Abstract
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.
Keywords
End-of-Life Processing, Advanced Disassembly/Repair-to-Order
Disciplines
Industrial Engineering | Mechanical Engineering
Publisher
Northeast Decision Sciences Institute
Publication Date
2010
Rights Information
Copyright 2010, Surendra M. Gupta
Rights Holder
Surendra M. Gupta
Permanent URL
Recommended Citation
Ondemir, Onder and Gupta, Surendra M., "An optimization framework for advanced disassembly/repair-to-order systems with remaining-life adjustment" (2010). Mechanical and Industrial Engineering Faculty Publications. Paper 12. http://hdl.handle.net/2047/d20000260
Click button above to open, or right-click to save.
COinS
Notes
Originally published in the Proceedings of the 2010 Northeast Decision Sciences Institute Conference, Alexandria, Virginia, March 26-28, 2010 (CD-ROM)