问题驱动的制造企业质量改进技术研究
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摘要
近年来,我国在轴承、齿轮和紧固件等基础件生产取得了突飞猛进的发展,其总体质量也得到了不断的提升。然而,由于受到人员、设备、技术与管理等多重因素的制约,许多企业在其制造过程中质量问题频发,特别重复性的质量事件屡见不鲜,致使企业穷于应付,不但带来巨大的经济损失,而且产品质量无法得到有效的保证与改善,这已成为我国制造企业目前迫切需要解决的难点。在国家自然基金和武器装备预研基金的资助下,本文围绕问题驱动的制造企业质量改进这个主题,开展以问题驱动为核心的制造企业质量改进技术研究。
第一章阐明了课题的背景,综述了国内外质量技术的研究现状,总结了企业质量改进发展的趋势和热点,从而引出了本文的研究内容是以“问题”为核心的制造企业质量改进技术及实现技术的研究;
第二章分析我国制造企业在质量问题管理领域存在的困惑,提出质量问题特征分类管理的需求。在对目前特征分类管理方法开展对比研究的基础上,构建了基于正交分类方法的制造过程的QP-DOC质量问题特征分类管理模型。通过质量问题特征分类管理模型的构建,为问题驱动的质量改进活动的开展奠定了基础;
第三章在问题特征分类管理模型的基础上,提出了问题驱动的质量改进模型,讨论基于ExGQM的业务过程描述模型、结构化质量改进模式的功能模块规划及知识资源管理等内容。从而为问题驱动的质量改进的实现奠定了基础;
第四章讨论了基于知识地图的质量改进案例知识整合方法。重点讨论了知识地图系统形式化描述、知识节点识别和描述、知识导航及知识节点检索向量构建等内容;
第五章在对制造企业生产过程监控研究成果进行分析的基础上,提出基于质量指标之间误差传播关系的生产过程监控点配置决策方法,使监控点的配置更加符合企业的实际情况;
第六章分析贝叶斯网络在质量问题诊断方面的优势及其存在的瓶颈,面向工序质量问题诊断的贝叶斯网络解构方法研究。重点讨论了案例的贝叶斯诊断网络模型的分解、模型库构建和基于子网模型的贝叶斯网络重构等内容,力图为面向工序质量问题诊断的贝叶斯网络模型的构建提供一个借鉴的思路和方法;
第七章在前面研究的基础上,以轴承企业为对象,研究问题驱动的质量改进在制造企应用。重点讨论了生产过程监控网络平台的构建等内容;
第八章总结了全文的研究内容及创新点,并展望了未来的研究工作。
In China, repetitive quality incidents continue to occur in the manufacturing process of our basic parts, which often forced companies to be engaged in event handling passively. Not only are caused huge economic losses, but also product quality can not be effectively improved. China's manufacturing enterprises are urgent to resolve these difficulties. From the grants of the National Natural Science Foundation and the weapons and equipment pre-research Fund, this paper researched on the technologies for quality improvement of issue-driven manufacturing companies.
In chapter one, the background of research, surveys the current research situation of quality improvement home and abroad is introduced and summarizes the development trends and hot spots of quality improvement, which leads to this dissertation research contents. Based on "issues", the research content includes quality improvement theory and key techniques for manufacturing companies.
In chapter two, the perplexities in quality control field of our manufacturing companies is analyzed and puts forward the requirement for the management of classification for the quality problems features. Based on the comparative study of current management of features classification and orthogonal classification, the dissertation proposes the QP-DOC model, which lay the foundation for the issue-driven quality improvement..
In chapter three, based on the model for features classification management, the dissertation proposes a issue-driven quality improvement model and discusses description model of business process based on ExGQM, structured function module plan of quality improvement mode and knowledge resource management. This lays the foundation for the implement of issue-driven quality improvement.
In chapter four, the method of knowledge integration for quality improvement case based on knowledge map is disscussed. It includes formal description of knowledge map system, identification and description of knowledge nodes, knowledge navigator and knowledge node retrieval vector construction.
In chapter five, the decision-making method of production process monitoring points based on error propagation between quality indexes is put forward. And the studies of researches on production process monitoring.
In chapter six, the strengths and bottleneck of Bayesian network in quality issues diagnosis and the deconstruction method of Bayesian networks in process quality problem diagnosis oriented is analyzed. It emphasizes on the decomposition of Bayesian network model for diagnosis, model base construction, and sub-net model reconfiguration based on Bayesian network. It tries to provide a draw on ideas and methods for the construction of Bayesian network model for process quality problem diagnosis.
Based on the researches of the front, chapter seven studies the application of issues-driven quality improvement in manufacturing enterprises with the bearing company as target.
In chapter eight, the contents and innovations of the dissertation is summarized and lookedto the future research.
第一章阐明了课题的背景,综述了国内外质量技术的研究现状,总结了企业质量改进发展的趋势和热点,从而引出了本文的研究内容是以“问题”为核心的制造企业质量改进技术及实现技术的研究;
第二章分析我国制造企业在质量问题管理领域存在的困惑,提出质量问题特征分类管理的需求。在对目前特征分类管理方法开展对比研究的基础上,构建了基于正交分类方法的制造过程的QP-DOC质量问题特征分类管理模型。通过质量问题特征分类管理模型的构建,为问题驱动的质量改进活动的开展奠定了基础;
第三章在问题特征分类管理模型的基础上,提出了问题驱动的质量改进模型,讨论基于ExGQM的业务过程描述模型、结构化质量改进模式的功能模块规划及知识资源管理等内容。从而为问题驱动的质量改进的实现奠定了基础;
第四章讨论了基于知识地图的质量改进案例知识整合方法。重点讨论了知识地图系统形式化描述、知识节点识别和描述、知识导航及知识节点检索向量构建等内容;
第五章在对制造企业生产过程监控研究成果进行分析的基础上,提出基于质量指标之间误差传播关系的生产过程监控点配置决策方法,使监控点的配置更加符合企业的实际情况;
第六章分析贝叶斯网络在质量问题诊断方面的优势及其存在的瓶颈,面向工序质量问题诊断的贝叶斯网络解构方法研究。重点讨论了案例的贝叶斯诊断网络模型的分解、模型库构建和基于子网模型的贝叶斯网络重构等内容,力图为面向工序质量问题诊断的贝叶斯网络模型的构建提供一个借鉴的思路和方法;
第七章在前面研究的基础上,以轴承企业为对象,研究问题驱动的质量改进在制造企应用。重点讨论了生产过程监控网络平台的构建等内容;
第八章总结了全文的研究内容及创新点,并展望了未来的研究工作。
In China, repetitive quality incidents continue to occur in the manufacturing process of our basic parts, which often forced companies to be engaged in event handling passively. Not only are caused huge economic losses, but also product quality can not be effectively improved. China's manufacturing enterprises are urgent to resolve these difficulties. From the grants of the National Natural Science Foundation and the weapons and equipment pre-research Fund, this paper researched on the technologies for quality improvement of issue-driven manufacturing companies.
