CIMS环境下车间级集成质量系统研究

文章分析了基于功能管理和基于过程管理两种模式的计算机辅助质量管理系统的集成结构模型,提出了车间级集成质量管理系统的功能模型。在此基础上,利用软件组件和Web技术,详细设计和实现了该系统的各个软件模块。该软件应用于实际,与CIMS其它子系统集成运行,提高了制造企业的车间整体质量水平。     

射频识别在多品种小批量生产管理中的应用研究

针对多品种小批量生产环境下,生产过程难以实现精准管理的问题,采用射频识别标签标识车间重要生产对象,关键应用管控点部署交互式作业控制终端,自动、实时、准确、详细地获取车间物理环境的信息。在此基础上,构建相应的生产管理系统的体系结构和集成化运行模式。研究多源异构实时生产信息融合技术和基于组件技术的可重构生产管理系统实现方法。该系统已成功应用于重庆某企业摩托车装配线,取得了良好的应用效果。     

基于Web的离散型制造业设备能力管理系统研究

该文针对大连某设备制造企业离散型车间的现有设备情况,分析了整体车间在实际生产中的业务模型和功能模型,建立了B/S模式的系统框架,开发了基于Web的设备能力管理系统(ECMS),实现了对设备管理的自动化、数字化和规范化,提高了离散型企业车间的生产效率,降低了生产成本,还与其他管理系统实现了有效集成。该系统已经在大连某设备制造有限公司试运行,系统运行良好,有效解决了离散型企业车间的设备能力管理问题,并得到用户的一致好评。     

构建面向航空制造企业的车间管理信息系统

目前我国大多数航空制造企业正处于生产方式和管理模式的转型时期,生产的组织和管理仅凭经验靠手工方式进行,管理者个体经验的差异常常导致生产组织效果的重大差别。航空制造企业机加车间的生产特点要求高效、优化和规范的车间管理系统与之相适应。论文通过对航空制造企业机加车间的业务流程描述和功能分析构建了以计划为核心、计划推动生产准备部门工作为运作模式的面向航空制造企业的车间管理信息系统模型,论述了其体系结构和功能特点,并用Delphi语言基于组件技术开发并予以实现。     

ERP中免疫遗传算法的关联规则挖掘

探讨了一种基于免疫遗传算法的关联规则数据挖掘系统模型,并成功应用于某大型制药公司已实施的ERP车间管理系统中,从车间已积累的大量生产历史数据中获得潜在的规律和趋势,为公司降低生产成本,提高产品生产能力提供了有效支持。内容包括基于免疫遗传算法的关联规则挖掘的研究、生产数据关联规则挖掘模型的建立以及该模型在ERP系统中的实现等。     

基于Delphi车间管理系统的开发

基于Delphi车间管理系统是一个以提高车间管理效率为目的的管理系统,此系统采用的是TCP/IP协议技术,以Delphi为开发平台,SQL Server2005为后台数据库。车间管理系统主要包括了质量管理、设备管理、配件管理、成本管理和人力资源管理几个模块,系统可以全自动的对车间内的相关仪器和生产设备进行资料采集,为车间的管理决策提供依据。     

整理车间多Agent生产管理系统的建模与过程优化

借助多Agent技术,提出了一种基于多Agent的生产管理结构模型,对用户实际需求和结构模型的合理性进行了分析.在此基础上,开发了一个柔性、动态、高效的生产管理系统,对车间目前的生产管理模式进行了优化.同时,对多个体Agent的主要功能、工作原理和系统建模过程进行了介绍.实际应用表明,多Agent的生产管理系统,解决了...     

COM+在钢铁企业经销系统中的应用

对COM＋基本结构及基于COM＋组件的多层应用模型进行了分析，将COM＋组件应用于某钢铁企业“整合型集团经销信息网络管理系统”中．初步实现了基于COM＋组件技术的三层客户端／服务器结构的系统模型．从而提高了钢铁企业经销系统的性能。     

基于组件的考试管理信息系统分析与设计

对考试管理的各个环节进行系统分析,提出了基于组件的考 试管理系统的设计方法,对考试管理中主要业务功能进行了组件模型设计。由这些组件集成 考试系统,不仅节约了开发周期,而且可实现考试的规范化,体现了考试的公平公正原则。     

