Analysis of an adaptive fuzzy system for disassembly process planning

Mark Turowski, Ying Tang, Matthew Morgan

Research output: Contribution to conferencePaperpeer-review

6 Scopus citations

Abstract

As product lifecycles are getting shorter and shorter, manufacturers are facing a great deal of economic and political pressure to reclaim and recycle their obsolete products. Disassembly, as one of the natural solutions, is of increasing importance in material and product recovery. However, most of the existing works on disassembly process planning use a deterministic model to characterize the high levels of uncertainty (e.g., uncertainty in product structure and condition and human factors) inherent in the process. This paper builds upon our previous work [7,8] to explicitly address the dynamics in disassembly using Fuzzy Petri Nets. An adaptive fuzzy system with an enhanced learning method is proposed to predict the impact of human factors and product uncertainty on disassembly. Simulation software is also developed to validate the proposed method and the robustness of the adaptive fuzzy system.

Original languageEnglish (US)
Pages249-254
Number of pages6
StatePublished - Dec 15 2005
Event2005 IEEE Interantional Symposium on Electronics and the Environment - Conference Record - New Orleans, LA, United States
Duration: May 16 2005May 19 2005

Other

Other2005 IEEE Interantional Symposium on Electronics and the Environment - Conference Record
CountryUnited States
CityNew Orleans, LA
Period5/16/055/19/05

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Waste Management and Disposal
  • Pollution
  • Electrical and Electronic Engineering

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