云制造环境下基于离散Markov跳变系统的机床装备资源动态优选方法

针对云制造环境下加工任务执行过程中机床装备资源易受紧急插单、加工质量异常、设备运行故障等高频随机扰动影响,致使产品加工服务质量(QoS)不能满足客户个性化需求的问题,提出一种基于离散Markov跳变系统的机床装备资源动态优化选择方法.首先,结合云制造服务运行特点,构建了云制造环境下面向加工任务执行过程的服务质量动态演化...     

云制造——面向服务的网络化制造新模式

为求解更加复杂的制造问题和开展更大规模的协同制造,分析了目前应用服务提供商、制造网格等现有网络化制造模式在应用推广等方面遇到的问题,阐述了云计算服务模式、云安全、高性能计算、物联网等理念和新技术对解决网络化制造中运营、安全等问题的契机。在此基础上提出了一种面向服务的网络化制造新模式——云制造。给出了云制造的定义,分析了云制造与应用服务提供商、制造网格等的区别。提出了一种云制造的体系结构,讨论了实施云制造所需攻克的关键技术和所取得的成果。最后,给出了一个云制造的典型应用案例——基于云仿真原型平台的云设计。     

Research on technologies and application of data mining for cloud manufacturing resource services

Nowadays, cloud manufacturing (CMfg) as a new service-oriented manufacturing mode has been paid wide attention around the world. However, one of the key technologies for better implementing CMfg services is how to address the problems faced by distributed massive and polymorphic data analysis and processing of manufacturing resource services in CMfg environment. In order to handle the problems, and promote development integration and business application of data mining, the research on technologies and application of data mining for cloud manufacturing resource (CMR) services has been carried out in this paper. The data mining application model and multi hierarchy architecture of CMR services are designed, and the topology of resource service data integrating process based on multi-Agent is presented. Besides, the preprocessing method of manufacturing resource data is proposed, and a CMR virtual data warehouse is established as well. In addition, an improved genetic algorithm oriented to manufacturing resource services is put forward, so as to achieve efficient searching and mining of massive polymorphic data. Finally, a case study is employed to illustrate the effectiveness and applicability of the proposed method in CMR service platform.     

Multi-task scheduling of distributed 3D printing services in cloud manufacturing

The problem of service matching and scheduling in cloud manufacturing (CMfg) is complex for different types of manufacturing services. 3D printing, as a rapidly developing manufacturing technology, has become an important service form in the CMfg platform due to its characteristics of personalized manufacturing. How to solve the task scheduling problem for distributed 3D printing services in CMfg needs further research. In this paper, a service transaction model of 3D printing services in CMfg is built. Based on the service transaction model, we propose 3D printing service matching strategies and matching rules of different service attributes, including model size, printing material, printing preciseness, task cost, task time, and logistics. To reduce the delivery time of tasks from service suppliers to service demanders, a 3D printing service scheduling (3DPSS) method is proposed to generate optimal service scheduling solutions. In 3DPSS, optimization objective, constraints, and optimization algorithm are presented in detail. Experimental results show that the average task delivery time of 3DPSS is shorter than that of typical scheduling methods, such as particle swarm optimization, pattern search, and sequential quadratic programming, when the amounts of tasks change.     

Application modes of cloud manufacturing and program analysis

Service-oriented manufacturing is a trend in the manufacturing industry in the 21st century. Numerous theories related to this trend have been proposed. In particular, three typical theories, namely, industry 4.0, industrial Internet, and cloud manufacturing (CMfg), are discussed in this paper, including their differences. Existing problems in CMfg are analyzed. From the perspective of the service supplier, and by considering former research, three application modes of CMfg are proposed. A 3D printing application mode of CMfg is presented based on the characteristics of 3D printing and discussed in detail. The key technologies of 3D printing in CMfg are explained according to the differences between traditional manufacturing and CMfg.     

