Due to environmental awareness and realization of cost savings, disassembly-to-order (DTO) concept has become popular. One of the main obstacles to making optimal DTO decisions is the uncertainty involved in end-of-life products (EOLPs). This uncertainty is due to the lack of information about the condition and the quantity of EOLPs returned. This uncertainty is removed by advanced disassembly/repair-to-order systems utilizing sensors to monitor the products in their life-cycle. Sensor technology enables remaining life estimation, thus allows advanced DTO models to deal with sophisticated component and product demands with remaining life adjustment.

This paper presents an optimization framework for advanced disassembly/repair-to-order (ADRTO) systems. The method is compared with a TABU search based heuristic algorithm.


Originally published in the Proceedings of the 2010 Northeast Decision Sciences Institute Conference, Alexandria, Virginia, March 26-28, 2010 (CD-ROM)


end-of-life processing, advanced disassembly/repair-to-order


Industrial Engineering | Mechanical Engineering


Northeast Decision Sciences Institute

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Copyright 2010, Surendra M. Gupta

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Surendra M. Gupta

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