本文選題：云制造 + 制造資源��； 參考：《西安理工大學》2017年碩士論文

【摘要】：近年來,云制造等先進網絡化制造模式的出現(xiàn),推動著制造業(yè)向全球化、一體化的方向發(fā)展。在云模式下,制造資源的優(yōu)化配置問題是實現(xiàn)“制造即服務”理念的關鍵。本文研究制造資源的服務化封裝、聚類分析以及優(yōu)化配置等,對于提升云制造的服務效率和大規(guī)模普及具有重要的現(xiàn)實意義。建立制造資源服務化描述模型與虛擬化封裝機制。針對制造資源海量性、異構性及獨立性的特征,基于面向對象的思維構建制造資源服務化描述模型,對模型中各模塊的功能和意義進行討論。針對資源結構和語義等驗證問題,建立一種基于Web的資源虛擬化封裝框架。對制造資源進行模糊聚類研究。針對制造資源間關聯(lián)性差、不利于實現(xiàn)高效檢索和優(yōu)化配置的問題,分別運用基于模糊相似矩陣的直接聚類法和FCM聚類算法對某一批制造資源進行聚類分析,對算法中的屬性權值設定、初始聚類中心的選取等問題進行討論和改進,提出了一種將兩種聚類方法進行結合運用的新算法。改進制造資源優(yōu)化配置算法。針對云模式下制造資源的優(yōu)化配置問題,建立相關問題的評價函數模型,對傳統(tǒng)遺傳算法進行自適應改進,采用混合輪盤賭法和錦標賽法的選取機制提高了算法的尋優(yōu)效率;采用自適應交叉率和變異率的方法保證了算法的多樣性和收斂性,賦予變異過程正反饋特性,提高了算法的穩(wěn)定性和求解質量。最后以實例驗證了算法改進的有效性,并得出了最優(yōu)的資源配置方案。設計并實現(xiàn)了制造資源優(yōu)化配置原型系統(tǒng)。根據制造資源配置研究中的諸多需求,以云制造服務平臺為研究主體,對平臺的總體結構、各模塊功能、理論和技術等進行設計與開發(fā),驗證了本文所研究理論與方法的可行性與有效性。
[Abstract]:In recent years, the emergence of advanced networked manufacturing model such as cloud manufacturing promotes the development of globalization and integration of manufacturing industry. In the cloud mode, the optimal allocation of manufacturing resources is the key to realize the concept of "manufacturing as a service". In this paper, the service encapsulation of manufacturing resources, clustering analysis and optimization of configuration are studied, which is of great practical significance for improving the service efficiency of cloud manufacturing and popularizing it on a large scale. Establish manufacturing resource service description model and virtualization encapsulation mechanism. Aiming at the characteristics of magnanimity, heterogeneity and independence of manufacturing resources, a service-oriented description model of manufacturing resources is constructed based on object-oriented thinking, and the functions and significance of each module in the model are discussed. A resource virtualization encapsulation framework based on Web is proposed for resource structure and semantics verification. Research on fuzzy clustering of manufacturing resources. Aiming at the problem of poor correlation among manufacturing resources, which is not conducive to efficient retrieval and optimal configuration, the direct clustering method based on fuzzy similarity matrix and FCM clustering algorithm are applied to cluster analysis of a batch of manufacturing resources. This paper discusses and improves the setting of attribute weight and the selection of initial clustering center in the algorithm, and proposes a new algorithm which combines the two clustering methods. Improve the optimal allocation algorithm of manufacturing resources. Aiming at the optimal allocation of manufacturing resources in cloud mode, the evaluation function model of related problems is established, and the traditional genetic algorithm is improved adaptively. The selection mechanism of mixed roulette method and tournament method is adopted to improve the efficiency of the algorithm. The adaptive crossover rate and mutation rate are used to ensure the diversity and convergence of the algorithm, and the positive feedback characteristics of the mutation process are given to improve the stability and quality of the algorithm. Finally, an example is given to verify the effectiveness of the improved algorithm, and the optimal resource allocation scheme is obtained. A prototype system for optimal configuration of manufacturing resources is designed and implemented. According to many requirements in the research of manufacturing resource allocation, this paper designs and develops the overall structure, function of each module, theory and technology of the platform, taking the cloud manufacturing service platform as the main body. The feasibility and validity of the theory and method studied in this paper are verified.
【學位授予單位】：西安理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP18;TP393.09

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