RFID Based e-quality tracking in service-oriented manufacturing execution system

The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system (MES). Accompanied with turning the MES into service-oriented manufacturing execution system (so-MES), real-time e-quality tracking (e-QT), in which real-time data are computed, has played more and more important roles in manufacturing. This paper presents an e-QT model through the study of real-time status data tracking and quality data collecting. An implementing architecture of the e-QT model is constructed on the basis of radio frequency identification devices (RFID) data-tracking network. In order to develop the e-QT system, some key enabling technologies, such as configuration, data collection, and data processing, etc, are studied. The relation schema between hardware is built for the RFID data-tracking network based on the configuration technique. Real-time data are sampled by using data collecting technique. Furthermore, real-time status and quality data in a shop-floor can be acquired in terms of using the real-time data computing method. Finally, a prototype system is developed and a running example is given so as to verify the feasibility of methods proposed in this paper. The proposed research provides effective e-quality tracking theoretical foundation through the use of RFID technology for the discrete manufacturing.     

Modular synthesis of Petri nets for modeling flexible manufacturing systems

This paper proposes a modular Petri net synthesis method for modeling flexible manufacturing systems based on synchronization among control processes of the manufacturing resources (such as robots and machines). In the method, the target system is modeled in a bottom-up and uniform manner by first describing the system's control processes using strongly connected state machines (SCSMs) as the basic modules. Each SCSM may contain multiple tokens to represent resources from the same type such as spaces in a buffer. Next, the common transitions and common transition subnets of the modules are merged to represent their synchronization. The system model constructed is proven to be conservative and thus bounded. Moreover, a restricted class of merged nets is proven to be live and reversible. For general classes of merged nets, this paper shows theorems that easily calculateP-invariants of the final net without solving the linear system equations. TheseP-invariants can be used to help in verifying the model's qualitative properties such as liveness.     

监控效用信息理论及其应用

随着互联网及网络化制造技术的发展与应用,基于互联网的远程监控系统成为新的相关研究热点.监控效用信息理论正是面向网络化远程监控系统,在现有互联网资源约束下,提出的有效实现实时监控的信息理论方法,并在实际制造系统中得到了应用.     

网络化制造资源集成研究

对网络化制造资源集成的内涵以及其与传统资源集成进行了比较研究。对网络化制造资源集成进行了系统研究；从层次分析的角度建立了网络化制造资源集成框架；对制造资源进行描述，提出了制造资源信息建模方法；给出了制造资源集成宏观数学模型并对其进行分析，提出提升制造资源集成系统的核心能力应采取的宏观措施。     

基于深度置信网络的大数据制造过程实时智能监控

针对基于浅层学习模型的过程监控方法难以对大数据制造过程运行状态进行实时智能监控的问题,提出了基于深度置信网络的大数据制造过程实时智能监控方法。利用灰度图建立大数据制造过程质量图谱,以精准表达其过程的运行状态;构建用于识别大数据制造过程质量图谱的深度置信网络;应用离线训练好的深度置信网络模型对当前监控窗口内的过程质量图谱进行识别,实现大数据制造过程实时智能监控。最后,应用该方法对某注塑件大数据制造过程进行实时质量智能监控,结果表明：所提方法的识别性能明显优于基于主成分分析与BP神经网络、支持向量机的识别模型,能有效应用于大数据制造过程实时质量智能监控。     

基于WSN和GPRS网络的远程水质监测系统

针对目前水质检测采用的实验室手工分析方法实时性差等问题,提出一种基于无线传感器网络(WSN)和GPRS网络的远程水质监测系统方案。以ZigBee技术的无线传感器网络和GPRS网络为核心,实现对水质参数的远程检测、实时监测等功能。用户可以方便地观察当前或历史水质状况,并为未来养殖方案制定提供合理依据。系统构建简单,节点放置位置灵活,且不受地理限制。实验表明,该系统稳定可靠、操作方便。     

制造业企业业务流程再造的建模方法

业务流程再造是实施制造业企业信息化的关键，而良好的建模方法是企业流程再造成功的必要工具。本文通过对目前制造业企业流程再造的特点和当前的流程建模方法进行分析，指出了传统企业流程模型方法在进行制造业企业业务流程再造过程中的局限性，进而提出了基于组件接口思想、采用分布式协同建模的新的适应网络化制造环境下的企业业务流程建模方法。     

Object-Oriented Modeling for Flexible Manufacturing Systems

Object-oriented modeling provides a new way of thinking about flexible manufacturing systems, using models organized around real-world concepts. This paper describes how the object modeling technique can be used to develop integrated factory models that embrace factory process modeling as well as policy modeling. Such models can be used to assess how quickly a manufacturing organization can adjust its operations to meet changes in demands for products, consumer preferences, supplier quality, and lead times. These models also can be used as vehicles for studying the impact of introducing new product lines or new process technology without the disruption or expense of pilot projects or test setups.     

