本文關(guān)鍵詞： 無人化 齒輪 生產(chǎn)系統(tǒng) 智能調(diào)度 遺傳算法　出處：《浙江工業(yè)大學》2015年碩士論文　論文類型：學位論文

【摘要】：齒輪是各類機械儀表中廣泛應(yīng)用的傳動零件,齒輪制造業(yè)在我國制造業(yè)中占據(jù)著不可動搖的地位,然而國內(nèi)齒輪市場逐漸飽和,競爭環(huán)境日益激烈,企業(yè)只有不斷提高核心競爭力才能占據(jù)有利的市場地位,未來齒輪加工朝著自動化、智能化、無人化、綠色化發(fā)展是一種必然的趨勢。論文以SH公司為原型,旨在提出一種無人化齒輪生產(chǎn)布局方式以及相應(yīng)的智能調(diào)度方法。在查閱相關(guān)文獻的基礎(chǔ)上,論文對原型企業(yè)SH公司展開現(xiàn)場調(diào)查,重點了解產(chǎn)品類型及特點、生產(chǎn)布局及生產(chǎn)調(diào)度等情況,進行典型產(chǎn)品分析、工藝分析、單元分析及無人化設(shè)計,提出了一種無人化齒輪生產(chǎn)線布局方式。針對無人化生產(chǎn)中的智能調(diào)度問題,構(gòu)建了分批調(diào)度模型,并提出一種能夠同時求解批量劃分和排序優(yōu)化的改進遺傳算法,對種群初始化過程、交叉變異過程等進行改進,最后以文獻中數(shù)據(jù)為例進行算法測試,仿真驗證算法的可行性和有效性,得到調(diào)度初始解。然后在靜態(tài)調(diào)度基礎(chǔ)上深入考慮動態(tài)變化的車間環(huán)境,仿真分析了加工時間變動、機器故障和交貨期變動三種突發(fā)事件下的重調(diào)度機制。論文最后借助Visual Basic面向?qū)ο笳Z言、Acess數(shù)據(jù)庫和Matlab高級計算語言開發(fā)了無人化齒輪生產(chǎn)調(diào)度系統(tǒng)。面對逐漸變化的市場需求和制造模式,論文創(chuàng)新性地提出了一種無人化齒輪生產(chǎn)布局方式,為未來齒輪制造提供了一種設(shè)想,是齒輪生產(chǎn)理念上的一大進步。此外,論文提出的分批調(diào)度思想優(yōu)于經(jīng)典調(diào)度理念,在自動化程度越來越高的今天將會得到廣泛應(yīng)用,是制造企業(yè)改變傳統(tǒng)生產(chǎn)模式的一條新途徑。
[Abstract]:Gear is a kind of transmission parts widely used in mechanical instruments. Gear manufacturing occupies an unshakable position in China's manufacturing industry. However, the domestic gear market is gradually saturated, and the competition environment is becoming increasingly fierce. Enterprises can only continuously improve their core competitiveness to occupy a favorable market position, the future gear processing towards automation, intelligent, unmanned, green development is an inevitable trend. The purpose of this paper is to put forward a kind of production layout mode and corresponding intelligent scheduling method of unmanned gear. On the basis of consulting relevant documents, the paper carries out a field investigation on SH Company, a prototype company. Focus on product types and characteristics, production layout and production scheduling, typical product analysis, process analysis, unit analysis and non-human design. In this paper, a layout method of unmanmade gear production line is proposed, and a batch scheduling model is constructed to solve the problem of intelligent scheduling in no-man production. An improved genetic algorithm is proposed, which can solve batch partition and sorting optimization simultaneously. The process of population initialization and crossover mutation is improved. Finally, the algorithm is tested by taking the data in the literature as an example. Simulation verifies the feasibility and effectiveness of the algorithm and obtains the initial solution of scheduling. Then on the basis of static scheduling the dynamic environment of the workshop is considered deeply and the processing time variation is simulated and analyzed. The rescheduling mechanism of machine failure and change of due date is discussed. Finally, the object-oriented language of Visual Basic is used. Acess database and Matlab advanced computing language are used to develop an unmanned gear production scheduling system, which faces the changing market demand and manufacturing mode. This paper creatively puts forward a kind of unmanmade gear production layout mode, which provides a kind of assumption for the future gear manufacture, and is a great progress in the gear production idea. The idea of batch scheduling proposed in this paper is superior to the classical scheduling idea and will be widely used today when the degree of automation is higher and higher. It is a new way for manufacturing enterprises to change the traditional production mode.
【學位授予單位】：浙江工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TH132.41;TH186

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本文編號：1446246