云制造资源虚拟化关键技术及应用

发布时间：2018-08-03 12:35

【摘要】：云制造作为一种新的面向服务的网络化协同制造模式,推动制造领域生产模式由以产品为中心向以服务为中心的快速变革。资源虚拟化是云制造实现的前提和基础,是提高整个云制造系统鲁棒性的关键。本文考虑云制造环境中分布制造企业间的异构制造资源与制造能力,研究云制造资源虚拟化的关键问题；分析制造领域资源与能力的关键特性,设计支持云制造服务内容与服务模式的资源虚拟化框架,提出面向制造资源与制造能力的虚拟化理论与方法,实现制造资源与制造能力的全局共享与流通。主要研究内容如下：(1)构建具有多粒度多视角的云制造资源虚拟化框架。针对云制造服务内容与服务模式,分析云制造资源在虚拟化过程中的存在形态、形态间的复杂关系、各种形态的复杂特性、以及资源使用的复杂性,构建多粒度多视角云制造资源虚拟化框架,提出框架的主要关键技术和运行机制,通过与已有框架的比较,分析所构建框架的特点。(2)设计云制造资源规范化描述模板并提出相应的语义填充方法。以云制造共享内容为对象,给出多粒度与多视角的定义,建立相应的形式化描述模型,提出求解资源粒度集的全序划分序列算法,用于实现多粒度转换与多视角交互；以制造能力为核心设计制造资源的概念模型,保证制造资源与制造能力间的松散耦合性；从资源与能力含义、应用模式、约束条件、上下文、云制造知识等角度分析影响制造资源与制造能力语义的关键因素,基于层次化方法组织相关元数据,建立制造资源与制造能力语义模型；基于建立的领域本体模型,提出制造资源与制造能力语义填充方法。(3)提出多粒度多目标虚拟资源生成算法。考虑资源应用中用户需求的多样性以及复杂制造任务间存在的多粒度与多角度间的差异,基于影响复杂任务分解的三个关键因素,将传统的资源功能相似度扩展到资源对复杂任务需求的贡献度、资源制造能力的协同等方面,分别设计面向属性、面向活动、面向过程的多粒度虚拟资源生成算法。考虑云平台资源应用所需的准确性与高效性,建立多目标虚拟资源生成模型,结合Fuzzy C-Means(FCM)算法的高效性与Gravitational search algorithm(GSA)的全局搜索能力,提出基于进化算法的虚拟资源生成算法,为云平台处理不同规模不同类型的资源应用提供多样选择。为对本文提出的资源虚拟化框架及方法的有效性进行验证,面向航空制造企业开发资源虚拟化应用原型系统。以直升机尾翼组件转子叶片的制造为例,实现了制造资源与制造能力的规范化描述和语义填充,并通过模拟仿真对提出的多粒度多目标虚拟资源算法进行验证。结果显示提出的模型与方法为云平台资源应用提供了充分全面的资源信息,并能保证资源与能力的语义一致性,扩大资源的使用范围,实现资源与能力的全局流通与共享。
[Abstract]:Cloud manufacturing, as a new service-oriented networked collaborative manufacturing model, promotes the rapid transformation of manufacturing model from product-centric to service-centric. Resource virtualization is the premise and foundation of cloud manufacturing and the key to improve the robustness of the whole cloud manufacturing system. In this paper, we consider heterogeneous manufacturing resources and manufacturing capabilities among distributed manufacturing enterprises in cloud manufacturing environment, study the key issues of cloud manufacturing resource virtualization, and analyze the key characteristics of manufacturing resources and capabilities. A resource virtualization framework supporting cloud manufacturing service content and service pattern is designed. A virtualization theory and method for manufacturing resources and manufacturing capabilities is proposed to realize the global sharing and circulation of manufacturing resources and manufacturing capabilities. The main research contents are as follows: (1) construct a cloud manufacturing resource virtualization framework with multi-granularity and multi-perspective. In view of cloud manufacturing service content and service mode, the paper analyzes the existing form of cloud manufacturing resources in the process of virtualization, the complex relationship between different forms, the complex characteristics of various forms, and the complexity of resource utilization. Build a multi-granularity and multi-perspective cloud manufacturing resource virtualization framework, propose the main key technology and running mechanism of the framework, and compare with the existing framework. The characteristics of the constructed framework are analyzed. (2) the cloud manufacturing resource normalization description template is designed and the corresponding semantic filling method is proposed. Taking the shared content of cloud manufacturing as the object, the definitions of multi-granularity and multi-perspective are given, the corresponding formal description model is established, and a total order partition sequence algorithm for solving resource granularity sets is proposed, which is used to realize multi-granularity transformation and multi-view interaction. The conceptual model of manufacturing resources is designed with manufacturing capability as the core to ensure the loose coupling between manufacturing resources and manufacturing capabilities, from the meaning of resources and capabilities, application patterns, constraints, context, The key factors affecting the semantics of manufacturing resources and manufacturing capabilities are analyzed from the point of view of cloud manufacturing knowledge. The semantic model of manufacturing resources and manufacturing capabilities is established based on the hierarchical method to organize the relevant metadata, and the domain ontology model is established. The semantic filling method of manufacturing resources and manufacturing capability is proposed. (3) A multi-granularity and multi-objective virtual resource generation algorithm is proposed. Considering the diversity of user requirements in resource applications and the differences between multi-granularity and multi-angle of complex manufacturing tasks, three key factors affecting the decomposition of complex tasks are considered. The traditional similarity of resource functions is extended to the contribution of resources to complex task requirements and collaboration of resource manufacturing capabilities. The algorithms of multi-granularity virtual resource generation are designed for attribute oriented, activity-oriented and process-oriented respectively. Considering the accuracy and efficiency of cloud platform resource application, a multi-objective virtual resource generation model is established. Combining the efficiency of Fuzzy C-Means (FCM) algorithm and the global search ability of Gravitational search algorithm (GSA), an evolutionary algorithm for virtual resource generation is proposed. It provides a variety of options for cloud platforms to handle resource applications of different sizes and types. In order to validate the framework and method of resource virtualization proposed in this paper, an application prototype system of resource virtualization is developed for aviation manufacturing enterprises. Taking the rotor blade manufacturing of helicopter tail component as an example, the standardized description and semantic filling of manufacturing resources and manufacturing capability are realized, and the proposed multi-granularity and multi-objective virtual resource algorithm is verified by simulation. The results show that the proposed model and method can provide full and comprehensive resource information for the application of cloud platform resources, ensure semantic consistency between resources and capabilities, expand the scope of use of resources, and realize the global circulation and sharing of resources and capabilities.
【学位授予单位】：东南大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TP393.09

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