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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