ADAPTIVE FUZZY SYSTEM FOR DISASSEMBLY PROCESS PLANNING WITH UNCERTAINTY

Disassembly is rapidly growing in importance as manufacturers face increasing pressure to deal with obsolete products in an environmentally responsible and economically sound manner. This paper builds upon our previous work to address uncertainty management in disassembly. By taking advantage of fuzzy logic and the formalism of Petri nets, this paper proposes a Fuzzy Disassembly Petri Net (F-DPN) model to mathematically represent uncertain product/component conditions. An adaptive fuzzy system with an iterative learning mechanism is then designed to dynamically estimate their impact on a disassembly process. Finding the disassembly path of a discarded product with the highest economic value and prediction confidence is accomplished through a recursive computation. The proposed method is exemplified and validated through the disassembly of a batch of telephone handsets.