期刊文献+

产品质量元数据的隐秘性 被引量:2

Product Quality Meta Data Secretive
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摘要 揭示了现实中质量元数据具有一定隐秘性的属性,分析了质量元数据隐秘性对顾客和企业的不同作用和不同意愿,引入都柏林核心资源集合的概念,定义了质量元数据由6要素构成的方法,并分别规范了6要素构成的应用样例,针对质量元数据的隐秘性提出了面向流程的质量元数据应用方法和数据流程,将质量元数据划分为故障元数据、制造元数据和功能元数据三大类,在尊重隐秘性的前提下,规划了质量元数据的共享原则和数据传递流程。 The authors reveal the certain secretive attribute that quality meta data has, quality meta data secretive to the customer and enterprise's different function and the different expectation, introduce the Dublin core resources set con cept, define quality meta data by 6 essential factor constitution method, and distinguish application example that consti tute of the standard 6 essential factors. They propose application method and the data flow in view of quality meta data se. cretive attribute, divide the quality meta data into 3 big types, namely defects meta data, manufacture meta data and function meta data with the premise of the secretive attribute being respected, plan the quality meta data sharing principie and the data transmission flow.
出处 《重庆大学学报(自然科学版)》 EI CAS CSCD 北大核心 2007年第5期87-90,共4页 Journal of Chongqing University
基金 国家自然科学基金资助项目(50375162)
关键词 质量元数据 隐秘性 质量工程 质量要素 数据流程 quality meta data secretive quality project quality essential factor data flow
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参考文献4

  • 1钱磊.知识管理到底管什么[J].企业管理,2003(11):25-27. 被引量:8
  • 2ISO 15836:2003(E).Information and documentation-the dublin core metadata element set[S].Genevese:International Organization for Standardization,2003.
  • 3GB/T 15835-1995.出版物数字用法的规定[S].北京:国家技术监督局,1995.
  • 4张根保.现代质量工程[M].北京:机械工业出版社,2005.

二级参考文献3

  • 1波兰尼,Personal knowledge,Routledge,London,1958.
  • 2Verna Allee The Knowledge Evolution,Butterworth-Heinemann, 1997.
  • 3野中郁次郎和竹内广隆,The Knowledge Creation Company:How Japanese Companies Create the Dynamics of Innovation,牛津大学出版社,1995.

共引文献8

同被引文献12

  • 1张根保.现代质量工程[M].北京:机械工业出版社,2004:15-18.
  • 2GB/T19001-2000.质量管理体系-要求(IdtIS09001:2000)[S].北京:中国标准出版社,2000.
  • 3Kumar A,Stecke K E, Motwani J. A Quality Index-Based Methodology for Improving Competitiveness: Analytical Development and Empirical Validation[J]. University of Michigan Business School, 2002: 7-8.
  • 4上海质量研究所.质量竞争力[M].北京:中国标准出版社,2006:96-118.
  • 5Pipino Leo L, Lee Yang W, Wang Richard Y. Data quality assessment [ J ]. Communication of the ACM, 2002,45(4) :211 -218.
  • 6Osman Balci. Verification, validation, and certification of modeling and simulation applications [C]//Proceedings of the 2003 Winter Simulation Conference. New Orleans, Louisiana, USA: [s. n. ] ,2003:150 - 158.
  • 7Cliff White. Simulation data guide [ R ]. Canberra, Australian: Australian Defense Simulation Office,2004 : 34 - 39.
  • 8Betsy B DeLong, Melissa O Miller. Verification and validation ensuring data credibility [ C ]//European Simulation Interoperability Workshop 2001 SIW.Orlando, Florida, USA : [ s. n. ] ,2001:206 - 214.
  • 9Stephanie Cammarata, Iris Kameny, Judy Lender, et al. The rand metadata management system [ R ]. California: National Defense Research Institute, 1995 : 11 - 19.
  • 10Jeff Rothenberg. A discussion of data quality for verification,validation and certification (VV&C) of data to be used in modeling[ C ]//Rand Project Memorandum PM - 709 - DMSO. Santa Monica, California: [ s. n. ] , 1997:24 -61.

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