Research on the impact of service provider cooperative relationship on cloud manufacturing platform

As an emerging service-oriented manufacturing paradigm, Cloud Manufacturing (CMfg) is expected to provide smart networked platforms that enable efficient global collaborations among cloud service providers in a product lifecycle. The service provider cooperative relationship (SPCR) plays a crucial part in cloud service scheduling and thus potentially influences the operational performance of a CMfg platform. The guaranteed SPCR could ensure service quality and reduce the interaction costs among service providers in the process of collaborative manufacturing tasks, thereby having a positive impact on the operational efficiency of a CMfg platform. The cost reduction and quality assurance, however, usually make the cost-effective services more attractive for an increasing number of manufacturing tasks and lead to load imbalance in a CMfg platform, thus having a negative impact on the operational efficiency. The impact mechanism of SPCR on a CMfg platform is still unclear from an evolutionary perspective. In this paper, we propose a CMfg platform evolution model (CPEM) to investigate the impacts of SPCR on the operational performance of a CMfg platform. Three quantitative metrics, from the perspective of cloud consumer, cloud operator, and cloud service provider, respectively, are established to support the performance evaluation. The results of contrast experiments reveal the impacts of SPCR on a CMfg platform.     

Common engines of cloud manufacturing service platform for SMEs

In order to improve the comprehensive competitiveness of small- and medium-sized enterprises (SMEs), a cloud manufacturing service platform for SMEs was implemented with the idea and model of cloud manufacturing (CMfg) in this paper. Using the transaction mode of multiple enterprises, multiple orders, and multi-party collaboration, the architecture and workflows of this cloud manufacturing service platform were designed. Some common engines, such as intelligent matching engine for supply and demand, transaction coordinating logic engine, and credit evaluation engine, were researched, which implement the semantic intelligent searching, order tracking, transaction task guiding, and collaborative management in the whole process of CMfg. As a case, this platform has been applied in the automobile and motorcycle parts manufacturing industry, which effectively integrates manufacturing service resources in this field through online services and offline services (O2O), achieving the effective management of service resources.     

云制造软资源封装研究

在研究现有制造资源的属性描述方法和封装模型的基础上,根据云制造汇聚资源服务进行集中管理以及为多个用户同时提供服务的特点,建立了一种新的基于Web服务的云制造软资源封装架构,并设计出通用软资源描述模型,结合该模型给出软资源封装的一般流程。通过数字化制造支持系统与PDM集成的实现,验证了云制造软资源的属性描述、封装模型建立和封装流程的可行性及合理性。     

云制造软资源封装研究

在研究现有制造资源的属性描述方法和封装模型的基础上,根据云制造汇聚资源服务进行集中管理以及为多个用户同时提供服务的特点,建立了一种新的基于Web服务的云制造软资源封装架构,并设计出通用软资源描述模型,结合该模型给出软资源封装的一般流程。通过数字化制造支持系统与PDM集成的实现,验证了云制造软资源的属性描述、封装模型建立和封装流程的可行性及合理性。     

Real-time task processing method based on edge computing for spinning CPS

Spinning production is a typical continuous manufacturing process characterized by high speed and uncertain dynamics. Each manufacturing unit in spinning production produces various real-time tasks, which may affect production efficiency and yarn quality if not processed in time. This paper presents an edge computing-based method that is different from traditional centralized cloud computation because its decentralization characteristics meet the high-speed and high-response requirements of yarn production. Edge computing nodes, real-time tasks, and edge computing resources are defined. A system model is established, and a real-time task processing method is proposed for the edge computing scenario. Experimental results indicate that the proposed real-time task processing method based on edge computing can effectively solve the delay problem of real-time task processing in spinning cyber-physical systems, save bandwidth, and enhance the security of task transmission.     

Cloud manufacturing service platform for small- and medium-sized enterprises

In order to address the key problems faced by small- and medium-sized enterprises (SMEs), existing solutions and shortcomings were analyzed. The possibilities by using the new emerged technologies and theories (e.g., cloud computing, internet of things, service-oriented technology) to solve the bottlenecks faced by SMEs are investigated. The idea of manufacturing resource and capability sharing based on cloud computing for SME is discussed, and an SME-oriented cloud manufacturing service platform (SME-CMfgSP) is introduced. The architecture of SME-CMfgSP is proposed, and the key technologies for implementing SME-CMfgSP are introduced in details. The challenges for implementing cloud manufacturing service platform for SMEs were discussed. A case study is described to illustrate the application of the proposed SME-CMfgSP.     

