Uncertainty propagation in a supply chain / network with uncertain facility performance Conference

Rezapour, S, Allen, JK, Mistree, F. (2014). Uncertainty propagation in a supply chain / network with uncertain facility performance . 7 10.1115/DETC201434255

cited authors

  • Rezapour, S; Allen, JK; Mistree, F


  • Decentralized production systems in supply chains / networks makes them more profitable and agile than traditional enterprises with centralized production systems. However, this decentralization makes supply chains / networks more vulnerable respect to uncertainties which are unavoidable. Today's supply chains / networks producing and supplying their products to markets are characterized by uncertain demands (called demand-side uncertainty) and uncertainties associated with the performances of their constituent production facilities (called supply-side uncertainty). Supply-side uncertainty is due to the fact that there is not any perfect production system. Sparse literature of supplyside uncertainty management in supply chains / networks is only restricted to supply chains / networks with single-echelon supply processes. However most of the real case supply chains / networks have longer production processes involving suppliers of suppliers, suppliers, component manufacturers, assemblers, etc. In this paper we fill this gap of the literature by considering a supply chain/network with multi-echelon supply process including unreliable production facilities working in markets with uncertain demands. We show that in such a complex production process in addition to investigating the local effects of the uncertainties in the performances of their corresponding facilities, it is necessary to consider their global and cumulative effect on the performance of the entire supply chain/networks by following the propagation of these uncertainties in the flow of the material and product. Not only we introduce and describe the salient features of uncertainty propagation phenomenon in supply chains/networks, but also we demonstrate its quantification approach. Finally we propose mathematical models and solution approaches that can provide robust production plans for the supply chain/network that are protected against all demand and supply side uncertainties and their propagated effects. Performances of the proposed models and solution approaches are tested with test problems and a real case problem from automotive industry.

publication date

  • January 1, 2014

Digital Object Identifier (DOI)

International Standard Book Number (ISBN) 13


  • 7