In chapter one, the background of research, surveys the current research situation of quality improvement home and abroad is introduced and summarizes the development trends and hot spots of quality improvement, which leads to this dissertation research contents. Based on "issues", the research content includes quality improvement theory and key techniques for manufacturing companies.
In chapter two, the perplexities in quality control field of our manufacturing companies is analyzed and puts forward the requirement for the management of classification for the quality problems features. Based on the comparative study of current management of features classification and orthogonal classification, the dissertation proposes the QP-DOC model, which lay the foundation for the issue-driven quality improvement..
In chapter three, based on the model for features classification management, the dissertation proposes a issue-driven quality improvement model and discusses description model of business process based on ExGQM, structured function module plan of quality improvement mode and knowledge resource management. This lays the foundation for the implement of issue-driven quality improvement.
In chapter four, the method of knowledge integration for quality improvement case based on knowledge map is disscussed. It includes formal description of knowledge map system, identification and description of knowledge nodes, knowledge navigator and knowledge node retrieval vector construction.
In chapter five, the decision-making method of production process monitoring points based on error propagation between quality indexes is put forward. And the studies of researches on production process monitoring.
In chapter six, the strengths and bottleneck of Bayesian network in quality issues diagnosis and the deconstruction method of Bayesian networks in process quality problem diagnosis oriented is analyzed. It emphasizes on the decomposition of Bayesian network model for diagnosis, model base construction, and sub-net model reconfiguration based on Bayesian network. It tries to provide a draw on ideas and methods for the construction of Bayesian network model for process quality problem diagnosis.
Based on the researches of the front, chapter seven studies the application of issues-driven quality improvement in manufacturing enterprises with the bearing company as target.
In chapter eight, the contents and innovations of the dissertation is summarized and lookedto the future research.
引文
[1]Marsh,Michael.CIM solutions - toward 21st century SPC[J].SMT Surface Mount Technology Magazine,1997,10:48-50.
[2]Guh R S,Tannock J D.IntelliSPC:a hybrid intelligent tool for on-line economical statistical process control[J].Expert Systems with Applications,1999,17:195-212.
[3]Devor R.E.,Chang T.h.and Sutherland J.W.Statistical Quality Design and Control[J].Macmillan Publishing Company,1992.
[4]Keats J B.,Montgomery D.C.Statistical Applications in Process Control[C].New York:Marcel Dekker,1996.
[5]Montgomery D.C.Introduction to Statistical Quality Control,3rd ed.NewYork[C]:John Wiley & Sons,1996.
[6]Dale H.Besterfield And Et Al.,Total Quality Management(2nd Ed),Upper Saddle River,N.J.:Prentice Hall,1999.
[7]David L.Goetsch,Stanley B.Davis Quality Management:Introduction To Total Quality Management For Production,Processing,And Services(3rd Ed).Pper Saddle River,NJ:Prentice Hall,2000.
[8]Tannock J.D.Automating Quality Systems.CHAPMAN &HALL,1992.
[9]麦肯锡公司,世界质量管理水平的发展[OL],http://www.zhkc.com.cn/zhuanjia5.htm,2004.
[10]国家自然科学基金委员会工程与材料料学部机械工程科学技术学术前沿编委会[M]。机械工程科学技术前沿.北京:机械工业出版社,1996.
[11]Feigonbaum,A.V.《全面质量管理》[M]。机械工业出版社,1991,6.
[12]王丽颖.小批量工序质量控制方法及其若干关键技术的研究(D).大连交通大学,2007.
[13]乐清洪.智能工序质量控制的理论与方法研究[D].西北工业大学,2002.
[14]吴德会.基于质量信息集成的智能质量控制技术研究[D].合肥工业大 学,2006.
[15]谢红卫等.典型人因可靠性分析方法评述[J].国防科技大学学报.2007,29(2):101-107.
[16]Ziaja.Henry J.Total product quality process model[C].Forty-Fourth Annual Quality Congress Transactions,San Francisco 1990,P:335-341.
[17]王美清,唐晓青.产品协同设计质量控制模型研究[J].计算机集成制造系统,2006,12(5):654-658.
[18]M.朱兰(美),质量控制手册[M].上海:上海人民出版社,1987,35-62
[19]刘大明,ISO9000与质量改进[M],广州:广东人民出版社,1996,33-45
[20]罗国英,林修齐主编,2000版ISO/DIS9000族标准质量管理体系教程[M],北京:中国经济出版社,2000,26-65
[21]R.P.Mohanty,N.Dahanayka.,Process improvement:evaluation of methods Quaky Process[J],Sept.1989,9:45-58
[22]Jiju Autony,Mike Karye and Anlreas Frangou.A strategic methodoluse of advanced statistical quality improvement[J],techniques Magazine,1998,10(3):169-176
[23]Liscomb P E,Quanlity system development-managing implementation of continuous quanlity improvement[C],Las Vegas NV:48th Annual Quality Congress.,May 1994,548-557
[24]Parvey D E.Sequential application of advanced quality tools[C],Las Vegas NV:48th Annual Quality Congress,May 1994,423-429
[25]Burton Gerald C.DOE and SPC on the shop floor-A case study[C],Boston MA:47th Annual Quality Congress May 1993,739-745
[26]Zayas-Castro Jose L,Mundo-Carsia.Victor Yield improvement through SPC and DOE[C],Nashville TN:46th Annual Quality Congress May 1994,444-450
[27]Hale-Bennet Cynthia,Lin Dennis K[J].From SPC to DOE:A case study at Meco Inc Quality Engineer,March 1997,9(3):489-502
[28]Espino-Ranirez Rosa M.,Allison Jack T.Tuna canning improvement through DOE,SPC[J].Nashville TN:46th Annual Quality Congress May 1993,451-457
[29]Mikel J.Harry.Six Sigma:A breakthrough strategy for profitability[J].Quality Process Mav 1998,5:60-64
[30]何祯,黑带计划与连续质量改进[J],中国质量,1999 C9):29-31.
[31]RoderickAMunro.Linlking six sigma with QS9000[J],Quality Progress,May 2000,5:47-53
[32]Alan W.H.Grant,Leonard A.Schlesinger.Realize your customers' full profit potential[J],Harvard Business Review,September-October 1995:59-72
[33]Kresta J V,MacGregor J F,Martin T E.Multivariate statistical monitoring of process operating performance[J],The Canadian J of Chem Eng,1991,69(2):35-47
[34]Davenport T H.Process Innovation:Reengineering Work through Information Technology[J],Harvard Business School Press,1993
[35]唐任仲,O.Mejabi.过程管理技术[J].杭州:浙江大学学报(工学版),2002.5(3):256-259
[36]Workflow Management coalition.The workflow reference model[J].WFMC TC00-1003,1994
[37]陈育靖.全面品质管理参考模式建立之研究[D].中国台湾国立台北科技大学生产系统工程与管理研究所硕士学位论文.2000.6
[39]肖智军,党新民,刘胜军.精益生产方式JIT[M].深圳:海天出版社.2002.8
[40].杨世锡,焦卫东,吴昭同.基于独立分量分析特征提取的复合神经网络故障诊断法[[J].振动工程学报,2004,17(4):438-442.
