【摘要】：隨著全球化經(jīng)濟的發(fā)展市場競爭越來越激烈。在這樣的市場環(huán)境下,消費者個性化需求不斷增多,在資源、成本、交貨期等約束條件下,不僅對產(chǎn)品規(guī)格和質(zhì)量提出了嚴格的要求,同時對產(chǎn)品的生產(chǎn)效率和企業(yè)的生產(chǎn)方式提出了更高的挑戰(zhàn)。在此形勢下,企業(yè)之間的競爭已不僅僅是簡單的產(chǎn)品和生產(chǎn)技術(shù)的競爭,同時還包括管理技術(shù)的競爭。OKP (One-of-a-Kind Production)即單件生產(chǎn)模式正是在這一背景下應(yīng)運而生和并得到發(fā)展。OKP企業(yè)普遍存在的品種多、專業(yè)性強、生產(chǎn)成本高、效率低、產(chǎn)品過程質(zhì)量難以保證、生產(chǎn)過程中資源約束及其動態(tài)性的特征和難點。因此OKP企業(yè)的計劃調(diào)度問題更為復(fù)雜。本文以單件制蟻群算法造企業(yè)實際生產(chǎn)中存在的問題出發(fā),在分析單件制造企業(yè)的特點基礎(chǔ)上,總結(jié)了現(xiàn)行單件制造企業(yè)生產(chǎn)計劃體系的不足。根據(jù)不足之處加以改進,提出了一種適合于單件制造企業(yè)的,包含年度計劃、產(chǎn)品計劃、零部件及工序計劃三個層次的分層計劃體系。考慮到單件制造企業(yè)在產(chǎn)品計劃層次具有項目管理的特征,提出了一種改進的分層網(wǎng)絡(luò)計劃方法,用于編制單件制造企業(yè)產(chǎn)品生產(chǎn)計劃。該網(wǎng)絡(luò)計劃模型不僅可以在產(chǎn)品物料清單不完整的情況下,通過分層計劃得到面向生產(chǎn)單元和生產(chǎn)序列的兩層網(wǎng)絡(luò)計劃圖。而且結(jié)合關(guān)鍵鏈技術(shù)中有關(guān)設(shè)置緩沖時間的內(nèi)容,針對不同完工概率的非關(guān)鍵節(jié)點添加不同程度緩沖,以此提高網(wǎng)絡(luò)計劃的可行性,進行整體網(wǎng)絡(luò)調(diào)整,實現(xiàn)設(shè)計、生產(chǎn)準備、生產(chǎn)與裝配的協(xié)同。針對零部件及工序計劃層次存在的計劃調(diào)度問題,提出了一種新的改進蟻群算法,該算法在構(gòu)建工藝路線可變的析取圖模型的基礎(chǔ)上,將蟻群算法與遺傳算法相結(jié)合,同時優(yōu)化信息素更新規(guī)則和狀態(tài)轉(zhuǎn)移概率模型。以解決多產(chǎn)品并行生產(chǎn)以及產(chǎn)品生產(chǎn)工藝可變的生產(chǎn)調(diào)度問題。最后結(jié)合背景企業(yè)生產(chǎn)實踐進行驗證,借助調(diào)研企業(yè)的數(shù)據(jù)加以驗證所提方法的有效性,以期對相關(guān)的理論研究和實踐應(yīng)用有所借鑒。
[Abstract]:With the development of global economy, market competition is becoming more and more fierce. In such a market environment, the personalized demand of consumers is increasing. Under the constraints of resources, cost, delivery time and other constraints, not only strict requirements for product specifications and quality have been put forward. At the same time, it puts forward higher challenges to the production efficiency of products and the mode of production of enterprises. In this situation, the competition between enterprises is not only the competition of simple products and production technology, At the same time, it also includes the competition of management technology. OKP (One-of-a-Kind Production), that is, single-piece production mode, emerges as the times require and has been developed under this background. OKP enterprises generally exist in many varieties, strong professionalism, high production cost and low efficiency. The product process quality is difficult to guarantee, and the resource constraint and its dynamic characteristics and difficulties in the production process. Therefore, the planning and scheduling problem of OKP enterprises is more complex. Based on the problems existing in the actual production of single-piece ant colony algorithm, and on the basis of analyzing the characteristics of single-piece manufacturing enterprises, this paper summarizes the shortcomings of the current production planning system of single-piece manufacturing enterprises. According to the shortcomings, a hierarchical planning system, which is suitable for single-piece manufacturing enterprises, is proposed, which includes three levels: annual plan, product plan, spare parts and process plan. Considering that single-piece manufacturing enterprises have the characteristics of project management at the product planning level, an improved hierarchical network planning method is proposed to compile the product production plan of single-piece manufacturing enterprises. The network planning model can not only obtain the two-layer network plan diagram for production unit and production sequence through hierarchical planning under the condition that the product bill of materials is incomplete. Combined with the content of setting buffer time in critical chain technology, different degrees of buffering are added for non-critical nodes with different completion probabilities, so as to improve the feasibility of network planning, adjust the whole network, realize design and production preparation. Cooperation between production and assembly. A new improved ant colony algorithm is proposed to solve the planning and scheduling problem of parts and processes. On the basis of constructing the disjunctive graph model with variable process route, the algorithm combines ant colony algorithm with genetic algorithm. At the same time, the pheromone update rules and the state transition probability model are optimized. In order to solve the multi-product parallel production and production process variable production scheduling problem. Finally, combined with the production practice of background enterprises, the effectiveness of the proposed method is verified by the data of research enterprises, in order to draw lessons from the relevant theoretical research and practical application.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：F273
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本文編號：2475694