發(fā)布時間：2018-05-06 12:57

  本文選題：公差分配 + 質(zhì)量損失��； 參考：《電子科技大學》2012年碩士論文

【摘要】：公差是連接產(chǎn)品設計與制造的橋梁,公差設計直接影響產(chǎn)品的制造成本大小和質(zhì)量的優(yōu)劣程度。目前對公差的研究主要側(cè)重于對成本和質(zhì)量的控制,對公差設計過程的穩(wěn)健性考慮較少。論文首先分析了公差分配的關(guān)鍵問題,接著分別從敏感穩(wěn)健性和可行穩(wěn)健性兩個方面著手,對并行公差的穩(wěn)健設計方法進行研究。 一般情況下要獲得更好的產(chǎn)品性能需要更小的公差值,但是這樣會導致成本的提高。公差的敏感穩(wěn)健設計方法就是通過名義尺寸值的調(diào)整使產(chǎn)品性能對公差的敏感度變小,從而有效地控制成本。在實際的加工過程中機器的加工能力會在一定的小范圍內(nèi)波動,造成約束條件的改變,有可能使傳統(tǒng)的優(yōu)化解成為不可行解。針對這一問題,論文提出了公差的可行穩(wěn)健性設計方法,建立了可行穩(wěn)健性的設計模型,并應用最小靈敏域方法對模型進行求解,得到了可行穩(wěn)健優(yōu)化解。 鑒于傳統(tǒng)遺傳算法搜索性能較弱的問題,采用了免疫遺傳算法對建立的敏感穩(wěn)健數(shù)學模型進行了優(yōu)化分配。其次,論文在分析產(chǎn)品的質(zhì)量損失函數(shù)問題的基礎上,針對實際產(chǎn)品難以獲得準確的質(zhì)量損失系數(shù)的這一難點,提出建立雙目標優(yōu)化數(shù)學模型的方法,將制造成本與質(zhì)量損失分別作為設計的目標,擴大了質(zhì)量損失的使用范圍,采用多目標優(yōu)化算法：NSGA-Ⅱ來求解,得到的多個解能夠滿足市場多樣化的需求。 本文的最后通過單向離合器和活塞-氣缸裝配的并行設計實例驗證了所提出理論和方法的有效性,并對公差設計的未來研究工作進行了有益的探討。
[Abstract]:Tolerance is a bridge connecting product design and manufacture. Tolerance design directly affects the manufacturing cost and quality of products. At present, the research on tolerance mainly focuses on the control of cost and quality, but less on the robustness of tolerance design process. In this paper, the key problem of tolerance allocation is analyzed, and then the robust design method of parallel tolerance is studied from two aspects: sensitive robustness and feasible robustness. Generally, smaller tolerances are required to achieve better product performance, but this can lead to higher costs. The sensitive robust design method of tolerance is to reduce the sensitivity of product performance to tolerance by adjusting nominal dimension value, so as to effectively control the cost. In the actual processing process, the machining ability of the machine will fluctuate in a certain range, resulting in the change of the constraint conditions, which may make the traditional optimization solution become the infeasible solution. In order to solve this problem, the feasible robust design method of tolerance is proposed, and the design model of feasible robustness is established. The model is solved by using the minimum sensitivity domain method, and the feasible robust optimal solution is obtained. In view of the weak search performance of the traditional genetic algorithm, the immune genetic algorithm is used to optimize the allocation of the sensitive and robust mathematical model. Secondly, on the basis of analyzing the problem of product quality loss function, aiming at the difficulty of obtaining accurate quality loss coefficient in actual product, the paper puts forward a method of establishing double objective optimization mathematical model. The manufacturing cost and the quality loss are taken as the target of the design, and the use range of the quality loss is enlarged, and the multi-objective optimization algorithm: NSGA- 鈪，

本文編號：1852401