[41].赵海东,缪旭东,吕世聘.基于神经网络的军用飞机故障预报系统研究闭[J].系统工程与电子技术,2003,25(7):894-896.
[42].朱三文,席泽敏,薛林.基于神经网络的雷达故障诊断专家系统[[J].机械与电子,2004(7):75-77.
[43].谢平一种用于故障诊断的演化小波神经网络[J].系统工程与电子技术,2003,25(6):742-745.
[44].吴桂峰,翟玉庆,陈虹,曹卫.基于小波一神经网络的电机振动故障诊断[J].控制工程,2004,11(2):152-154,176.
[45].赵宏,廖忠.基于遗传网络的提升设备故障诊断研究[[J].煤矿机械,2004(8):121-123.
[46].曲正伟,王云静.基于混沌神经网络的电机故障诊断[[J].控制工程,2003,10(4):302-345.
[47].侯祥林,李永强,虞和济,纪盛青.非线性机械设备系统的分形神经网络诊断方法[[J].振动工程学报、2001,14(2):220-223.
[48]周志华,陈兆乾,骆斌,陈世福.基于混合学习算法IHMCAP的故障诊断模型[[J].自动化学报2000,26(4):529-532.
[49].Xu Z,Zhao H.Design of fault detection and isolation via wavelet analysis and neural network[A].IEEE International,Symposium on Intelligent Control[C].Vancouver,Canada.2002.467-472.
[50]Jack L B,Nandi A K.Fault detection using support vector machines and artificial neural networks,augmented by genetic algorithms[J].Mechanical Systems and Signal Processing,2002,13(2-3):373-390.
[51]Paul M Frank,Birgit Koppen-Seliger.Fuzzy Logic and Neural Network Application to Fault Diagnosis[J].International Journal of Approximate Reasoning,1997,16:67-88.
[52].张苗苗,谢剑英,方敏,徐国良.基于模糊神经网络的智能诊断系统的研制[J].计算机工程,1999,25(3):53-54,74.
[53].David B Leake,Andrew Kinley,David Wilson.Case-Based CBR:Capturing and Resuing Reasoning About Case Adaptation[J].International Journal of Expert Systems,1997,10(2):197-213.
[54].张晓阳,孙宇,张荣涛,郭兴华.基于实例的故障诊断方法研究与应用[[J].南京理工大学学报,2003,27(1):64-67.
[55].史定华,王松瑞.故障树分析技术方法和理论[M].北京:北京师范大学出版社.1993.
[56].金星,洪延姬,武江涛,沈怀荣.基于故障树的智能型故障诊断系统[[J].宇航学报,2001,22(3):111-113.
[57].Bonaldi E L,Borges da Silva L E,Lambert-Tomes G,Ollveira L E L,Assuncao F O.Using Rough Sets Techniques as a Fault Diagnosis Classifier for Induction Motors[A]. IEEE Center[C]. 2002.3383-3388.
[58].Shusaku Tsumoto,Hiroshi Tanaka. Extraction of Domain Knowledge from Databases based on Rough set Theory[A]. IEEE Center. 1996. 748-754.
[59].Khoo L P, Tor S B, Zhai L Y. A Rough-Set-Based Approach for Classification and Rule Induction[J]. International 3ournal of Advanced Manufacturing Technology, 1999, 15: 438-444.
[60].Uirich Rembold. Computer Integrated Manufacturing Technology and System[M]. New York and Basel: Marcel Dekker,INC, 1985
[61].Syohei Ishizu. A conceptuall framework for quality information systems. IEMC 96, Managing Virtual Enterprises, 1996: p217-220,
[62]Dessouky MI, Kapoor SG A Methodology for Integrated Quality System[J]. Journal of Engineering for Industry, A S M E, 1987: 241-247
[63]J.D. Tannock, etc. Strategies for integrated systems in quality control. Proc. Of 4th European Conf. Automated Manufacturing, 1987,(5): 213-222
[64]Vosniakos G, Wang J. A software system framework for planning and operation of quality control in discrete part manufacturing[J]. Computer Integrated Manufacturing Systems, 1997,10(1): 9-25
[65] Jose A. Heredia, Ip-Shing Fan. A Framework for an Integrated Quality System[J].Journal of Materials Processing Technology, 1996,61(5): 195-200
[66] Chang S I, Visser JJ. A framework for distributed quality control[J]. Computer & Industrial Engineering,1998,35(1,2): 181-18
[67] Wang Z Y,Rajurkar K P, Kapoor A. Architecture for agile manufacturing and its interface with computer integrated manufacturing[J]. Journal of Materials Processing Technology, 1996,61 (3): 99-103
[68] Yang H P, Zeng Z L, et al. Distributed Quality Assurance System Framework for Agile Manufacturing[C]. Proceeding of ICCIM'97, Singapore, 1997
[69] Kwai-Sang Chin, Guijiang Duan, Xiaoqing Tang. A computer integrated framework for global quality chain management[J]. Int J Adv Manuf Technol,2006,27: 547-560
[70]唐晓青,段桂江.面向全球化制造的协同质量链管理[J].中国质量,2002(9):25-27
[71]段桂江,等.CIMS环境下集成质量信息系统框架模型[J].计算机集成制造系统-CIMS,1997,3(5):25-28
[72]段桂江,唐晓青,汪叔淳.面向现代制造企业的集成质量系统模型[J].中国机械工程,1999,10(3):292-295
[73]廖东,张建勋,万军等.集成质量系统发展战略的探讨[J].重庆大学学报,1999,22(5):17-20
[74]孔造杰.CIMS环境下质量信息系统框架模型的比较研究[J].计算机集成制造系统,2000,4(2):85.88
[75]杨旭,王东鹏,马玉林等.基于CIMS环境下的质量管理信息系统的设计[J].高技术通讯,2000,8:70-74
[76]杨鸿鹏,赵丽萍,曾晓流等.敏捷制造模式下质量保证系统体系结构研究[J].计算机集成制造系统.1998,6:31-33
[77]杨鸿鹏,赵丽萍,林志航等.敏捷制造模式下的分布式计算机质量信息系统[J].计算机集成制造系统.1998,8:34-39
[78]李春芝.支持并行设计的质量信息模型研究[D].西北工业大学,2005
[79]孙蓓蓓.面向敏捷制造环境的集成质量系统的研究[D].南京:东南大学,2001
[80]李孟清,陈志祥.基于因特网的NGMS质量管理与质量保证系统[J].华中理工大学学报,1999,27(6):51-53
[81]罗书强,何玉林,贾彦民等.分散网络化制造模式下集成质量系统的研究[J].制造业自动化,2000,12(12):8-12
[82]洪著财.基于XML的动态质量信息系统的研究[D].东南大学博士学位论文,2004
[83]张志胜.基于XML的动态质量信息系统关键技术研究[D].东南大学博士学位论文,2004
[84]吴军,邓超,等.面向PLM的协同质量管理系统[J].华中科技大学学报(自然科学版),2006,34(6):74-76
[85]张公绪主编.两种质量诊断理论及其应用[M].科学出版社,2000
[86]余忠华,吴昭同.面向小批量制造过程的质量控制方法研究[J].机械工程学报,2001,8(8):60-64.
