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A machine survival time-based maintenance workforce allocation model for production systems

Ighravwe, D.E and Oke, Sunday Ayoola (2016) A machine survival time-based maintenance workforce allocation model for production systems. African Journal of Science, Technology, Innovation and Development., 8 (5-6). pp. 457-466.

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Abstract

Development. (Published by Taylor and Francis) Abstract: Today’s maintenance workforce operate in a complex business environment and rely on metrics that indirectly link equipment breakdown, fluctuating production rate, demand uncertainties and fluctuating raw material requirements. This has triggered a change of scope as well as the substance of maintenance workforce theory and practice and the necessary requirement to promote a full understanding of maintenance workforce optimisation of some seemingly nonpolynomial hard problems. Theorising is essential on the near optimal solution techniques for the maintenance workforce problem. In this paper, a fuzzy goal programming model is proposed and used in formulating a single objective function for maintenance workforce optimisation with stochastic constraint consideration. The performance of the proposed model was verified using data obtained from a production system and simulated annealing (SA) as a solution method. The results obtained using SA and differential evolution (DE) was compared on the basis of computational time and quality of solution. We observed that the SA results outperform that of DE algorithm. Based on the results obtained, the proposed model has the capacity to generate reliable information for preventive and breakdown workforce maintenance planning.

Item Type: Article
Uncontrolled Keywords: Maintenance planning, meta-heuristics, workforce performance, raw material shortage, conditional probability, fuzzy logic theory
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 16 Feb 2017 11:24
Last Modified: 16 Feb 2017 11:24
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/7794

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