本文選題：裝配序列規(guī)劃（ASP）　切入點：裝配線平衡（ALB）　出處：《上海交通大學》2014年博士論文　論文類型：學位論文

【摘要】：船舶制造中的裝配工作一般耗時最久、需要的關鍵資源最多。其中，分段裝配工時大概占船體裝配總工時的45%左右，分段裝配成本在船體裝配總成本中所占的比例更是高達50%以上。因此，研究船體分段裝配過程中的最優(yōu)化問題，對縮短船體建造周期、減少裝配成本以及提高裝配質量具有重大意義。 本文以船體平面分段裝配為對象，研究了分段裝配序列規(guī)劃與裝配線平衡方法，為解決復雜產品的裝配最優(yōu)化問題提供決策依據(jù)。研究工作主要包括以下內容： （1）基于實例推理（CBR）與基于幾何約束推理相結合的平面分段裝配序列規(guī)劃方法。船體分段結構復雜，所包含的零部件眾多，給可行裝配序列推理造成很大的困難。另外，在結構組成上，組成分段的零部件之間沒有嚴格的幾何約束關系，滿足幾何約束的可行序列數(shù)量較大，不利于序列的評價及優(yōu)選。本文利用基于實例推理的方法，參照與裝配問題最相似實例的裝配順序，生成裝配問題的初始優(yōu)先約束關系，然后結合基于約束的推理，生成裝配體完整的裝配序列，并利用遺傳算法進行裝配序列選優(yōu)。論文用具體加工算例驗證了該方法的有效性。 （2）批量型裝配線平衡問題建模及求解方法研究。在分段部件裝配過程中，各部件不僅要滿足加工時間、平臺占用面積等的約束，還需符合一定的完工優(yōu)先關系。以裝配線勞動生產率最大化及工作站負荷均衡為優(yōu)化目標，在合理假設的基礎上，，建立批量型裝配線平衡問題的數(shù)學模型。本文利用文化基因算法對問題進行求解，尋找最優(yōu)的分段部件裝配計劃。通過染色體的解碼過程實現(xiàn)任務的智能分批，設計了序列自動調整算子，保證生成的最優(yōu)解符合優(yōu)先關系約束。另外，在算法框架中加入局部搜索算子，加快了算法的求解過程。最后通過分段部件裝配的實際算例驗證算法的有效性。該問題的解決，對于具有優(yōu)先關系約束的任務割分或排序問題的求解具有參考價值。 （3）混合型裝配線平衡問題建模及求解方法研究。船體平面分段裝配流水線平衡的目的是尋找最優(yōu)的加工任務排序，實現(xiàn)總任務的生產周期最短、任務拖期數(shù)量最少以及工作站負荷均衡等目標。為了獲取該多目標優(yōu)化問題的Pareto最優(yōu)解，本文在合理假設的基礎上，構建了混合型裝配線平衡問題的數(shù)學模型。提出了一種改進的多目標遺傳算法，設計了個體適應值的分配策略及Pareto解集更新機制，使得算法能夠快速地獲取滿足優(yōu)化目標的多組非劣解。最后通過船體平面分段裝配實例驗證了算法的有效性�；旌涎b配線平衡問題的解決，可以為多目標組合優(yōu)化問題非劣解的求取提供一定的參照。 （4）產品裝配序列規(guī)劃及裝配線平衡系統(tǒng)集成方法研究。研究了序列規(guī)劃及裝配線平衡的關系，構建了船體平面分段裝配最優(yōu)化應用系統(tǒng)，并以國內某造船廠平面分段裝配的實際加工數(shù)據(jù)對系統(tǒng)進行了驗證。 綜上，本文給出了一整套船體平面分段裝配過程最優(yōu)化的解決方法，對企業(yè)縮短分段裝配工時、節(jié)約生產成本提供了決策支持。
[Abstract]:The general assembly work of Shipbuilding's longest and most critical resource needs. Among them, sub assembly time probably accounted for about 45% of the total hull assembly, sub assembly cost in hull assembly in the total cost of the proportion is up to more than 50%. Therefore, optimization research on hull assembly process. To shorten the construction cycle of the hull, reduce assembly cost and is of great significance to improve the quality of assembly.
In this paper, segmented assembly sequence planning and assembly line balancing method are studied based on segmented assembly of hull plane, which provides decision basis for solving assembly optimization problems of complex products.
(1) based on case-based reasoning (CBR) plane combined with geometric constraints based on piecewise assembly sequence planning method. Hull structure is complex, contains many components, causing great difficulties for feasible assembly sequence reasoning. In addition, in structure, no strict geometric constraint relationship between the composition of some parts meet, the geometric constraint of feasible sequence number is large, is not conducive to the sequence evaluation and optimization. This paper uses the method of case based reasoning, assembly sequence and assembly problems referring to the similar case, the initial generation of assembly precedence relationship problems, and then combined with constraint based reasoning, generating assembly assembly sequence integrity, and assembly sequence optimization by genetic algorithm. The specific processing examples verify the effectiveness of the method.
(2) batch type assembly line balancing problem modeling and solving methods in the study. The segmentation of each component in the assembly process, not only to meet the processing time, the platform occupied area and other constraints, also need to meet certain priority to the assembly line. The completion of labor productivity maximization and work station load balancing as the optimization goal, based on reasonable assumptions, establish mathematical model of batch type assembly line balancing problem. This paper uses the memetic algorithm to solve the problem, finding the optimal segment assembly plan. The task of intelligent batch through the decoding process of chromosomes, designed to automatically adjust the sequence of operators, ensure that the generated optimal solution with precedence constraints. In addition, join a local search operator in the algorithm frame, to speed up the algorithm. Finally, through the actual effectiveness of the segmentation assembly example verification algorithm. The problem The solution is of reference value for solving the problem of task cutting or sorting with priority relation constraints.
(3) research on Modeling and solving method of mixed model assembly line balancing problem. Hull plane block assembly line balance is objective to find the optimal sorting processing tasks, achieve total task production cycle short, the minimum number of tardy tasks and workstation load balancing goals. To obtain the Pareto optimal solutions of multi-objective optimization problem in this paper, on the basis of rational hypothesis, constructs a mathematical model for mixed model assembly line balancing problem. This paper proposed an improved multi-objective genetic algorithm, the design of individual adaptation strategies and Pareto value of solution set update mechanism, the algorithm can quickly obtain a satisfying non inferior solution. Finally, the optimization goal the plane through the hull block assembly examples verify the effectiveness of the algorithm. To solve the mixed model assembly line balancing problem, for multi-objective optimization non dominated solutions for providing certain Reference.
(4) research on system integration method of product assembly sequence planning and assembly line balance. To study the relationship between sequence planning and assembly line balancing, planar hull block assembly optimization application system is constructed, the verification of the system data and the actual processing by a domestic shipyard plane block assembly.
In conclusion, this paper gives a complete solution to the optimization of hull plane sectional assembly process, which provides decision support for shortening segmental assembly time and saving production cost.

【學位授予單位】：上海交通大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：U671

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