[87]余忠华.面向多品种小批量制造过程的SPC策略、方法与辅助系统的研究[D].杭州:浙江大学,1999
[88]殷建军.面向多品种、小批量制造环境的过程质量监控方法及嵌入式系统的研究[D].杭州:浙江大学,2004
[89]殷建军,余忠华,吴昭同.基于现场总线的嵌入式SPC系统研究[J].浙江大学学报,2004,(6)
[90]张文生.小批量生产过程中产品质量控制的研究[J].系统工程理论与实践,2002,(5):24-30
[91]Guh R S,Tannock J D.IntelliSPC:a hybrid intelligent tool for online economical statistical process control[J].Expert Systems with Applications,1999,17:195-212
[92]Stumpff,Milton A.Statistical process control will improve your quality and profits[J].Ceramic Engineering and Science Proceedings,1997:p384-388
[93]M.M.Salti and A.Statham,"A Review of The Literature on the Use of SPC in Batch Production",Quality and Relibablity Engineering International V10,1994,pp49-61
[93]Agrawal R,Lawless J F and Mackay R J.Analysis of Variation Transmission in Manufacturing Processes-Part Ⅱ.Quality Technol.,1999,31(2):143-154
[94]余忠华,吴昭同,面向小批量制造过程的质量控制方法研究[J],机械工程学报,2001年,第8期
[95]Hu,S.J.,Stream-of-Variation Theory for Automotive Body Assembly,Annals of the CIRP,Vol.46,No.1,Mantripragada,R.and Whitney,D.E.,"Modeling and Controlling Variation Propagation in Mechanical Assemblies Using State Transition Models," IEEE Transactions on Robotics and Automation,1999,15
[96]杜世昌 奚立峰,潘尔顺 串并联混合式多阶段制造系统产品质量建模与控制[J],计算机集成制造系统,2006年,第7期
[97]Mantripragada,R.and Whitney,D.E.Modeling and Controlling Variation Propagation in Mechanical Assemblies Using State Transition Models[C],IEEE Transactions on Robotics and Automation,1999,15
[98]Q.Huang.,J.Shi.,J.Yuan.,Part Dimensional Error and Its Propagation Modeling in Multi-Operational Machining Processes,ASME Journal of Manufacturing Science and Engineering,MAY 2003,Vol.125/255
[99]S.Zhou,Q.Huang,and J.Shi.,State Space Modeling of Dimensional Variation Propagation in Multistage Machining Process Using Differential Motion Vectors,IEEE Transactions on Robotics and Automation,Vol.19,no.2,April 2003
[100]Ding,Y.,Shi,J.,and Ceglarek,D.,Diagnosability Analysis of Multi-station Manufacturing Processes,ASME Transactions,Journal of Dynamics Systems,Measurement,and Control,2002,Vol.124,pp 1-13.
[101]赵家黎 郭伟 牛占文等.基于误差流理论的多工位装配过程质量稳定[J],机械工程学报,2006年第11期.
[102]Naruemon W,David W.Coit,Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty,Reliability Engineering and System Safety 92(2007) 395-407
[103]Dan M.Shalev,Joseph Tiran,Condition-based fault tree analysis(CBFTA):A new method for improved fault tree analysis(FTA),reliability and safety calculations,Reliability Engineering and System Safety 92(2007) 1231-1241
[104]K.W.Chau,Reliability and performance-based design by artificial neural network,Advances in Engineering Software 38(2007) 145-149
[105]Anjana Meel,Warren D.Seide,Plant-specific dynamic failure assessment using Bayesian theory,Chemical Engineering Science 61(2006) 7036-705
[106]Christian Delvosalle,et al.ARAMIS project:A comprehensive methodology for the identification of reference accident scenarios in process industries,Journal of Hazardous Materials 130(2006) 200-219
[107]V.B.KRENG,CHIA-HUA CHANG,Bayesian Network Based Multiagent System-Application in E-Marketplace,Computers and Mathematics with Applications 46(2003) 429-444
[108]周祖德.现代机械制造系统的监控与故障诊断.武汉:华中理工大学出版 社,1998
[109]蒋剑飞,史宪铭,武小悦,基于设备状态管理的制造系统可靠性仿真,计算机仿真,2005年8月,第22卷第8期
[110]R.J.Kuo,Multi-sensor integration for on-line tool wear estimation through artificial neural networks and fuzzy neural network,Engineering Applications of Artificial Intelligence 13(2000) 249-261
[111]Cenk(U|¨)ndeyl,Eric Tatara,Ali Cma,Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations,Journal of Biotechnology 108(2004)
[112]张映峰,江平宇,基于Web的CNC设备e一化研究,计算机集成制造系统,2004,10(4)
[113]唐晓青,现代制造模式下的质量管理,科学出版社,2004
[114]E.P.Paladini,An expert system approach to quality control,Expert Systems with Applications,2000(18)
[118]刘锋.基于加工特征的回转类零件快速数控编程技术研究[D].南京航空航天大学,2007
[119]蒋新宇.基于特征的刀具智能选取及其数据管理技术研究[D].浙江大学,2003
[120]陈皓.基于特征技术的工艺决策系统开发[D].湘潭大学,2006
[121]丘宏俊.基于知识的飞机装配工艺设计关键技术研究[D].西北工业大学,2006
[132]姜南,唐晓青.基于作业质量成本的质量改进决策模型研究[J].计算机集成制造系统-CIMS.Vol.9 No.10:849-853
[134]Liao S H.Knowledge management technologies and applications-literature review form 1995 to 2002[J].Expert Systems with Applications,2003,25(2):155-164
[135]Nonaka I,Takeuchi H.The knowledge-creating company:How Japanese Companies Create the Dynamics of Innovation[M].Oxford:Oxford University Press,1995
[136]A.Preece,et.al.Better knowledge management through knowledge engineering [J].IEEE Intelligent Systems,2001,Jan./Feb.,36-44
