A grey-based approach for managing uncertainties and performance in automotive supply chains

Abstract

Automotive supply chains are among the most complicated chains to manage because of the involvement of enormous number of suppliers and the associated uncertainties. Any disruption in the chain has a great impact on the performance of the entire chain. Uncertainties in supply chains interfere with their performance and managing uncertainties and risks to reduce this interference is a costly affair. The supply chain managers, therefore, need to prioritise uncertainties in terms of their negative impact on the performance. This will help them identify and adopt an appropriate mitigation strategy to reduce the effect of any kind of uncertainty on a given parameter of performance. Since the occurrence of any kind of uncertainty and its effect on a given performance parameter cannot be ascertained for a selected time horizon, a grey-based modelling technique has been developed to model the relationship between uncertainty and performance.