Discrete event-driven model predictive control for real-time work-in-process optimization in serial production systems

Advanced technologies (e.g., distributed sensors, RFID, and auto-identification) can gather processing information (e.g., system status, uncertain machine breakdown, and uncertain job demand) accurately and in real-time. By combining this transparent, detailed, and real-time production information with production system physical properties, an intelligent event-driven feedback control can be designed to reschedule the release plan of jobs in real-time without work-in-process (WIP) explosion. This controller should obtain the operational benefits of pull (e.g., Toyota’s Kanban system) and still develop a coherent planning structure (e.g., MRPII). This paper focuses on this purpose by constructing a discrete event-driven model predictive control (e-MPC) for real-time WIP (r-WIP) optimization. The discrete e-MPC addresses three key modelling problems of serial production systems: (1) establish a max-plus linear model to describe dynamic transition behaviors of serial production systems, (2) formulate a model-based event-driven production loss identification method to provide feedback signals for r-WIP optimization, and (3) design a discrete e-MPC to generate the optimal job release plan. Based on a case from an industrial sewing machine production plant, the advantages of the discrete e-MPC are compared with the other two r-WIP control strategies: Kanban and MRPII. The results show that the discrete e-MPC can rapidly and cost-effectively reconfigure production logic. It can decrease the r-WIP without deteriorating system throughput. The proposed e-MPC utilizes the available transparent sensor data to facilitate real-time production decisions. The effort is a step forward in smart manufacturing to achieve improved system responsiveness and efficiency.     

Hybrid parallel computing of minimum action method

In this work, we report a hybrid (MPI/OpenMP) parallelization strategy for the minimum action method recently proposed in [17]. For nonlinear dynamical systems, the minimum action method is a useful numerical tool to study the transition behavior induced by small noise and the structure of the phase space. The crucial part of the minimum action method is to minimize the Freidlin–Wentzell action functional. Due to the fact that the corresponding Euler–Lagrange equation is, in general, highly nonlinear and of high order, we solve the optimization problem directly instead of discretizing the Euler–Lagrange equation to provide a general but equivalent numerical framework. To enhance the efficiency of the minimum action method for general dynamical systems we consider parallel computing. In particular, we present a hybrid parallelization strategy based on MPI and OpenMP. Numerical results are presented to demonstrate the efficiency of the proposed parallelization strategy.     

煤矿冲击地压和煤与瓦斯突出感知报警方法研究

提出了基于温度的冲击地压和煤与瓦斯突出感知报警方法:使用红外热像仪等监测物体温度,使用甲烷传感器监测环境甲烷浓度;当物体温度高于煤矿井下环境温度和已暴露煤岩温度,并且高于环境温度和已暴露煤岩温度的物体数量较多、体积和面积较大,则判定发生冲击地压、煤与瓦斯突出、矿井火灾或瓦斯和煤尘爆炸事故;进一步判别高温物体温度,若大于设定阈值,则判定发生矿井火灾或瓦斯和煤尘爆炸事故,反之,则判定发生冲击地压或煤与瓦斯突出事故;进一步分析甲烷浓度变化,若甲烷浓度迅速升高,则判定发生煤与瓦斯突出事故,反之,则判定发生冲击地压事故。提出了基于速度的冲击地压和煤与瓦斯突出感知报警方法:使用激光雷达、毫米波雷达、超声波雷达、双目视觉摄像机等监测物体移动速度,使用甲烷传感器监测环境甲烷浓度;当物体移动速度不小于设定阈值时,则判定发生冲击地压、煤与瓦斯突出或瓦斯和煤尘爆炸事故;进一步判别速度异常物体的数量、体积和面积,若速度异常物体的数量较少、体积和面积较小,则判定发生瓦斯和煤尘爆炸事故,若速度异常物体的数量较多、体积和面积较大,则判定发生冲击地压或煤与瓦斯突出事故;进一步分析甲烷浓度变化,若甲烷浓度迅速升高,则判定发生煤与瓦斯突出事故,反之,则判定发生冲击地压事故。提出了多信息融合的冲击地压和煤与瓦斯突出感知报警及灾源判定方法:监测并融合温度、速度、加速度、掩埋深度、声音、气压、风速、风向、粉尘、甲烷浓度、设备状态、微震、地音、应力、红外辐射、电磁辐射、图像等多种信息,感知冲击地压和煤与瓦斯突出;通过不同位置参数变化的幅度、先后时序关系及传感器损坏情况,判定灾源。     

Timestamping messages and events in a distributed system using synchronous communication

Determining order relationship between events of a distributed computation is a fundamental problem in distributed systems which has applications in many areas including debugging, visualization, checkpointing and recovery. Fidge/Mattern’s vector-clock mechanism captures the order relationship using a vector of size N in a system consisting of N processes. As a result, it incurs message and space overhead of N integers. Many distributed applications use synchronous messages for communication. It is therefore natural to ask whether it is possible to reduce the timestamping overhead for such applications. In this paper, we present a new approach for timestamping messages and events of a synchronously ordered computation, that is, when processes communicate using synchronous messages. Our approach depends on decomposing edges in the communication topology into mutually disjoint edge groups such that each edge group either forms a star or a triangle. We show that, to accurately capture the order relationship between synchronous messages, it is sufficient to use one component per edge group in the vector instead of one component per process. Timestamps for events are only slightly bigger than timestamps for messages. Many common communication topologies such as ring, grid and hypercube can be decomposed into edge groups, resulting in almost 50% improvement in both space and communication overheads. We prove that the problem of computing an optimal edge decomposition of a communication topology is NP-complete in general. We also present a heuristic algorithm for computing an edge decomposition whose size is within a factor of two of the optimal. We prove that, in the worst case, it is not possible to timestamp messages of a synchronously ordered computation using a vector containing fewer than components when N ≥ 2. Finally, we show that messages in a synchronously ordered computation can always be timestamped in an offline manner using a vector of size at most . An earlier version of this paper appeared in 2002 Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS). The author V. K. Garg was supported in part by the NSF Grants ECS-9907213, CCR-9988225, an Engineering Foundation Fellowship. This work was done while the author C. Skawratananond was a Ph.D. student at the University of Texas at Austin.     