[137]Dieng R,Corby O,Giboin A,Ribiere M.Methods and Tools for Corporate Knowledge Management[J].International Joural of Human Computer Studies,1999,51(3):97-105
[138]王君.一种基于知识地图集的知识管理系统模型框架[J].工业工程与管理,2003,(6):10-14
[16]Kreng V B,Tsai C M.The construct and application of Knowledge diffusion model[J].Expert Systems with Applications,2003,25(2):177-186
[139]乐飞红,陈锐.企业知识管理实现流程中知识地图的几个问题[J].图书情报知识,2000,(3):15-17
[140]AI-Rasheedi,Hussain;.Chapman,Terrance V;Oskay,Mehmet;AI-Khamees,Waleed,Using Knowledge Mapping Techniques To Build a Living Full-Field Model of an Oil Field[J],Proceedings of the Middle East Oil Show,2003,13:985-992
[141]Chung,GK.W.K(UniversityofCalifomia);O'Neil,H.F.Jr.;Herl,H.E.Use of computer-based collaborative knowledge mapping to measure team processes and team outcomes[J],Computers in Human Behavior,1999,15(3):463-493
[142]Vail E F.What is A Knowledge Map?[EB/OL].http://www.km-review.com,2002-08-29[143]邓三鸿.知识地图的构建与使用[D].南京:南京大学,2003
[144]Martin J.Eppler.Making Knowledge Visible Through Intranet Knowledge Maps:Concepts,Elements,Cases[J].Proceedings of the 34th Hawaii International Conference on System Sciences,2001
[149]Fiona Zhao,Xun Xu,S.Q.Xie.Computer-Aided Inspection Planning-The state of the art.Acta Automatica Sinica,Volume 35,Issue 3,March 2009,Pages 233-238
[150]Martin Oppermann,Wilfried Sauer,Heinz Wohlrabe.Optimization of Inspection Strategies by Use of Quality Cost Model and SPC.ISSE,Calimanesti-Caciulata,Romania,May 5-9,2004
[151]N.V.R.Naidu.Mathematical model for quality cost optimization.Robotics and Computer-integrated Manufacturing.Volume 24,Issue 6,December 2008,Pages 811-815
[152]Rodrigo J.P.Ferreira,Adiel Teixeira de Almeida.A multi-criteria decision model to determine inspection intervals of condition monitoring based on delay time analysis.Reliability Engineering & System Safety,Volume 94,Issue 5,May 2009,Pages 905-912
[153]Jie C,GreinerR,Kelly J,et al.Learning Bayesian network from data:An information-theory based approach[J].Artificial Intelligence,2002,137:43-90.
[154]胡笑旋.贝叶斯网建模技术及其在决策中的应用[D].合肥工业大学博士学位论文,2006.
[155]Xiang Y.A probabilistic framework for cooperative multi-agent distributed interpretation and optimization of communication[J].Artificial Intelligence,2006,87(1-2):295-342.
[156]杨善林,胡小建,马溪骏.DIDSS环境下信息agent系统任务规范的分解[J].系统工程学报.2004,Vol.19 No.5:489-495
[157]胡玉胜,涂序彦,崔晓瑜等.基于贝叶斯网的不确定性知识的推理方法[J].计算机集成制造系统-CIMS.2007,7(12):65-68.
[158]王体春,钟诗胜,王威.基于公理化设计的多级实例知识重用技术研究[J].计算机集成制造系统-CIMS.2008,14(5):833-840.
[159]胡玉胜,涂序彦,崔晓瑜等.基于贝叶斯网的不确定性知识的推理方法[J].计算机集成制造系统-CIMS.2007,7(12):65-68.
[160]杨善林,胡笑旋.融合知识和数据的贝叶斯网络构造.模式识别与人工智能,2006,19(1):31-34.
[161]杨善林,胡笑旋.基于案例和规则推理的贝叶斯网建模.哈尔滨工业大学学报(自然科学版),2006,38(10):1644-1648
[162]张曙,《中国制造企业怎样进入二十一世纪》,国防工业出版社,1997
[163]陶必悦,周有华,我国轴承产品及其关键技术发展预测(之一),轴承工业,2000年,9月.
[164]Stumpff Milton A.Statistical process control will improve your quality and profits,Ceramic Engineer and Science and Reliability Engineering International, 1991,7:437-448.
[165]吴晓蓉,汪乐,涂时亮 互连网技术在嵌入式系统中的实现,计算机工程,2001年4月,第27卷,第4期:1-4。
[166]殷建军.面向多品种、小批量制造环境的过程质量监控方法及嵌入式系统的研究[D].杭州:浙江大学,2004
[167]殷建军,余忠华,吴昭同.基于现场总线的嵌入式SPC系统研究[J].浙江大学学报,2004,(6):1422-1427
[2]Guh R S,Tannock J D.IntelliSPC:a hybrid intelligent tool for on-line economical statistical process control[J].Expert Systems with Applications,1999,17:195-212.
[3]Devor R.E.,Chang T.h.and Sutherland J.W.Statistical Quality Design and Control[J].Macmillan Publishing Company,1992.
[4]Keats J B.,Montgomery D.C.Statistical Applications in Process Control[C].New York:Marcel Dekker,1996.
[5]Montgomery D.C.Introduction to Statistical Quality Control,3rd ed.NewYork[C]:John Wiley & Sons,1996.
[6]Dale H.Besterfield And Et Al.,Total Quality Management(2nd Ed),Upper Saddle River,N.J.:Prentice Hall,1999.
[7]David L.Goetsch,Stanley B.Davis Quality Management:Introduction To Total Quality Management For Production,Processing,And Services(3rd Ed).Pper Saddle River,NJ:Prentice Hall,2000.
[8]Tannock J.D.Automating Quality Systems.CHAPMAN &HALL,1992.
[9]麦肯锡公司,世界质量管理水平的发展[OL],http://www.zhkc.com.cn/zhuanjia5.htm,2004.
[10]国家自然科学基金委员会工程与材料料学部机械工程科学技术学术前沿编委会[M]。机械工程科学技术前沿.北京:机械工业出版社,1996.
[11]Feigonbaum,A.V.《全面质量管理》[M]。机械工业出版社,1991,6.
[12]王丽颖.小批量工序质量控制方法及其若干关键技术的研究(D).大连交通大学,2007.
[13]乐清洪.智能工序质量控制的理论与方法研究[D].西北工业大学,2002.
[14]吴德会.基于质量信息集成的智能质量控制技术研究[D].合肥工业大 学,2006.
[15]谢红卫等.典型人因可靠性分析方法评述[J].国防科技大学学报.2007,29(2):101-107.
[16]Ziaja.Henry J.Total product quality process model[C].Forty-Fourth Annual Quality Congress Transactions,San Francisco 1990,P:335-341.
[17]王美清,唐晓青.产品协同设计质量控制模型研究[J].计算机集成制造系统,2006,12(5):654-658.
