云制造环境下机床装备资源优化配置方法及技术研究

发布时间：2018-06-01 07:40

本文选题：机床装备 + 云制造　；参考：《重庆大学》2015年博士论文

【摘要】：机床装备制造企业、应用企业及其服务企业量大面广,是我国工业经济的重要组成部分。随着云计算、大数据、物联网及移动互联网等信息技术与先进制造技术的深度融合应用,网络化、智能化、绿色化、服务化等已成为机床装备行业的重要发展方向。广大机床装备制造企业在应对日益激烈的全球化竞争过程中,正逐步从传统机床装备制造商、销售商向智能生产线整体解决方案提供商、装备全生命周期服务商方向转型;机床装备应用企业在优化精益生产能力、快速响应市场需求的过程中,对机床装备网络化集成运行、加工过程实时监控与诊断等基于网络的协同制造服务提出了迫切的需求。如何创新制造服务模式,实现企业资源的充分共享和跨域协作,以支持广大机床装备企业开展生产性服务业务,已成为当前先进制造领域探索和研究的重要科学命题之一。云制造——一种基于泛在网络的智慧制造模式,可支持分散资源的集中管理,集中资源的按需服务,其“制造即服务”的核心思想为以上问题提供了崭新的解决思路。论文在借鉴国内外相关研究成果的基础上,针对机床装备企业间的资源共享和业务协同需求,结合云制造的服务理念,提出一种机床装备资源优化配置云服务平台,并对其所涉及的部分关键技术进行一定的探索和研究。首先,分析了传统机床装备企业的转型发展需求,结合云制造相关理论,提出了一种可支持机床装备资源语义描述、服务封装、搜索匹配、优化配置与运行监控的机床装备资源优化配置云服务平台,论述了平台实现思路,研究了平台的体系结构、运行模式和商业模式,并建立了支持平台实现的关键技术体系。然后,根据平台总体框架,对其涉及的部分关键技术进行了探索和研究,包括:①针对云制造环境下机床装备资源具有异质异构、动态演化、高度自治等特点及规范化描述需求,研究了一种基于Web服务建模本体(Web Service Modeling Ontology,WSMO)的机床装备资源语义描述与封装方法,包括:提出了一种基于WSMO的机床装备资源语义描述与封装实现框架;研究了机床装备资源元数据本体表示方法和机床装备资源服务化封装技术,并结合一机床装备资源实例验证了该方法的可行性。②针对云制造环境下机床装备资源种类多样、功能相似、信息动态变化等特点导致搜索匹配效率和精度不高的问题,以形成资源优化配置可行解域为目标,研究了一种基于语义的机床装备资源供需匹配方法。提出了一种包括基本信息匹配、IOPE参数匹配、QoS属性匹配和综合匹配的机床装备资源分级匹配实现框架,研究了各匹配阶段的量化方法及实现算法,并结合实例验证该方法的适用性。③针对云制造环境下服务制约因素多、制造环境变化快、资源配置评价难度较大等特点,为获得资源优化配置最优解,提出了包括服务时间(T)、服务成本(C)、服务质量(Q)、服务知识(K)、服务环境(E)、服务可靠性(R)、服务容错性(Ft)和综合满意度(Sa)等八维分量的机床装备资源优化配置评价指标体系,构建了一种基于Multi-Agent的机床装备资源配置评价模型,设计了基于混合粒子群的模型求解算法,并结合一实例验证了该配置评价模型和求解算法的有效性。最后,结合国家863/CIMS主题资助项目“中小企业云制造服务平台共性关键技术研究”的实施,设计并开发了一套机床装备资源优化配置云服务平台原型系统,并在重庆市某机床装备企业中进行了初步应用验证,取得了良好的应用效果。
[Abstract]:Machine tools and equipment manufacturing enterprises, application enterprises and their service enterprises are an important part of China's industrial economy. With the deep integration of information technology and advanced manufacturing technology, such as cloud computing, large data, Internet of things and mobile Internet, network, intelligence, green, service and so on have become the emphasis of machine tools and equipment industries. In order to develop the direction, the large machine tool and equipment manufacturing enterprises are gradually changing from the traditional machine tool equipment manufacturer, the seller to the overall solution provider of the intelligent production line and the whole life cycle service provider in the process of responding to the increasingly fierce global competition; the machine tool and equipment enterprises are optimizing the lean production capacity and responding quickly. In the process of market demand, there is an urgent need for the networked integrated operation of machine tool equipment, the real-time monitoring and diagnosis of processing process and the cooperative manufacturing service based on the network. How to innovate the manufacturing service mode, realize the full sharing of enterprise resources and cross domain cooperation, so as to support the production service business of the large machine tools and equipment enterprises, It has become one of the important scientific propositions in the field of advanced manufacturing field. Cloud manufacturing, an intelligent manufacturing model based on ubiquitous network, can support centralized management of scattered resources and focus on the demand for resources. The core idea of "manufacturing as a service" provides a new solution to the problem. On the basis of the relevant research results both at home and abroad, in view of the resource sharing and business synergy demand among the machine tools and equipment enterprises and the service concept of cloud manufacturing, a cloud service platform for machine tool resources optimization is proposed, and some key technologies involved are explored and studied. First, the traditional machine tool assembly is analyzed. In order to meet the needs of enterprises' transformation and development, combined with the theory of cloud manufacturing, a cloud service platform which can support the semantic description of machine tool resources, service encapsulation, search and match, optimization configuration and operation monitoring is proposed. The implementation ideas of the platform are discussed, and the system structure, operation mode and business model of the platform are discussed. And then, the key technology system for supporting platform implementation is established. Then, according to the overall framework of the platform, some key technologies involved are explored and studied, including: (1) the characteristics of heterogeneous, dynamic evolution, high self governance and standardized description requirements for machine tool resources under the cloud manufacturing environment, and a research based on We B service modeling Ontology (Web Service Modeling Ontology, WSMO) for the semantic description and encapsulation of machine tool resources, including a framework for semantic description and encapsulation of machine tool resources based on WSMO, the ontology representation method of machine tool resource metadata and the service encapsulation technology of machine tool resources, and the integration of machine tools and equipment resources. An example of machine tool resources proves the feasibility of this method. Secondly, in view of the variety of machine tool resources, similar functions and dynamic changes of information in the cloud manufacturing environment, the search matching efficiency and precision are not high, in order to form the feasible solution domain of the resource optimization configuration, a semantic based machine tool equipment capital is studied. Source supply and demand matching method. A framework for classification and matching of machine tool resources including basic information matching, IOPE parameter matching, QoS attribute matching and comprehensive matching is proposed. The quantization methods and implementation algorithms of each matching phase are studied, and the applicability of the method is verified by an example. Thirdly, the service constraints in cloud manufacturing environment are verified. In order to obtain optimal solution for optimal allocation of resources, the advantages of eight dimensions of eight dimension components, including service time (C), service quality (Q), service knowledge (K), service environment (E), service reliability (R), service fault tolerance (Ft) and comprehensive satisfaction (Sa), are proposed. In this paper, the evaluation model of machine tool resources based on Multi-Agent is constructed, and a model solving algorithm based on mixed particle swarm is designed, and the effectiveness of the allocation evaluation model and the algorithm is verified by an example. Finally, combined with the national 863/CIMS theme subsidized project "the cloud manufacturing of small and medium enterprises" The implementation of the research on the common key technology of the service platform, designed and developed a set of prototype system for the optimization configuration of the machine tool resources, and carried out preliminary application and verification in a machine tool enterprise in Chongqing, and achieved good application results.
【学位授予单位】：重庆大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TG502

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