藉拆卸順序構造圖達成多目標之選擇性拆卸順序規劃

Abstract

選擇性拆卸是一門藉由有計畫性的拆除產品各種零件，來達到重複利用、再回收以及重新製造等功能以達到綠色設計的學問。其包含的項目－拆卸順序規劃的發展已從單一目標零件演變成多目標零件，但是諸多細節，例如：緊固件的種類及限制或是拆除方向等的考量仍不夠完善。因此本篇論文針對多目標之選擇性拆卸順序規劃，提出了新的一套圖像表示法－拆卸順序構造圖，主要考量為緊固件的限制、減少零件拆卸數量以及降低拆卸產品方向變換次數。藉由參考前人之'以規則為基礎的遞歸選擇性拆卸順序規劃的綠色設計'獲得建構零件拆卸順序構造圖的資訊。本研究再進一步使拆卸順序構造圖具有可合併整合的特性，藉由此特性可以有效率的快速獲得多目標之拆卸順序。並且，本論文使用了基因演算法來獲得拆卸順序構造圖的結果並且轉換成實際順序。最後透過兩個案例討論，有系統地展示使用拆卸順序構造圖獲得多目標之拆卸順序辦法的全部流程以及結果。

“Selective disassembly” disassembles certain product components for reuse, recycle, and remanufacturing to achieve the goal of green design. It has developed from single-target to multiple-target, but the details such as fasteners constraint, and disassembly directions are still not considered throughly. This thesis proposes a new method for multiple-target selective disassembly sequence planning using a Disassembly Sequence Structure Graph (DSSG). Fasteners constraint, minimal removals, and minimal reorientations are considered in this thesis. According to parameters settings of the thesis “Rule-Based Recursive Selective Disassembly Sequence Planning for Green Design”, we are able to obtain necessary information for constructing a DSSG. By the characteristics of DSSG that different DSSGs are able to be combined into one DSSG with multiple target components, the proposed method can obtain a multiple target disassembly sequence fast and efficiently. Furthermore, a genetic algorithm is used to optimize the results and transfer the graphical information into realistic disassembly sequences. In the end, two case studies show the capabilities of the proposed method and final results are presented.