[18]M.朱兰(美),质量控制手册[M].上海:上海人民出版社,1987,35-62
[19]刘大明,ISO9000与质量改进[M],广州:广东人民出版社,1996,33-45
[20]罗国英,林修齐主编,2000版ISO/DIS9000族标准质量管理体系教程[M],北京:中国经济出版社,2000,26-65
[21]R.P.Mohanty,N.Dahanayka.,Process improvement:evaluation of methods Quaky Process[J],Sept.1989,9:45-58
[22]Jiju Autony,Mike Karye and Anlreas Frangou.A strategic methodoluse of advanced statistical quality improvement[J],techniques Magazine,1998,10(3):169-176
[23]Liscomb P E,Quanlity system development-managing implementation of continuous quanlity improvement[C],Las Vegas NV:48th Annual Quality Congress.,May 1994,548-557
[24]Parvey D E.Sequential application of advanced quality tools[C],Las Vegas NV:48th Annual Quality Congress,May 1994,423-429
[25]Burton Gerald C.DOE and SPC on the shop floor-A case study[C],Boston MA:47th Annual Quality Congress May 1993,739-745
[26]Zayas-Castro Jose L,Mundo-Carsia.Victor Yield improvement through SPC and DOE[C],Nashville TN:46th Annual Quality Congress May 1994,444-450
[27]Hale-Bennet Cynthia,Lin Dennis K[J].From SPC to DOE:A case study at Meco Inc Quality Engineer,March 1997,9(3):489-502
[28]Espino-Ranirez Rosa M.,Allison Jack T.Tuna canning improvement through DOE,SPC[J].Nashville TN:46th Annual Quality Congress May 1993,451-457
[29]Mikel J.Harry.Six Sigma:A breakthrough strategy for profitability[J].Quality Process Mav 1998,5:60-64
[30]何祯,黑带计划与连续质量改进[J],中国质量,1999 C9):29-31.
[31]RoderickAMunro.Linlking six sigma with QS9000[J],Quality Progress,May 2000,5:47-53
[32]Alan W.H.Grant,Leonard A.Schlesinger.Realize your customers' full profit potential[J],Harvard Business Review,September-October 1995:59-72
[33]Kresta J V,MacGregor J F,Martin T E.Multivariate statistical monitoring of process operating performance[J],The Canadian J of Chem Eng,1991,69(2):35-47
[34]Davenport T H.Process Innovation:Reengineering Work through Information Technology[J],Harvard Business School Press,1993
[35]唐任仲,O.Mejabi.过程管理技术[J].杭州:浙江大学学报(工学版),2002.5(3):256-259
[36]Workflow Management coalition.The workflow reference model[J].WFMC TC00-1003,1994
[37]陈育靖.全面品质管理参考模式建立之研究[D].中国台湾国立台北科技大学生产系统工程与管理研究所硕士学位论文.2000.6
[39]肖智军,党新民,刘胜军.精益生产方式JIT[M].深圳:海天出版社.2002.8
[40].杨世锡,焦卫东,吴昭同.基于独立分量分析特征提取的复合神经网络故障诊断法[[J].振动工程学报,2004,17(4):438-442.
[41].赵海东,缪旭东,吕世聘.基于神经网络的军用飞机故障预报系统研究闭[J].系统工程与电子技术,2003,25(7):894-896.
[42].朱三文,席泽敏,薛林.基于神经网络的雷达故障诊断专家系统[[J].机械与电子,2004(7):75-77.
[43].谢平一种用于故障诊断的演化小波神经网络[J].系统工程与电子技术,2003,25(6):742-745.
[44].吴桂峰,翟玉庆,陈虹,曹卫.基于小波一神经网络的电机振动故障诊断[J].控制工程,2004,11(2):152-154,176.
[45].赵宏,廖忠.基于遗传网络的提升设备故障诊断研究[[J].煤矿机械,2004(8):121-123.
[46].曲正伟,王云静.基于混沌神经网络的电机故障诊断[[J].控制工程,2003,10(4):302-345.
[47].侯祥林,李永强,虞和济,纪盛青.非线性机械设备系统的分形神经网络诊断方法[[J].振动工程学报、2001,14(2):220-223.
[48]周志华,陈兆乾,骆斌,陈世福.基于混合学习算法IHMCAP的故障诊断模型[[J].自动化学报2000,26(4):529-532.
[49].Xu Z,Zhao H.Design of fault detection and isolation via wavelet analysis and neural network[A].IEEE International,Symposium on Intelligent Control[C].Vancouver,Canada.2002.467-472.
[50]Jack L B,Nandi A K.Fault detection using support vector machines and artificial neural networks,augmented by genetic algorithms[J].Mechanical Systems and Signal Processing,2002,13(2-3):373-390.
[51]Paul M Frank,Birgit Koppen-Seliger.Fuzzy Logic and Neural Network Application to Fault Diagnosis[J].International Journal of Approximate Reasoning,1997,16:67-88.
[52].张苗苗,谢剑英,方敏,徐国良.基于模糊神经网络的智能诊断系统的研制[J].计算机工程,1999,25(3):53-54,74.
[53].David B Leake,Andrew Kinley,David Wilson.Case-Based CBR:Capturing and Resuing Reasoning About Case Adaptation[J].International Journal of Expert Systems,1997,10(2):197-213.
[54].张晓阳,孙宇,张荣涛,郭兴华.基于实例的故障诊断方法研究与应用[[J].南京理工大学学报,2003,27(1):64-67.
[55].史定华,王松瑞.故障树分析技术方法和理论[M].北京:北京师范大学出版社.1993.
[56].金星,洪延姬,武江涛,沈怀荣.基于故障树的智能型故障诊断系统[[J].宇航学报,2001,22(3):111-113.
[57].Bonaldi E L,Borges da Silva L E,Lambert-Tomes G,Ollveira L E L,Assuncao F O.Using Rough Sets Techniques as a Fault Diagnosis Classifier for Induction Motors[A]. IEEE Center[C]. 2002.3383-3388.
[58].Shusaku Tsumoto,Hiroshi Tanaka. Extraction of Domain Knowledge from Databases based on Rough set Theory[A]. IEEE Center. 1996. 748-754.
[59].Khoo L P, Tor S B, Zhai L Y. A Rough-Set-Based Approach for Classification and Rule Induction[J]. International 3ournal of Advanced Manufacturing Technology, 1999, 15: 438-444.
