Abstract
This paper draws on the “human reliability” concept as a structure for gaining insight into the maintenance workforce assessment in a process industry. Human reliability hinges on developing the reliability of humans to a threshold that guides the maintenance workforce to execute accurate decisions within the limits of resources and time allocations. This concept offers a worthwhile point of deviation to encompass three elegant adjustments to literature model in terms of maintenance time, workforce performance and return-on-workforce investments. These fully explain the results of our influence. The presented structure breaks new grounds in maintenance workforce theory and practice from a number of perspectives. First, we have successfully implemented fuzzy goal programming (FGP) and differential evolution (DE) techniques for the solution of optimisation problem in maintenance of a process plant for the first time. The results obtained in this work showed better quality of solution from the DE algorithm compared with those of genetic algorithm and particle swarm optimisation algorithm, thus expressing superiority of the proposed procedure over them. Second, the analytical discourse, which was framed on stochastic theory, focusing on specific application to a process plant in Nigeria is a novelty. The work provides more insights into maintenance workforce planning during overhaul rework and overtime maintenance activities in manufacturing systems and demonstrated capacity in generating substantially helpful information for practice.
Highlights
The promise of human reliability as a principal determinant of risk evaluation success in human-managed systems has since been acknowledged (Boring et al 2004; Boring and Bye 2008)
We suggest the combination of fuzzy goal programming and differential evolution as a solution method for the nonlinear optimisation model generated in the optimal value deformation for the model considering the maintenance workforce variables
We present information on the selected nonlinear mixed-integer optimisation model, fuzzy goal programming (FGP) model and the meta-heuristics which are well thought-out as solution approaches for the formulated FGP procedure
Summary
The promise of human reliability as a principal determinant of risk evaluation success in human-managed systems has since been acknowledged (Boring et al 2004; Boring and Bye 2008). Notwithstanding, human reliability has potentials of deepening and changing our insights of maintenance workforce optimisation. A great deal of the theory of maintenance is inclined to underestimate the outstanding worth of the return-on-investment concept of the human aspect of maintenance (see Raza and Al-Turki 2007). The purpose of this article is to delve into the potentialities for an innovative analysis of a reliability-oriented maintenance workforce optimisation model. The work breaks new grounds in maintenance theory and practice from novel perspectives, drawing inspiration from the outstanding capabilities of fuzzy goal programming, differential evolution and the return-on-investment concept. The concept of return-on-investment is arguably of several decades ago, and has been employed widely in hardware evaluation of maintenance resources
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