配用电云平台分布式实时数据处理技术研究

为解决配电网云平台大规模实时数据的处理问题,设计了一种分布式实时数据处理方法。集群分布式实时数据库可实现海量数据的分布式存储,而且具有统一访问和管理功能。提出了一种新型分布式SCADA系统,进一步提高实时数据的分布式处理能力。给出了新型分布式SCADA系统架构,包括基础设施、分布式资源与任务处理、分布式实时数据处理、分布式数据处理。在云计算环境下,讨论了弹性事件队列和弹性应用框架等关键技术,系统地建立同云计算相适应框架,全面提升系统的数据采集、存储、分析、计算、扩展等能力。     

凸轮轴数控磨削云平台的研究与设计

针对整合磨削加工领域资源的问题,借鉴云计算与云制造的思想,提出并开发了整合与利用磨削软硬两大类资源的磨削云平台。提出了磨削云平台体系架构,设计了其软件结构,研究了其关键技术。利用人工智能技术,设计了磨削云平台应用需求模型及其工作流程与关键算法。开发了SaaS服务系统、PaaS服务系统、IaaS-to-PaaS分布式异构数据库同步复制系统、IaaS服务系统、用户注册登录管理系统5个软件子系统所组成的磨削云平台,使得企业在资源利用上更为优化便捷。将该磨削云平台应用于实际生产,有效提高了生产加工效率,降低了生产成本。     

基于深度学习算法的调度自动化云平台任务优化策略研究

分析了云平台任务调度的特点和目标,从任务调度算法入手,提出了基于改进粒子群算法的电力调度自动化系统的人工智能方法,开发了云计算操作的模型。基于该算法和物理模型的运行控制考虑了 QoS 要求和平台云居民的环境负载平衡,可以有效提高所提电力调度自动化系统的云平台任务调度的效率。以电力自动化云平台为分析对象,研究其架构,将修正的 PSO 算法与云资源调度模型的结构拓扑相结合,建立三级数据节点,给出了基于改进 PSO 的云平台调度模型,旨在提高云计算资源配置效率,改善云服务质量,解决电力调度自动化系统的任务调度问题。     

依赖多子群分层混合算法的云计算信息系统安全等级保护测评

基于多子群分层混合算法的云计算信息系统的概念和信息安全等级保护(Information security level protection,ISLP)的基本内涵,研究了云计算信息系统的系统结构和信息处理机制。其中,提出了一种多子群分层混合算法的云计算信息系统信息安全等级保护测评方法,即分布式配置与集中式云计算相结合,及其软硬件框架与感知检测集成,并提出了基于镜头原理的信息处理框架及其接收信息处理的流程。设计了多子群分层混合算法,利用镜头聚焦模型和五个阶段的信息处理序列,建立并解析了云计算的工作规律及其自反馈调整,验证了所提出思想的合理性和优势。     

扩展型混合磨削云PAAS系统的研究与设计

计算机辅助磨削制造软件是磨削制造加工领域的软实力资源,扩展型混合磨削云PAAS系统为整合利用磨削制造软件资源提供了一个通用的、可扩展的平台,它利用混合云计算技术为磨削制造加工企业使用CAM软件资源提供了方便可靠、费用低廉的途径。设计了PAAS系统的网络及软件体系架构,阐述了系统的实现原理、功能及关键技术,利用人工智能技术设计了CAM方案控制算法,开发了磨削云PAAS软件系统,并对其在磨削行业的实践应用及发展趋势做了介绍。     

基于MapReduce和多目标蚁群算法的制造云服务动态选择算法

基于云计算技术和云服务技术研究了云服务的动态选择问题,给出了云制造服务层次化模型,提出了一种基于MapReduce和多目标蚁群算法的制造云服务动态选择算法(CSSMA)。依据CSSMA设计了多目标蚁群算法、Map函数、Reduce函数和优化策略等,并将其分布式并行运行于制造云平台中。仿真实验结果表明:CSSMA具备良好的处理大规模问题的能力,适用于制造云服务动态选择问题的求解。     

云计算中分布式软件系统兼容性自动检测方法

为避免软件系统之间的冲突,提高软件整体协调性能,提出云计算中分布式软件系统兼容性自动检测方法。构建云计算基本架构,探究云计算在软件兼容性检测中提供的多种服务模式;建立基本粒子群算法模型,通过对权重与学习因子的调节,确定合适的离散度,保证粒子多样性;采用分支路径覆盖式,成立嵌套分支与谓词分支,计算分支综合权重,获取最佳适应度函数;引入碰撞域有关理论,设置兼容性检测样本的关键参考量,经过对碰撞半径的调整生成覆盖率较高的测试用例,当满足停止条件时,结束迭代,输出检测结果。实验结果证明,所设计方法检出率较高,减少用户等待时间,降低 CPU 使用率,且自动化程度较高。