Application of a Taguchi-fuzzy approach for prediction of maintenance-production workforce parameters of manufacturing systems

Abstract

Maintenance workforce evaluation has recently received increased attention due to its significant positive influence on manufacturing. Much theoretical and practical work has been done in this area. However, its optimisation considering uncertainties has not been adequately addressed. The current study develops a novel approach providing an understanding of the uncertainties while including factors for workforce size determination using an integrated Taguchi-fuzzy technique. The feasibility of a fuzzy maintenance workforce model as an expert tool was investigated and the results were validated using a literature model. The current study observed that the developed fuzzy workforce prediction and optimisation tool can be used to avoid complex mathematical expressions for workforce size prediction. Compared to ARIMA, the model offers comparable results and can be easily used by maintenance mangers.