Adaptive Fuzzy System for Disassembly Process Planning with Uncertainty

用於不確定環境下拆卸計畫管理的自適應模糊系統

10.29977/JCIIE.200701.0002

唐瑛(Ying Tang)；馬克確繞斯基(Mark Turowski)

拆卸計畫過程 ； 自適應模糊系統 ； 模糊Petri nets ； 不定因素管理 ； disassembly process planning ； adaptive fuzzy system ； fuzzy Petri nets ； uncertainty management

工業工程學刊

24卷1期（2007 / 01 / 01）

20 - 29

英文

目前，製造商門面臨各方的壓力去有效的處理他們廢舊的產品，減少這些廢舊品對環境的影響。隨著這些壓力的不斷增加，拆卸工程變得越來越重要。基於我們以前的工作，這篇文章主要是探討了拆卸過程中的不定因素的管理。利用模糊控制和Petri Nets的優點，我們建立了一個模糊拆卸Petri net模型(F-DPN)，用數學的方法去表現產品或者零件的不定狀態。基於這個模型，我們設計了一個有學習功能的自適應模糊系統去動態的評估這些不定狀態對拆卸過程的影響。通過不斷的遞迴計算，我們的方法最終能找到一個最優的拆卸途徑，給與製造商們最大的經濟回報。電話聽筒拆卸的實例進一步驗證我們的方法。

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.

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