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...     

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.     

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.     

面向制造网格的任务管理系统研究

为协调和共享制造网格中分布的资源，设计并实现了一个面向网格服务的任务管理系统。建立了该系统的功能模型和工作流程，定义了面向零件和组件加工任务的网格资源节点模型和任务模型；基于任务时间、成本和服务质量的约束，建立了任务分解规则和资源节点的匹配规则，设计了任务调度及状态监控方案；最后构建了系统实现的体系结构和信息交换过程。基于网格原理，系统各功能被封装为网格服务，通过任务管理中心实现对服务的调用。系统已被集成到某区域网络化制造服务平台，为企业提供了与制造过程相关的网格服务。     

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.     

A study of optimal allocation of computing resources in cloud manufacturing systems

As a new advanced service-oriented networked manufacturing model, cloud manufacturing (CMfg) has been proposed recently. The optimal allocation of computing resources (OACR) is a core part for implementing CMfg. High heterogeneity, high dynamism, and virtualization make the OACR problem more complex than the traditional scheduling problems in grid system or cloud computing system. In this paper, a new comprehensive model for OACR is proposed in the CMfg system. In this model, all main computation, communication, and reliability constraints in the special circumstances are considered. To solve the OACR problem, a new improved niche immune algorithm was presented. Associated with the niche strategy, new heuristics are designed flexibly based on the characteristics of the problem and pheromone is added for adaptive searching. Experiments demonstrate the effectiveness of the designed heuristic information and show NIA’s high performances for addressing the OACR problem compared with other intelligent algorithms.     

基于分层任务网络的云制造任务分解方法

提出了一种基于顺序任务分解的云制造任务分解算法。首先给出云制造任务描述模型以及任务约束结构的相关定义,对制造任务粒度分析方法、制造任务内聚性度量方法和制造任务相关性度量方法进行了研究。然后,采用递归分解算法对任务进行优化分解,并在分解过程中考虑任务的资源匹配问题。最后,以某变速箱试制任务分解为实例验证了所提方法的可行性和有效性。     

面向云计算环境任务调度的改进蚁群算法

云计算环境下的任务调度问题是一个NP完全问题,其目的是在各个处理节点上合理分配任务,优化调度策略以保证有效完成任务。以总任务完成时间最短和计算成本最低为优化目标,针对蚁群优化算法易陷入局部最优的缺陷,提出了一种求解该问题的改进蚁群算法。该算法将遗传算法的二点交叉算子融入到蚁群优化算法中,以提高蚁群优化算法的局部搜索能力。通过在云仿真平台Cloud Sim上进行仿真实验,结果表明改进蚁群算法缩短了总任务完成时间,降低了计算成本,从而证明了该算法能有效地解决云计算环境下的任务调度问题,并且其优化能力和收敛速度优于蚁群优化算法和改进离散粒子群算法。     

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。     

考虑配合加工的作业车间启发式倒排调度算法

目前对制造业领域作业车间调度问题研究中,配合加工增加了调度的约束,使调度的难度进一步加大。根据实际配合加工作业车间环境,建立了以最短加工时间为目标的调度模型,采用启发式倒排算法对其求解,该算法能保证工件的交货期,最后通过实例对算法进行验证并给出对比结果。     

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。     

面向服务链构建的云制造资源集成共享技术研究

为实现时序约束关联任务驱动的云制造环境下面向服务链构建的制造资源集成共享,研究并提出一种能促进云制造环境下制造资源快速共享、广域集成和分散服务特点的服务过程模型,对基于语义本体的云制造任务与资源建模、基于Web服务资源框架的云制造资源的平台服务化封装方案、云制造任务分解与时序约束关联原子任务链构建技术,以及云制造资源服务链构建技术等关键问题进行了研究,有效解决了云制造环境下异构资源描述、虚拟化、检索匹配与服务组合问题,最后通过仿真算例对提出的云制造服务模式及技术方案进行了验证。     

