A novel approach for benchmarking maintenance based on fuzzy reliability index for the replacement of street lights under uncertainty

In this study, the authors consider the context of products whose component failures cannot be rectified through repair actions, but can only be fixed by replacement. The authors developed a cost effective decision model based on reliability for the replacement of street lights. The replacement policy for benchmarking maintenance time based on fuzzy reliability index, which can grab uncertainty, is proposed in this study. The study determined the link amongst individual replacement and the group replacement policies by defining the economic instant for replacing street lights. A decision support model incorporating uncertainty and impreciseness is presented to estimate prior maintenance efforts. The individual and the group replacement policies are exposed by housing a subjective theoretical framework and explained with a numerical procedure to illustrate the applicability of the proposed approach. The study provides valuable insight for using the real time information for designing a replacement model using fuzzy logic.