VB中通信控件的设置与应用

介绍了利用MSComm控件进行通信时串行口的打开与关闭,缓冲区的设置和数据的收发形式,同时也介绍了握手协议和通信时错误信号的捕获。     

时空数据库索引方法研究

时空数据库作为数据库研究领域中的一个重要分支,经过近十年的发展,在时空数据模型、时空查询优化与索引和时空本体论等方面取得了许多成果。现实世界中的许多实体都具有空间特性和时态特性,需要数据库管理系统提供有效的时空数据管理能力,如地籍管理系统中的地块、交通管理系统中的车辆等。时空数据库用于管理形状和位置随时问变化的对象。为了快速访问其庞大的数据量,必须建立有效的时空索引以提高各类时空查询的效率。提出了一种新的时空索引方法（瓣索引）,它综合了快照和事件这两种时空信息建模方法。不仅能够处理时间片查询和时间段查询,而且能够进行事件查询。SEST索引使用R-tree结构来存储快照,用一种日志数据结构来存储发生在两次相邻快照之间的事件。通过实验对比SEST索引和HR—tree,结果表明：当变化频率在1％到13％之间时,SEST索引比HR—tree需要的存储空间少;当变化频率在1％到7％之间时,在时间段查询方面,SEST索引比HR—tree要好。因为SEST索引是一种面向事件的结构,所以事件查询时效率很高。     

Modeling and Managing Interactions among Business Processes

Most workflow management systems (WfMSs) only support the separate andindependent execution of business processes. However, processes often needto interact with each other, in order to synchronize the execution of theiractivities, to exchange process data, to request execution of services, orto notify progresses in process execution. Recent market trends also raisethe need for cooperation and interaction between processes executed in differentorganizations, posing additional challenges. In fact, in order to reduce costsand provide better services, companies are pushed to increase cooperation and toform virtual enterprises, where business processes span across organizationalboundaries and are composed of cooperating workflows executed in differentorganizations. Workflow interaction in a cross-organizational environment iscomplicated by the heterogeneity of workflow management platforms on top ofwhich workflows are defined and executed and by the different and possiblycompeting business policies and business goals that drive process executionin each organization.In this paper we propose a model and system that enable interactionbetween workflows executed in the same or in different organizations. Weextend traditional workflow models by allowing workflows to publish andsubscribe to events, and by enabling the definition of points in the processexecution where events should be sent or received. Event notifications aremanaged by a suitable event service that is capable of filtering andcorrelating events, and of dispatching them to the appropriate targetworkflow instances. The extended model can be easily mapped onto anyworkflow model, since event specific constructs can be specified by means ofordinary workflow activities, for which we provide the implementation. Inaddition, the event service is easily portable to different platforms, anddoes not require integration with the WfMS that supports the cooperatingworkflows. Therefore, the proposed approach is applicable in virtually anyenvironment and is independent on the specific platform adopted     

混合监测技术在并行与分布式性能监测中的应用

主要介绍了混合监测技术在并行与分布式系统性能分析评价中的应用。分析比较了常用的几种监测技术,给出了各自的优缺点,介绍了混合监测中的事件的定义,自动装备的过程。事件的采集和分析这向个关键步骤,提出装备的层交化。最后提出了混合监测中会遇到一些问题并给出了相应的解决方法。     

低温冻结石门揭煤煤体温度及力学性能变化规律研究

为研究低温冻结石门揭煤煤体温度及力学性能变化规律,制作煤样时将U形铜管预埋在内并进行注液氮冻结,通过温度测量、红外热成像、单轴压缩等试验分析了不同冻结时间下煤样内部及表面温度和应力-应变变化特征。试验结果表明:随着冻结时间的增加,煤样内部及表面温度呈下降趋势;煤样表面最低温度位于U形铜管附近,煤样表面最高温度位于煤样边界;在压密阶段,随着冻结时间的增加,煤样应变逐渐减小,压密阶段缩短;在弹性变形阶段和屈服阶段,随着冻结时间的增加,煤样最大应力和弹性模量均呈增大趋势。     

一种无监督的窃密攻击及时发现方法

近年来,窃密攻击成为了最严重的网络安全威胁之一.除了恶意软件,人也可以成为窃密攻击的实施主体,尤其是组织或企业的内部人员.由人实施的窃密很少留下明显的异常痕迹,给真实场景中攻击的及时发现和窃密操作的分析还原带来了挑战.提出了一个方法,将每个用户视为独立的主体,通过对比用户当前行为事件与其历史正常行为的偏差检测异常,以会话为单元的检测实现了攻击发现的及时性,采用无监督算法避免了对大量带标签数据的依赖,更能适用于真实场景.对算法检测为异常的会话,进一步提出事件链构建方法,一方面还原具体窃密操作,另一方面通过与窃密攻击模式对比,更精确地判断攻击.在卡内基梅隆大学的CERT内部威胁数据集上进行了实验,结果达到99%以上的准确率,且可以做到无漏报、低误报,证明了方法的有效性和优越性.