基于组件的车间管理信息系统模型

基于组件的软件开发方法成为当前软件开发的一个新的重要方法,但是如何合理地划分组件的粒度,使组件的重用性与可维护性达到最佳平衡是非常困难的。为此,文章研究了车间管理信息系统的组件技术,建立了车间管理信息系统的组件模型,提出了内核组件、支撑组件、外壳组件、虚拟数据库的概念。     

面向虚拟森林仿真的多层场景引擎设计

为快速绘制具有真实感的大规模虚拟森林场景,在分析虚拟森林场景仿真特点的基础上,提出面向虚拟森林仿真多层场景引擎的总体结构,对该场景引擎中的实时地形生成技术、地形模型的简化算法和渲染加速等关键技术展开研究,开发了虚拟森林仿真系统。应用结果表明,面向虚拟森林仿真的多层场景引擎有助于提高复杂森林场景的绘制效率,能较好地满足用户进行实时漫游和交互控制的需求。     

Semantic integration of enterprise information systems using meta-metadata ontology

This paper proposes a non-domain-specific metadata ontology as a core component in a semantic model-based document management system (DMS), a potential contender towards the enterprise information systems of the next generation. What we developed is the core semantic component of an ontology-driven DMS, providing a robust semantic base for describing documents’ metadata. We also enabled semantic services such as automated semantic translation of metadata from one domain to another. The core semantic base consists of three semantic layers, each one serving a different view of documents’ metadata. The core semantic component’s base layer represents a non-domain-specific metadata ontology founded on ebRIM specification. The main purpose of this ontology is to serve as a meta-metadata ontology for other domain-specific metadata ontologies. The base semantic layer provides a generic metadata view. For the sake of enabling domain-specific views of documents’ metadata, we implemented two domain-specific metadata ontologies, semantically layered on top of ebRIM, serving domain-specific views of the metadata. In order to enable semantic translation of metadata from one domain to another, we established model-to-model mappings between these semantic layers by introducing SWRL rules. Having the semantic translation of metadata automated not only allows for effortless switching between different metadata views, but also opens the door for automating the process of documents long-term archiving. For the case study, we chose judicial domain as a promising ground for improving the efficiency of the judiciary by introducing the semantics in this field.     

Graphical causal inference and copula regression model for apple keywords by text mining

Apple is a leading company of technological evolution and innovation. This company founded and produced the Apple I computer in 1976. Since then, based on its innovative technologies, Apple has launched creative and innovative products and services such as the iPod, iTunes, the iPhone, the Apple app store, and the iPad. In many fields of academia and business, diverse studies of Apple’s technological innovation strategy have been performed. In this paper, we analyze Apple’s patents to better understand its technological innovation. We collected all applied patents by Apple until now, and applied statistics and text mining for patent analysis. By using graphical causal inference method, we created the causal relations among Apple keywords preprocessed by text mining, and then we carried out the semiparametric Gaussian copula regression model to see how the target response keyword and the predictor keywords are relating to each other. Furthermore, Gaussian copula partial correlation was applied to Apple keywords to find out the detailed dependence structure. By performing these methods, this paper shows the technological trends and relations between Apple’s technologies. This research could make contributions in finding vacant technology areas and central technologies for Apple’s R&D planning.     

基于规则引擎的电子采购逆向竞拍的研究

近年来规则引擎技术已广泛应用于金融、电子商务及制造业等领域。当前大型企业的采购方式越来越多样化,传统采购系统所采用的逆向竞拍方案已不能满足现有需求。本文研究了规则引擎技术在企业电子采购系统中的应用,以将程序代码和业务规则分离开来。企业可以按照不同采购需求个性化配置采购规则,规则引擎控制整个拍卖过程,拍卖结束后系统再利用规则引擎自动对报价进行评分,帮助企业选择最优供应商,使其在采购过程中降低成本,提高采购效率。     

Smart Maintenance Decision Support Systems (SMDSS) based on corporate big data analytics

The purpose of this article is to outline the architectural design and the conceptual framework for a Smart Maintenance Decision Support System (SMDSS) based on corporate data from a Fortune 500 company. Motivated by the rapidly transforming landscape for big data analytics and predictive maintenance decision making, we have created a system capable of providing end users with recommendations to improve asset lifecycles. Methodologically, a cost minimization algorithm is used to analyze a large industry service and warranty data sets and two analytical decision models were developed and applied to a case study for an electrical circuit breaker maintenance problem. Some of these techniques can be applied to other industries, such as jet engine maintenance, and can be expanded to others with implications for robust decision analysis. The SMDSS provides a predictive analytical model that can be applied in manufacturing and service based industries. Our findings and results show that existing solution algorithms and optimization models can be applied to large data sets to lay out executable decisions for managers.     