冗余信标及其在Petri网结构控制中的应用

提出了冗余严格极小信标的概念 ,冗余信标是网拓扑的一种特殊结构。在保证网系统的所有信标不被清空时 ,只需要考虑那些非冗余的严格极小信标即可。这样便降低无死锁Petri控制器设计的复杂性 ,大大增强了Petri网处理复杂系统的能力。同时提出了一种死锁控制的迭代算法 ,使用冗余信标的概念可以大大简化Petri网的设计。以自动制造系统为例 ,说明了这种概念的应用。     

基于项目计划与协调的网络联盟制造系统框架

网络联盟制造作为一种新的制造模式,引起广泛的关注。本文从基于项目计划与协调的网络联盟制造系统的主要思想和重要特征出发,推导出了基于项目计划与协调的网络联盟制造系统的概念模型,并采用系统集成设计方法推导出了基于项目计划与协调的网络联盟制造系统框架。最后通过开发的原型系统作了系统验证,取得了较好的效果。     

基于过程方法的制造企业质量管理系统模型研究

运用过程方法对制造企业的质量管理系统展开研究,分析、探讨了质量管理过程方法的本质特点与应用原则;将质量体系的过程网络模型与制造企业质量管理业务相结合,基于过程组与过程单元构造了过程集成化的质量管理系统模型;将制造企业的质量管理体系解析、封装为产品实现过程质量管理、综合质量业务管理和质量体系管理三个过程组,对过程组的单元构成及其内外部集成机制进行了分析与描述。该模型为制造企业质量管理系统设计与规划提供了一种新思路。     

竞争型人工神经网络的统计过程控制模式识别

统计过程控制(SPC)在现代制造和服务行业中是最常应用的性能改进工具之一,休哈特控制图作为SPC的基本方法,在质量管理领域得到了充分的应用,但是控制图的识别一直比较困难.为此,将神经网络引入到休哈特控制图中,用神经网络的方法对质量控制中控制图进行了识别,并建立了以竞争型人工神经网络为基础的新的神经网络,判断出控制图中的基本失效模式.     

企业协同交互建模系统研究

随着网络技术与网络应用的迅速发展,企业生产经营也走向了网络化。企业由“大而全”、“小而全”模式走向了企业间的合作,出现了企业间的动态联盟与虚拟企业。     

基于网络的企业参考模型库

随着 Internet技术的发展与网络技术的不断进步 ,企业生产经营朝全球化与网络化方向发展。针对现代企业对企业模型的新需求及现代经营环境的特点 ,本文系统地研究了基于网络的企业模型库构造方法 ,并介绍了我们正在开发的基于网络的企业参考模型库系统 (Network Based Reference Modeling System,NBRMS)。该系统把网络信息技术、分布式数据库技术、协同工程等领域的成果应用到企业参考模型库的建设中 ,切实解决企业参考模型库的创建、使用与维护等方面的问题。     

基于个人数字代理的制造质量控制与加工误差分析研究

为了满足高效便捷灵活地控制零件工序质量的要求,将无线网络技术引入制造过程,提出了基于无线网络技术的制造质量控制模式,并从运行逻辑和物理实现两个方面进行了深入描述与分析。该模式以基于个人数字助理的移动质量控制终端为核心,实现零件工序质量信息和制造过程各节点信息的实时处理与分析。研究了无线网络环境下多生产模式工序质量控制的实现技术,提出了将过程质量控制图与加工设备工况信息相结合的加工误差关联分析方法。最后,建立了基于无线网络技术的在线工序质量控制和误差分析原型系统,并对上述理论和技术进行了验证。     

产品质量智能预测控制研究

介绍了质量预测控制的研究现状,提出了基于质量特征参数序列的质量智能预测控制系统模型,分析了系统的稳定性.根据提出的系统模型利用动态神经网络对加工过程质量特征参数的变化进行了跟踪实验,效果良好.     

Statistical process control with intelligence using fuzzy ART neural networks

With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.     

Statistical process control with intelligence using fuzzy ART neural networks

With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.     

虚拟制造在细长轴磨削加工中的应用

虚拟制造在制造业的应用有了很大进展。对虚拟制造用于细长轴的磨削加工进行了探讨,通过建模和仿真,模拟细长轴的磨削加工过程,为细长轴的机械加工、质量控制提供了一条新的途径。     

面向制造网格的资源优化配置方法

时间、质量、成本和服务是影响现代制造企业竞争力的关键因素。为此，在制造网格中，需要设计一个合理高效的制造资源优化配置方法，从而为每个制造任务寻找到最适合的制造资源。在对网格制造资源优化配置过程中的一些概念进行形式化定义和描述的基础上，基于物理网络，详细论述了制造资源的网络结构模型及其性质；然后以此为基础，提出了应用逐步筛选的方法进行制造资源的优化配置，从而搜索出满足制造任务需求的T，Q，C，S性能指标的最佳制造资源。最后通过一个实例验证了此方法的正确性。