A hybrid decision support system for slow moving spare parts joint replenishment: a case study in a nuclear power plant

This paper presents a hybrid Decision Support System (DSS) for slow moving spare parts joint replenishment in a nuclear power plant. In this study, we integrate the fuzzy and grey theory-based spare parts criticality class evaluation model to confirm the target service level, and the web-based joint replenishment DSS to obtain reasonable purchase parameters that can be helpful for reducing total inventory holding costs. The proposed DSS was successful in decreasing inventories holding costs significantly by modifying the unreasonable purchase applications while maintaining the predefined target service level.

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