for modelling complex repairable systems subject to preventive maintenance (PM). These include the baseline intensity, scaling factors and explanatory variables. We investigate these aspects in detail and apply the models to five sets of reliability data collected from the main pumps at oil refineries. We use likelihood methods to estimate the model parameters and compare how well the models fit the data. Our analyses suggest that a log-linear baseline intensity function performs well and that an exponential deterministic scaling function is useful for corrective maintenance. The inclusion of explanatory variables to represent the quality of last maintenance and time since last maintenance also proves to be beneficial. We develop algorithms for simulating the reliability behaviour of a complex repairable system into the future, in order to schedule appropriate maintenance activities, identifying special cases that simplify the algebra. Applying these methods to the oil pump data, we derive recommendations for PM plans and demonstrate that adopting this strategy can lead to substantial savings.

Item type: Article
ID code: 9173
Keywords: complex repairable system • generalized proportional intensities models • preventive maintenance scheduling, Commerce, Technology (General), Management. Industrial Management, Probabilities. Mathematical statistics, Business and International Management, Strategy and Management, Computer Science Applications, Management Science and Operations Research, Management of Technology and Innovation
Subjects: Social Sciences > Commerce
Technology > Technology (General)
Social Sciences > Industries. Land use. Labor > Management. Industrial Management
Science > Mathematics > Probabilities. Mathematical statistics
Department: Strathclyde Business School > Management Science
Related URLs:
Depositing user: Strathprints Administrator
Date Deposited: 26 Nov 2009 14:30
Last modified: 04 Sep 2014 21:02
URI: http://strathprints.strath.ac.uk/id/eprint/9173

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