Authors: Ajith Kumar Parlikad, Duncan McFarlane
Addresses: Department of Engineering, Institute for Manufacturing, Cambridge University, 17 Charles Babbage Road, Cambridge CB3 0FS, UK. ' Department of Engineering, Institute for Manufacturing, Cambridge University, 17 Charles Babbage Road, Cambridge CB3 0FS, UK
Abstract: Product recovery is beset by uncertainty regarding the quality of end-of-life (EOL) products, and in order to ascertain the reusability of these products, they have to undergo expensive tests. This undermines the profitability of the recovery process. The key to improve the effectiveness of product recovery is to improve the quality of information available before testing. Emerging data capture technologies can significantly improve the availability of information. However, in order to maximise the potential of these technologies, appropriate decision-making algorithms that exploit such information must be developed. We model the recovery process using a decision-theoretic approach, and derive strategies to ascertain the reusability of EOL products, and also to decide when tests are beneficial. We show that improving the quality of information leads to increase in effectiveness of the recovery process by reducing the need for tests.
Keywords: decision analysis; applied probability; uncertainty modelling; product recovery decisions; decision making; EOL products; end-of-life products; product reuse; information quality; data capture; decision theory.
International Journal of Product Lifecycle Management, 2009 Vol.4 No.1/2/3, pp.186 - 206
Received: 04 Jun 2009
Accepted: 22 Sep 2009
Published online: 17 Feb 2010 *