Supply chain control logic for enabling adaptability under uncertainty

Abstract

This paper suggests a probabilistic inference method of quantifying a buyer's likelihood to purchase a highly customised product. The probabilistic inference method utilises the principles of Bayesian networks. This method is integrated into an Internet based supply chain control logic where supply chain partners provide real time or near real time information, regarding the availability of parts needed for the production of highly customisable products. The supply chain plan that is generated is robust, ensuring the supply of the right part at the right time at a rather reasonable cost, thus eliminating the quality defects of the product. The concept is demonstrated in a typical supply chain case, taken from the automotive industry.

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