Achieving sharp deliveries in supply chains through variance pool allocation

Garg, D and Narahari, Y and Viswanadham, N (2006) Achieving sharp deliveries in supply chains through variance pool allocation. In: European Journal of Operational Research, 171 (1). pp. 227-254.

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Abstract

Variability reduction and business process synchronization are acknowledged as key to achieving sharp and timely deliveries in supply chain networks. In this paper, we develop an approach that facilitates variability reduction and business process synchronization for supply chains in a cost effective way. The approach developed is founded on an analogy between mechanical design tolerancing and supply chain lead time compression. We first present a motivating example to describe this analogy. Next, we define, using process capability indices, a new index of delivery performance called delivery sharpness which, when used with the classical performance index delivery probability, measures the accuracy as well as the precision with which products are delivered to the customers. Following this, we solve the following specific problem: how do we compute the allowable variability in lead time for individual stages of the supply chain so that specified levels of delivery sharpness and delivery probability are achieved in a cost-effective way? We call this the variance pool allocation (VPA) problem. We suggest an efficient heuristic approach for solving the VPA problem and also show that a variety of important supply chain design problems can be posed as instances of the VPA problem. One such problem, which is addressed in this paper, is the supply chain partner selection problem. We formulate and solve the VPA problem for a plastics industry supply chain and demonstrate how the solution can be used to choose the best mix of supply chain partners.

Item Type:	Journal Article
Publication:	European Journal of Operational Research
Publisher:	Elsevier Science B.V.
Additional Information:	Copyright for this article belongs to Elsevier B.V.
Keywords:	Supply chain management; Lead time reduction; Variability reduction; Process capability indices; Statistical tolerancing; Variance pool allocation (VPA)
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	26 Nov 2007
Last Modified:	19 Sep 2010 04:22
URI:	http://eprints.iisc.ac.in/id/eprint/5027

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