[60].Uirich Rembold. Computer Integrated Manufacturing Technology and System[M]. New York and Basel: Marcel Dekker,INC, 1985
[61].Syohei Ishizu. A conceptuall framework for quality information systems. IEMC 96, Managing Virtual Enterprises, 1996: p217-220,
[62]Dessouky MI, Kapoor SG A Methodology for Integrated Quality System[J]. Journal of Engineering for Industry, A S M E, 1987: 241-247
[63]J.D. Tannock, etc. Strategies for integrated systems in quality control. Proc. Of 4th European Conf. Automated Manufacturing, 1987,(5): 213-222
[64]Vosniakos G, Wang J. A software system framework for planning and operation of quality control in discrete part manufacturing[J]. Computer Integrated Manufacturing Systems, 1997,10(1): 9-25
[65] Jose A. Heredia, Ip-Shing Fan. A Framework for an Integrated Quality System[J].Journal of Materials Processing Technology, 1996,61(5): 195-200
[66] Chang S I, Visser JJ. A framework for distributed quality control[J]. Computer & Industrial Engineering,1998,35(1,2): 181-18
[67] Wang Z Y,Rajurkar K P, Kapoor A. Architecture for agile manufacturing and its interface with computer integrated manufacturing[J]. Journal of Materials Processing Technology, 1996,61 (3): 99-103
[68] Yang H P, Zeng Z L, et al. Distributed Quality Assurance System Framework for Agile Manufacturing[C]. Proceeding of ICCIM'97, Singapore, 1997
[69] Kwai-Sang Chin, Guijiang Duan, Xiaoqing Tang. A computer integrated framework for global quality chain management[J]. Int J Adv Manuf Technol,2006,27: 547-560
[70]唐晓青,段桂江.面向全球化制造的协同质量链管理[J].中国质量,2002(9):25-27
[71]段桂江,等.CIMS环境下集成质量信息系统框架模型[J].计算机集成制造系统-CIMS,1997,3(5):25-28
[72]段桂江,唐晓青,汪叔淳.面向现代制造企业的集成质量系统模型[J].中国机械工程,1999,10(3):292-295
[73]廖东,张建勋,万军等.集成质量系统发展战略的探讨[J].重庆大学学报,1999,22(5):17-20
[74]孔造杰.CIMS环境下质量信息系统框架模型的比较研究[J].计算机集成制造系统,2000,4(2):85.88
[75]杨旭,王东鹏,马玉林等.基于CIMS环境下的质量管理信息系统的设计[J].高技术通讯,2000,8:70-74
[76]杨鸿鹏,赵丽萍,曾晓流等.敏捷制造模式下质量保证系统体系结构研究[J].计算机集成制造系统.1998,6:31-33
[77]杨鸿鹏,赵丽萍,林志航等.敏捷制造模式下的分布式计算机质量信息系统[J].计算机集成制造系统.1998,8:34-39
[78]李春芝.支持并行设计的质量信息模型研究[D].西北工业大学,2005
[79]孙蓓蓓.面向敏捷制造环境的集成质量系统的研究[D].南京:东南大学,2001
[80]李孟清,陈志祥.基于因特网的NGMS质量管理与质量保证系统[J].华中理工大学学报,1999,27(6):51-53
[81]罗书强,何玉林,贾彦民等.分散网络化制造模式下集成质量系统的研究[J].制造业自动化,2000,12(12):8-12
[82]洪著财.基于XML的动态质量信息系统的研究[D].东南大学博士学位论文,2004
[83]张志胜.基于XML的动态质量信息系统关键技术研究[D].东南大学博士学位论文,2004
[84]吴军,邓超,等.面向PLM的协同质量管理系统[J].华中科技大学学报(自然科学版),2006,34(6):74-76
[85]张公绪主编.两种质量诊断理论及其应用[M].科学出版社,2000
[86]余忠华,吴昭同.面向小批量制造过程的质量控制方法研究[J].机械工程学报,2001,8(8):60-64.
[87]余忠华.面向多品种小批量制造过程的SPC策略、方法与辅助系统的研究[D].杭州:浙江大学,1999
[88]殷建军.面向多品种、小批量制造环境的过程质量监控方法及嵌入式系统的研究[D].杭州:浙江大学,2004
[89]殷建军,余忠华,吴昭同.基于现场总线的嵌入式SPC系统研究[J].浙江大学学报,2004,(6)
[90]张文生.小批量生产过程中产品质量控制的研究[J].系统工程理论与实践,2002,(5):24-30
[91]Guh R S,Tannock J D.IntelliSPC:a hybrid intelligent tool for online economical statistical process control[J].Expert Systems with Applications,1999,17:195-212
[92]Stumpff,Milton A.Statistical process control will improve your quality and profits[J].Ceramic Engineering and Science Proceedings,1997:p384-388
[93]M.M.Salti and A.Statham,"A Review of The Literature on the Use of SPC in Batch Production",Quality and Relibablity Engineering International V10,1994,pp49-61
[93]Agrawal R,Lawless J F and Mackay R J.Analysis of Variation Transmission in Manufacturing Processes-Part Ⅱ.Quality Technol.,1999,31(2):143-154
[94]余忠华,吴昭同,面向小批量制造过程的质量控制方法研究[J],机械工程学报,2001年,第8期
[95]Hu,S.J.,Stream-of-Variation Theory for Automotive Body Assembly,Annals of the CIRP,Vol.46,No.1,Mantripragada,R.and Whitney,D.E.,"Modeling and Controlling Variation Propagation in Mechanical Assemblies Using State Transition Models," IEEE Transactions on Robotics and Automation,1999,15
[96]杜世昌 奚立峰,潘尔顺 串并联混合式多阶段制造系统产品质量建模与控制[J],计算机集成制造系统,2006年,第7期
[97]Mantripragada,R.and Whitney,D.E.Modeling and Controlling Variation Propagation in Mechanical Assemblies Using State Transition Models[C],IEEE Transactions on Robotics and Automation,1999,15
[98]Q.Huang.,J.Shi.,J.Yuan.,Part Dimensional Error and Its Propagation Modeling in Multi-Operational Machining Processes,ASME Journal of Manufacturing Science and Engineering,MAY 2003,Vol.125/255
[99]S.Zhou,Q.Huang,and J.Shi.,State Space Modeling of Dimensional Variation Propagation in Multistage Machining Process Using Differential Motion Vectors,IEEE Transactions on Robotics and Automation,Vol.19,no.2,April 2003
[100]Ding,Y.,Shi,J.,and Ceglarek,D.,Diagnosability Analysis of Multi-station Manufacturing Processes,ASME Transactions,Journal of Dynamics Systems,Measurement,and Control,2002,Vol.124,pp 1-13.
[101]赵家黎 郭伟 牛占文等.基于误差流理论的多工位装配过程质量稳定[J],机械工程学报,2006年第11期.