两种优化训练的FNN在船舶柴油机故障诊断中的性能研究

本文针对船舶柴油机故障诊断系统,基于遗传算法（genetic algorithm,GA）和蚁群优化算法（ant colony optimization algorithm,ACOA）构造了2种优化训练的模糊神经网络（fuzzy neural network,FNN）智能故障诊断模式,给出了该模糊神经网络智能故障诊断系统的结构及其参数选取方法,通过对船舶柴油机燃烧子系统的FNN模型结构权值和阈值优化训练的故障诊断仿真研究,对两种方式的性能进行对比研究,仿真测试结果表明,基于ACOA的诊断模型具有更好的故障诊断知识表达准确性和较快的收敛速度等特点,具有较好的应用前景。     

一个基于链接分析的相关度排序算法及其在专题搜索引擎中应用

对HITS(Hyperlink-Induced Topic Search)算法进行研究,克服其主体漂移和扩大化等缺点,改进并提出建立一个新的基于链接分析的Web检索结果的相关度排序方法,并把它应用到一个专题搜索引擎中.     

Survey on hierarchical routing schemes in?��flat�� distributed hash tables

The first generation of DHT designs offered a completely flat structure of the key space that is randomly partitioned among participating DHT nodes. That has certain advantages, for example, even distribution of workload among nodes. On the other hand, grouping keys under a single authority or achieving latency guarantees for queries is difficult. To address these shortcomings, various kinds of hierarchy have been proposed over recent years. The last generation is hierarchical DHTs (HDHTs) where nodes are organized onto layers; each next layer consists of supernodes for the previous layer. In this survey paper, we thoroughly go over the evolution of DHTs from pure flat to pre-hierarchical. Our focus is on hierarchical schemes in DHT routing. We argue that their application is not restricted within HDHT designs. We sequentially built a set of design principles; each provides a base for hierarchical routing schemes. In the extreme case, application these principles leads to HDHT designs.     

Scalable protection for MPEG-4 fine granularity scalability

The newly adopted MPEG-4 fine granularity scalability (FGS) video coding standard offers easy and flexible adaptation to varying network bandwidths and different application needs. Encryption for FGS should preserve such adaptation capabilities and enable intermediate stages to process encrypted data directly without decryption. In this paper, we propose two novel encryption algorithms for MPEG-4 FGS that meet these requirements. The first algorithm encrypts an FGS stream (containing both the base and the enhancement layers) into a single access layer and preserves the original fine granularity scalability and error resilience performance in an encrypted stream. The second algorithm encrypts an FGS stream into multiple quality layers divided according to either peak signal-to-noise ratio (PSNR) or bit rates, with lower quality layers being accessible and reusable by a higher quality layer of the same type, but not vice versa. Both PSNR and bit-rate layers are supported simultaneously so a layer of either type can be selected on the fly without decryption. The base layer for the second algorithm may be unencrypted to allow free view of the content at low-quality or content-based search of a video database without decryption. Both algorithms are fast, error-resilient, and have negligible compression overhead. The same approach can be applied to other scalable multimedia formats.     

An intelligent simulation model to evaluate scheduling strategies in a steel company

An embedded structure is selected to construct an intelligent simulation model. A framework is proposed so that both the event generator and expert system are controlled by a simulation mechanism. The expert system includes an inference engine and a knowledge base. When the simulation mechanism starts the inference engine, the inference engine reasons based on the system states. Then the system will process the events according to the inference results. An ‘intelligent entity’ simulates an entity with intelligence such as a ‘real’ server, manager or pilot. The SIMSCRIPT II.5 simulation language is used to illustrate how the proposed framework can be implemented in an example situation of harbour unloading by a steel company which needs to import coal when the capacity of the harbour is limited. Finally, possible future research directions are presented.