面向用户个性化需求的云制造服务配置方法研究
发布时间：2018-09-11 16:49
【摘要】：满足用户的个性化需求是现代制造企业面临的主要挑战,也是它们追求的重要目标。然而,传统网络化制造模式侧重于制造企业之间针对特定记产品或项目的业务协同,在满足用户个性化需求方面存在局限性。新兴网络化制造模式—云制造,融合了现代信息技术和传统制造技术,在满足用户的个性化需求、实现制造资源与服务的完全共享和优化配置方面具有明显的优势。本论文围绕用户个性化需求,研究云制造模式下制造服务的匹配与组合优化问题,具有重要的理论意义和应用价值。主要的研究内容包括:构建了面向用户个性化需求的云制造服务配置框架。针对用户的个性化需求,采用云制造服务相似度进行形式化表示。引入层次分析法、K-means聚类算法和变精度粗糙集,综合评价云制造服务相似度,量化用户的个性化需求。将云制造服务相似度扩展到云制造服务描述模型中,充分体现用户的个性化需求。设计了面向用户个性化需求的云制造服务匹配算法。基于QoS属性相似度,提出了云制造服务匹配算法和面向用户个性化需求的云制造服务保留算法。精选并修正候选云制造服务集合,降低了组合优化过程解空间,提高了组合效率,在保证用户高效获取并使用云制造服务的同时,将最接近用户期望的云制造服务提供给用户。建立了面向用户个性化需求的云制造服务组合优化模型并求解。在分析云制造服务组合优化过程的基础上,构建了面向用户个性化需求的云制造服务组合优化模型。采用矩阵整数编码和块交叉策略对遗传算法进行改进,并将其用于云制造服务组合优化模型求解。通过云制造服务相似度改变染色体适应度值,验证模型和算法的合理性和有效性。设计并实现了面向用用户个性化需求的云制造服务配置原型系统。对系统整体框架和功能模块进行了分析,利用支持C#编程语言的Visual Studio开发水平台以及SQL Server数据库,设计并开发了面向用户个性化需求的云制造服务配置原型系统,验证了本论文所研究模型和方法的可行性。
[Abstract]:To meet the individual needs of users is the main challenge faced by modern manufacturing enterprises, and it is also an important goal that they pursue. However, the traditional networked manufacturing model focuses on the business collaboration between manufacturing enterprises for specific products or projects, which has limitations in meeting the individual needs of users. Cloud manufacturing, a new networked manufacturing model, combines modern information technology with traditional manufacturing technology. It has obvious advantages in satisfying the individual needs of users, realizing the complete sharing of manufacturing resources and services and optimizing the configuration of manufacturing resources and services. This paper focuses on the personalized requirements of users, and studies the matching and composition optimization of manufacturing services in cloud manufacturing mode, which has important theoretical significance and application value. The main research contents are as follows: the configuration framework of cloud manufacturing service is constructed. According to the personalized requirements of users, the similarity of cloud manufacturing services is formalized. The K-means clustering algorithm and variable precision rough set are introduced to evaluate the similarity of cloud manufacturing services and to quantify the personalized requirements of users. The similarity of cloud manufacturing services is extended to the cloud manufacturing service description model to fully reflect the personalized needs of users. A cloud manufacturing service matching algorithm is designed for user personalized requirements. Based on the similarity of QoS attributes, a cloud manufacturing service matching algorithm and a cloud manufacturing service retention algorithm are proposed. The set of candidate cloud manufacturing services is selected and corrected, which reduces the solution space of composition optimization process and improves the composition efficiency. The cloud manufacturing service that is closest to the user's expectation is provided to the user at the same time as the user can obtain and use the cloud manufacturing service efficiently. A cloud manufacturing service composition optimization model for personalized user requirements is established and solved. Based on the analysis of the optimization process of cloud manufacturing service composition, a cloud manufacturing service composition optimization model is constructed to meet the needs of users. The genetic algorithm is improved by matrix integer coding and block crossover strategy, and it is used to solve the optimization model of cloud manufacturing service composition. The validity and rationality of the model and algorithm are verified by changing the chromosome fitness by cloud manufacturing service similarity. A prototype system of cloud manufacturing service configuration is designed and implemented. The whole frame and function module of the system are analyzed. The prototype system of cloud manufacturing service configuration is designed and developed based on Visual Studio platform and SQL Server database, which supports C # programming language. The feasibility of the model and method studied in this paper is verified.
【学位授予单位】：西安理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.09
本文编号：2237270
[Abstract]:To meet the individual needs of users is the main challenge faced by modern manufacturing enterprises, and it is also an important goal that they pursue. However, the traditional networked manufacturing model focuses on the business collaboration between manufacturing enterprises for specific products or projects, which has limitations in meeting the individual needs of users. Cloud manufacturing, a new networked manufacturing model, combines modern information technology with traditional manufacturing technology. It has obvious advantages in satisfying the individual needs of users, realizing the complete sharing of manufacturing resources and services and optimizing the configuration of manufacturing resources and services. This paper focuses on the personalized requirements of users, and studies the matching and composition optimization of manufacturing services in cloud manufacturing mode, which has important theoretical significance and application value. The main research contents are as follows: the configuration framework of cloud manufacturing service is constructed. According to the personalized requirements of users, the similarity of cloud manufacturing services is formalized. The K-means clustering algorithm and variable precision rough set are introduced to evaluate the similarity of cloud manufacturing services and to quantify the personalized requirements of users. The similarity of cloud manufacturing services is extended to the cloud manufacturing service description model to fully reflect the personalized needs of users. A cloud manufacturing service matching algorithm is designed for user personalized requirements. Based on the similarity of QoS attributes, a cloud manufacturing service matching algorithm and a cloud manufacturing service retention algorithm are proposed. The set of candidate cloud manufacturing services is selected and corrected, which reduces the solution space of composition optimization process and improves the composition efficiency. The cloud manufacturing service that is closest to the user's expectation is provided to the user at the same time as the user can obtain and use the cloud manufacturing service efficiently. A cloud manufacturing service composition optimization model for personalized user requirements is established and solved. Based on the analysis of the optimization process of cloud manufacturing service composition, a cloud manufacturing service composition optimization model is constructed to meet the needs of users. The genetic algorithm is improved by matrix integer coding and block crossover strategy, and it is used to solve the optimization model of cloud manufacturing service composition. The validity and rationality of the model and algorithm are verified by changing the chromosome fitness by cloud manufacturing service similarity. A prototype system of cloud manufacturing service configuration is designed and implemented. The whole frame and function module of the system are analyzed. The prototype system of cloud manufacturing service configuration is designed and developed based on Visual Studio platform and SQL Server database, which supports C # programming language. The feasibility of the model and method studied in this paper is verified.
【学位授予单位】：西安理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.09
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