【摘要】：產(chǎn)品拆卸是綠色制造的重要環(huán)節(jié),拆卸序列規(guī)劃的目的是尋找拆卸成本最低,耗費(fèi)時(shí)間最短的拆卸路徑。 為了使拆卸序列的評(píng)價(jià)更加符合實(shí)際,本文著重研究了拆卸序列的穩(wěn)定性評(píng)價(jià)方法。為了提高拆卸過程的穩(wěn)定性,減少拆卸時(shí)間,降低拆卸成本,本研究將緊固件看作獨(dú)立的零件,分析螺紋面在重力支撐關(guān)系中的作用,然后根據(jù)重力的逐級(jí)傳遞關(guān)系建立重力支撐矩陣。然后,根據(jù)該矩陣判斷并計(jì)算子裝配體中不穩(wěn)定零件的數(shù)量,對(duì)拆卸序列的穩(wěn)定性進(jìn)行評(píng)價(jià)。 為了實(shí)現(xiàn)有效的拆卸序列規(guī)劃,本文提出一種基于免疫算法的拆卸序列規(guī)劃方法,針對(duì)拆卸序列規(guī)劃的需求,結(jié)合免疫算法的特點(diǎn),對(duì)現(xiàn)有算法進(jìn)行改進(jìn),用單親變異方法取代雙親交叉算子,以降低算法對(duì)初始種群的依賴;同時(shí)使用兩種方法提取疫苗,一種來自于經(jīng)驗(yàn)知識(shí),另一種提取于進(jìn)化過程中的種群,以提高算法的搜索速度;用精英代謝代替?zhèn)鹘y(tǒng)的新陳代謝,以提高算法的收斂性能。 最后,將改進(jìn)的免疫算法應(yīng)用于裝配體實(shí)例,通過試驗(yàn)的方法,分別從基準(zhǔn)件疫苗,疫苗提取間隔代數(shù),疫苗接種概率和精英代謝率等幾個(gè)方面對(duì)算法性能進(jìn)行驗(yàn)證,得到一個(gè)較佳的參數(shù)設(shè)置,以證明算法的收斂效率。同時(shí),對(duì)拆卸過程中,子裝配體穩(wěn)定性評(píng)估和零件穩(wěn)定性評(píng)估進(jìn)行比較,證明使用零件的穩(wěn)定性對(duì)拆卸過程進(jìn)行評(píng)估的方法比較直接、合理。
[Abstract]:Product disassembly is an important part of green manufacturing. The purpose of disassembly sequence planning is to find the disassembly path with the lowest cost and the shortest time. In order to make the evaluation of disassembly sequence more practical, the stability evaluation method of disassembly sequence is studied in this paper. In order to improve the stability of the disassembly process, reduce the disassembly time and reduce the disassembly cost, the fastener is regarded as an independent part in this study, and the role of the thread surface in the gravity support relationship is analyzed. Then the gravity support matrix is established according to the stepwise transfer relation of gravity. Then, the stability of disassembly sequence is evaluated by judging and calculating the number of unstable parts in subassembly according to the matrix. In order to realize effective disassembly sequence planning, this paper presents a disassembly sequence planning method based on immune algorithm. According to the requirement of disassembly sequence planning and the characteristics of immune algorithm, the existing algorithms are improved. The parent crossover operator is replaced by a single parent mutation method to reduce the dependence of the algorithm on the initial population, and two methods are used to extract the vaccine, one from empirical knowledge and the other from evolutionary populations. In order to improve the search speed of the algorithm and to replace the traditional metabolism with elite metabolism, the convergence performance of the algorithm can be improved. Finally, the improved immune algorithm is applied to the assembly case, and the performance of the algorithm is verified from several aspects, such as benchmark vaccine, vaccine extraction interval algebra, vaccination probability and elite metabolic rate, etc. A better parameter setting is obtained to prove the convergence efficiency of the algorithm. At the same time, the stability evaluation of subassemblies and parts is compared in the process of disassembly, which proves that the method of evaluating the disassembly process by using the stability of parts is more direct and reasonable.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH186;TP18

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