Human cognitive analysis of disassembly planning using fuzzy petri nets

Disassembly, as the process of systematic removal of desirable constituent parts from an assembly, is of growing importance due to the increasing environmental and economic pressures. Designing and improving disassembly process towards a more economic manner is worthwhile investigating. This paper extends our previous work on human factors in disassembly. More specifically, a Fuzzy Petri Net (FPN) is proposed to mathematically model uncertainties in the disassembly process due to the variations in operator skill level and product condition. An adaptive fuzzy system is further developed for the decision-making in disassembly process planning (DPP), where a learning mechanism is engaged to monitor the quality of various parameter estimates and exploit the past “knowledge” regarding uncertainties. This idea is exemplified through the disassembly of a discarded product with three components.

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