[102]Naruemon W,David W.Coit,Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty,Reliability Engineering and System Safety 92(2007) 395-407
[103]Dan M.Shalev,Joseph Tiran,Condition-based fault tree analysis(CBFTA):A new method for improved fault tree analysis(FTA),reliability and safety calculations,Reliability Engineering and System Safety 92(2007) 1231-1241
[104]K.W.Chau,Reliability and performance-based design by artificial neural network,Advances in Engineering Software 38(2007) 145-149
[105]Anjana Meel,Warren D.Seide,Plant-specific dynamic failure assessment using Bayesian theory,Chemical Engineering Science 61(2006) 7036-705
[106]Christian Delvosalle,et al.ARAMIS project:A comprehensive methodology for the identification of reference accident scenarios in process industries,Journal of Hazardous Materials 130(2006) 200-219
[107]V.B.KRENG,CHIA-HUA CHANG,Bayesian Network Based Multiagent System-Application in E-Marketplace,Computers and Mathematics with Applications 46(2003) 429-444
[108]周祖德.现代机械制造系统的监控与故障诊断.武汉:华中理工大学出版 社,1998
[109]蒋剑飞,史宪铭,武小悦,基于设备状态管理的制造系统可靠性仿真,计算机仿真,2005年8月,第22卷第8期
[110]R.J.Kuo,Multi-sensor integration for on-line tool wear estimation through artificial neural networks and fuzzy neural network,Engineering Applications of Artificial Intelligence 13(2000) 249-261
[111]Cenk(U|¨)ndeyl,Eric Tatara,Ali Cma,Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations,Journal of Biotechnology 108(2004)
[112]张映峰,江平宇,基于Web的CNC设备e一化研究,计算机集成制造系统,2004,10(4)
[113]唐晓青,现代制造模式下的质量管理,科学出版社,2004
[114]E.P.Paladini,An expert system approach to quality control,Expert Systems with Applications,2000(18)
[118]刘锋.基于加工特征的回转类零件快速数控编程技术研究[D].南京航空航天大学,2007
[119]蒋新宇.基于特征的刀具智能选取及其数据管理技术研究[D].浙江大学,2003
[120]陈皓.基于特征技术的工艺决策系统开发[D].湘潭大学,2006
[121]丘宏俊.基于知识的飞机装配工艺设计关键技术研究[D].西北工业大学,2006
[132]姜南,唐晓青.基于作业质量成本的质量改进决策模型研究[J].计算机集成制造系统-CIMS.Vol.9 No.10:849-853
[134]Liao S H.Knowledge management technologies and applications-literature review form 1995 to 2002[J].Expert Systems with Applications,2003,25(2):155-164
[135]Nonaka I,Takeuchi H.The knowledge-creating company:How Japanese Companies Create the Dynamics of Innovation[M].Oxford:Oxford University Press,1995
[136]A.Preece,et.al.Better knowledge management through knowledge engineering [J].IEEE Intelligent Systems,2001,Jan./Feb.,36-44
[137]Dieng R,Corby O,Giboin A,Ribiere M.Methods and Tools for Corporate Knowledge Management[J].International Joural of Human Computer Studies,1999,51(3):97-105
[138]王君.一种基于知识地图集的知识管理系统模型框架[J].工业工程与管理,2003,(6):10-14
[16]Kreng V B,Tsai C M.The construct and application of Knowledge diffusion model[J].Expert Systems with Applications,2003,25(2):177-186
[139]乐飞红,陈锐.企业知识管理实现流程中知识地图的几个问题[J].图书情报知识,2000,(3):15-17
[140]AI-Rasheedi,Hussain;.Chapman,Terrance V;Oskay,Mehmet;AI-Khamees,Waleed,Using Knowledge Mapping Techniques To Build a Living Full-Field Model of an Oil Field[J],Proceedings of the Middle East Oil Show,2003,13:985-992
[141]Chung,GK.W.K(UniversityofCalifomia);O'Neil,H.F.Jr.;Herl,H.E.Use of computer-based collaborative knowledge mapping to measure team processes and team outcomes[J],Computers in Human Behavior,1999,15(3):463-493
[142]Vail E F.What is A Knowledge Map?[EB/OL].http://www.km-review.com,2002-08-29[143]邓三鸿.知识地图的构建与使用[D].南京:南京大学,2003
[144]Martin J.Eppler.Making Knowledge Visible Through Intranet Knowledge Maps:Concepts,Elements,Cases[J].Proceedings of the 34th Hawaii International Conference on System Sciences,2001
[149]Fiona Zhao,Xun Xu,S.Q.Xie.Computer-Aided Inspection Planning-The state of the art.Acta Automatica Sinica,Volume 35,Issue 3,March 2009,Pages 233-238
[150]Martin Oppermann,Wilfried Sauer,Heinz Wohlrabe.Optimization of Inspection Strategies by Use of Quality Cost Model and SPC.ISSE,Calimanesti-Caciulata,Romania,May 5-9,2004
[151]N.V.R.Naidu.Mathematical model for quality cost optimization.Robotics and Computer-integrated Manufacturing.Volume 24,Issue 6,December 2008,Pages 811-815
[152]Rodrigo J.P.Ferreira,Adiel Teixeira de Almeida.A multi-criteria decision model to determine inspection intervals of condition monitoring based on delay time analysis.Reliability Engineering & System Safety,Volume 94,Issue 5,May 2009,Pages 905-912
[153]Jie C,GreinerR,Kelly J,et al.Learning Bayesian network from data:An information-theory based approach[J].Artificial Intelligence,2002,137:43-90.
[154]胡笑旋.贝叶斯网建模技术及其在决策中的应用[D].合肥工业大学博士学位论文,2006.
[155]Xiang Y.A probabilistic framework for cooperative multi-agent distributed interpretation and optimization of communication[J].Artificial Intelligence,2006,87(1-2):295-342.
[156]杨善林,胡小建,马溪骏.DIDSS环境下信息agent系统任务规范的分解[J].系统工程学报.2004,Vol.19 No.5:489-495
[157]胡玉胜,涂序彦,崔晓瑜等.基于贝叶斯网的不确定性知识的推理方法[J].计算机集成制造系统-CIMS.2007,7(12):65-68.
[158]王体春,钟诗胜,王威.基于公理化设计的多级实例知识重用技术研究[J].计算机集成制造系统-CIMS.2008,14(5):833-840.
[159]胡玉胜,涂序彦,崔晓瑜等.基于贝叶斯网的不确定性知识的推理方法[J].计算机集成制造系统-CIMS.2007,7(12):65-68.
[160]杨善林,胡笑旋.融合知识和数据的贝叶斯网络构造.模式识别与人工智能,2006,19(1):31-34.
[161]杨善林,胡笑旋.基于案例和规则推理的贝叶斯网建模.哈尔滨工业大学学报(自然科学版),2006,38(10):1644-1648
[162]张曙,《中国制造企业怎样进入二十一世纪》,国防工业出版社,1997
[163]陶必悦,周有华,我国轴承产品及其关键技术发展预测(之一),轴承工业,2000年,9月.
[164]Stumpff Milton A.Statistical process control will improve your quality and profits,Ceramic Engineer and Science and Reliability Engineering International, 1991,7:437-448.
[165]吴晓蓉,汪乐,涂时亮 互连网技术在嵌入式系统中的实现,计算机工程,2001年4月,第27卷,第4期:1-4。
[166]殷建军.面向多品种、小批量制造环境的过程质量监控方法及嵌入式系统的研究[D].杭州:浙江大学,2004
[167]殷建军,余忠华,吴昭同.基于现场总线的嵌入式SPC系统研究[J].浙江大学学报,2004,(6):1422-1427