求解分布式混合流水线调度问题的改进双层嵌套式遗传算法

针对分布式混合流水线生产的生产调度问题,模拟实际排产中的排产到线和排产到时的排产策略,提出了基于改进双层嵌套式遗传算法的两层优化模型。外层依据流水线分配平衡和准时交货等基本原则总体上解决生产订单在流水线之间的分配问题,内层以最小生产时间为主要目的求解流水线的生产订单生产次序问题。考虑到双层嵌套式遗传算法的时间复杂性,基于模糊逻辑理论设计了一种模糊控制器来动态调整遗传算子,并采用主动检测停止方法,提高算法效率。使用某空调工厂的实际生产数据验证了算法的可行性、计算结果的准确性及排产策略的有效性,为高级计划与排程(Advanced Planning and Scheduling,APS)中大规模复杂供应链调度问题提供了可借鉴的方法。     

基于协同进化粒子群的多层供应链协同优化

为了从整体角度优化调度供应链网络的各个环节,研究了带软时间窗的分批配送问题及其对需求分配与生产调度的影响,考虑在满足一定客户满意度水平条件下的最小化运作成本。建立了该问题的模型,针对此模型设计了协同进化粒子群优化算法并进行求解。通过实验研究表明,软时间窗对于问题的运作成本有很大的影响,整个供应链网络的协同优化对降低运作成本起到了关键的作用。     

考虑任务行程时间的多载量自动导引车系统防死锁任务调度

针对多载量自动导引车（AGV）系统的任务调度和缓冲区死锁问题,提出了考虑任务行程时间的防死锁任务调度方案。以最小化延迟率和交通负荷不均衡度为目标,建立了任务调度模型;分析了任务调度中的实际约束,并在任务行程时间约束下构建了预测模型;针对任务调度模型,提出了一种基于人工免疫-灰狼优化（AI-GWO）算法的多目标防死锁任务调度方法,利用死锁避免规则禁止即将引发工位缓冲区死锁的任务运行,并融合AI-GWO算法对任务执行顺序进行多目标优化;最后,根据AGV负载均衡度进行AGV任务分配。仿真结果表明,上述任务行程时间预测模型具有较高的准确率,任务调度模型及防死锁调度方法具有较好的优化性能和计算效率,从而显著提高了物流系统的任务准时率和路径网络的交通负荷均衡度。     

面向配做的柔性生产线调度

配做是精密加工中常用的方法,它增加了调度约束和调度的难度。为解决这一难题,在对各种调度约束标准化的基础上,进行了适于配做的调度操作标准化技术和启发式调度算法的研究,保证了调度解的正确性并实现了调度解的快速生成,在此基础上进行了调度解优化技术和调度评估方法的研究,最终实现了人机协同的调度、评估一体化,为配做生产提供了有效的调度工具。     

云制造下设计任务与知识资源双边匹配方法

设计任务与知识资源的匹配大多是以业务流程为基础的单向匹配,为解决研发设计任务与知识资源之间的双边匹配问题,提出面向云制造模式的研发设计任务与知识资源双边匹配总体框架,该框架包括双边匹配满意度评价指标体系构建、多指标满意度评价信息处理和多目标双边匹配决策模型构建与求解等关键步骤。以卫星产品研制工艺知识为例,验证了所提方法在解决设计任务和知识资源双边匹配,以及提升产品设计任务执行效率与质量方面的有效性。     

网络化制造环境下服务匹配与合成问题研究

针对网络化制造环境下制造服务的集成需要,提出了基于语义的制造服务匹配、合成及运行框架。该框架关注网络化制造过程的建模、运行、监控和改进等问题,指出服务的匹配与合成算法是网络化制造服务集成运行框架的关键问题。给出了制造服务的形式化定义,基于语义信息,从功能、输入输出参数及服务质量等方面综合考虑,建立了完整的匹配算法框架。通过建立服务合成的最短路径模型解决服务合成的优化问题。给出了服务匹配与合成算法的应用示例,并提出了进一步的研究方向。