【作者】 张勇；

【导师】 张宏文； 齐伟；

【作者基本信息】 石河子大学 ， 工程硕士（专业学位）， 2019， 硕士

【摘要】 为应对新工业革命下的国际竞争,全球制造业正向智能化、信息化、服务化转型。全球制造业已然形成合作与竞争共存态势,实现企业与行业间的协同合作已成为必然趋势。农业机械作为装备制造业的重要组成部分,其服务化转型必不可缺。本文通过对新疆中小型农业机械制造企业进行了调研,并针对其存在的问题,提出将农业机械制造业同云制造技术相结合的构想,以实现农业机械制造业的服务化转型,将农业机械制造资源封装为服务,建立一种面向农业机械的云制造服务平台,从而提高农机制造资源的使用效率。该研究的关键技术如下:(1)建立农业机械云制造服务平台的整体架构通过深入分析农业机械特点,分析农业机械制造企业的需求,基于云制造的基本概念模型,明确农业机械云制造服务平台的服务对象。提出农机云制造服务平台的整体架构,包括物理资源层、服务资源层、核心驱动层、功能模块层、用户层以及外部的支撑环境。根据上述架构,确立平台各个功能模块与基本运行模式,为平台搭建提供理论支撑。(2)农业机械云制造资源的分类与服务需求规范准确描述结合农业机械制造资源特征,提出了符合农业机械制造资源的分类方法,并建立资源分类体系结构,将平台内资源划分为6部分:制造硬件资源、制造软件资源、人力资源、信息资源、知识资源和其它资源。并建立了资源服务属性集合和需求信息属性集合,以水平摘锭式采棉机采摘头性能测试平台为例,实现复杂、异构的农业机械资源服务与需求的规范准确描述。(3)建立农业机械云制造服务模型与搜索匹配机制基于本体思想,分析了平台本体构建过程,通过斯坦福大学开发的本体建模软件Protégé建立平台资源本体模型,以水平摘锭式采棉机采摘头综合性能检测服务为例,建立了资源服务化描述本体模型。构建本体模型后,基于本体知识深度理论,得出资源服务的搜索匹配机制与流程。(4)农业机械云制造资源访问控制机制及安全性研究通过访问控制理论分析,结合本平台需求,建立了基于角色(RBAC)的平台访问控制模型,实现用户权限的合理分配,确保平台的运行安全可靠。最后,结合上述理论研究与实例分析,搭建出农业机械云制造服务平台,并对系统功能界面及部分数据库进行了设计。为农业机械制造资源的使用效率的提高以及促进农业机械制造业的快速发展提供了一个有效途径。更多还原

【Abstract】 In response to the international competition under the new industrial revolution,the global manufacturing industry is transforming into intelligence,information and service.The global manufacturing industry has formed a coexistence of cooperation and competition,and achieving synergy between enterprises and industries has become an inevitable trend.As an important part of the equipment manufacturing industry,agricultural machinery was indispensable for its service transformation.This paper investigated the small and medium-sized agricultural machinery manufacturing enterprises in Xinjiang,and proposed the concept of combining agricultural machinery manufacturing with cloud manufacturing technology in order to realize the service transformation of agricultural machinery manufacturing and the agricultural machinery.Manufacturing resources were packaged as services to establish a cloud manufacturing service platform for agricultural machinery,thereby improving the efficiency of the use of agricultural machinery manufacturing resources.The key technologies of the study were as follows:(1)Established the overall structure of the agricultural machinery cloud manufacturing service platformThrough in-depth analysis of the characteristics of agricultural machinery,analysis of the needs of agricultural machinery manufacturing enterprises,based on the basic conceptual model of cloud manufacturing,the service objects of the agricultural machinery cloud manufacturing service platform were clarified.The overall architecture of the agricultural machinery cloud manufacturing service platform was proposed,including physical resource layer,service resource layer,core driver layer,functional module layer,user layer and external supporting environment.According to the above structure,each functional module and basic operation mode of the platform are established,which provides theoretical support for platform construction.(2)Classification of agricultural machinery cloud manufacturing resources and accurate description of service demand specificationsCombined with the characteristics of agricultural machinery manufacturing resources,this paper proposes a classification method in line with agricultural machinery manufacturing resources,and establishes a resource classification system structure,which divides the resources in the platform into six parts: manufacturing hardware resources,manufacturing software resources,human resources,information resources,and knowledge resources.And other resources.The resource service attribute set and the demand information attribute set are established,and the horizontal picking type picking machine picking head performance testing platform was taken as an example to realize the accurate and standardized description of the complex and heterogeneous agricultural machinery resource service and demand.(3)Establishing agricultural machinery cloud manufacturing service model and search matching mechanismBased on the ontology idea,the platform ontology construction process was analyzed.The platform resource ontology model was established by the ontology modeling software Protégé developed by Stanford University.The comprehensive performance detection service of the horizontal picking picker picking head was taken as an example to establish the resource service description.After constructing the ontology model,based on the ontology knowledge depth theory,the search matching mechanism and process of resource service are obtained.(4)Agricultural machinery cloud manufacturing resource access control mechanism and security researchBased on the analysis of access control theory and the requirements of this platform,a role-based(RBAC)platform access control model was established to realize the reasonable allocation of user rights and ensure the safe and reliable operation of the platform.Finally,combined with the above theoretical research and case analysis,the agricultural machinery cloud manufacturing service platform was built,and the system function interface and some databases were designed.It provides an effective way to improve the efficiency of the use of agricultural machinery manufacturing resources and promote the rapid development of agricultural machinery manufacturing.更多还原