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Journal of Intelligent & Robotic Systems

, Volume 91, Issue 3–4, pp 603–616 | Cite as

A Decision Maker-Centered End-of-Life Product Recovery System for Robot Task Sequencing

  • Mohammad Alshibli
  • Ahmed El Sayed
  • Ozden Tozanli
  • Elif Kongar
  • Tarek M. Sobh
  • Surendra M. Gupta
Article

Abstract

End-of-life (EOL) disassembly focuses on regaining the value embodied in products which are considered to have completed their useful lives due to a variety of reasons such as lack of technical functionality and/or lack of demand. Disassembly is known to possess unique characteristics due to possible changes in the EOL product structure and hence, cannot be considered as the reverse of assembly operations. With similar reasoning, obtaining a near-optimal/optimal disassembly sequence requires intelligent decision making during the disassembly when the sequence needs to be regenerated to accommodate these unforeseeable changes. That is, if one or more components which were included in the original bill-of-material (BOM) of the product is missing or if one or more joint types are different than the ones that are listed in the original BOM, the sequence needs to be able to adapt and generate a new and accurate alternative for disassembly. These considerations require disassembly sequencing to be solved by more powerful and versatile methodologies justifying the utilization of image detection technologies for online real-time disassembly while imposing search techniques which would provide more efficient solutions than their exhaustive search counterparts. Therefore, EOL disassembly sequencing literature offers a variety of heuristic techniques. As with any data driven technique, the performance of the proposed methodologies is heavily reliant on the accuracy and the flexibility of the algorithms and their abilities to accommodate several special considerations such as preserving the precedence relationships during disassembly while obtaining near-optimal or optimal solutions. This study builds on previous disassembly sequencing research and introduces an automated robotic disassembly framework for EOL electronic products. The model incorporates decision makers’ (DMs’) preferences into the problem environment for efficient material and component recovery. A numerical example is provided to demonstrate the functionality of the proposed approach.

Keywords

Computer Science Decision support techniques Disassembly sequencing Electronic product recovery Industrial robots Multiple criteria decision making Recycling Robotic manipulation Simulated annealing 

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringUniversity of BridgeportBridgeportUSA
  2. 2.Department of Computer Science and EngineeringUniversity of BridgeportBridgeportUSA
  3. 3.Department of Technology ManagementUniversity of BridgeportBridgeportUSA
  4. 4.Departments of Mechanical Engineering and Technology ManagementUniversity of BridgeportBridgeportUSA
  5. 5.CMfgE, School of EngineeringUniversity of BridgeportBridgeportUSA
  6. 6.Mechanical and Industrial Engineering and Director of Laboratory for Responsible Manufacturing, 334 SN, Department of MIENortheastern UniversityBostonUSA

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