Engineering index : the quantification of uncertain margins and reliabilities with sparse data /

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Description

The Engineering Index (EI) provides a measure of goodness for engineered systems, subsystems, components, and product functions. The EI supports certification and planning endeavors by assessing both a product's current state as well as inferring how a system potentially changes over time relative to their requirements. This work will show how Bayes Theorem can be used to accomplish this inference. The inference available through EI allows decision makers to plan for, and possibly mitigate, problems ahead of a crisis by estimating how a product's changes impacts system performance.

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7 p.

Creation Information

Reardon, B. J. (Brian J.); Booker, J. M. (Jane M.); Dolin, Ronald M.; Faust, C. L. (Cheryll L.) & Hamada, Michael, January 1, 2002.

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Description

The Engineering Index (EI) provides a measure of goodness for engineered systems, subsystems, components, and product functions. The EI supports certification and planning endeavors by assessing both a product's current state as well as inferring how a system potentially changes over time relative to their requirements. This work will show how Bayes Theorem can be used to accomplish this inference. The inference available through EI allows decision makers to plan for, and possibly mitigate, problems ahead of a crisis by estimating how a product's changes impacts system performance.

Physical Description

7 p.

Source

  • Final version published in: Soft Computing, Multimedia, Biomedicine, Image Processing and Financial Engineering. Proceedings of the Fifth Biannual World Automation Congress (WAC 2002) ISSCI 2002 and IFMIP 2002, 9-13 June 2002, Orlando, FL, USA, p. 141-6

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  • Report No.: LA-UR-02-0865
  • Report No.: LA-UR-02-865
  • Grant Number: none
  • Office of Scientific & Technical Information Report Number: 976085
  • Archival Resource Key: ark:/67531/metadc927607

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  • January 1, 2002

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

Description Last Updated

  • Dec. 12, 2016, 5:52 p.m.

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Reardon, B. J. (Brian J.); Booker, J. M. (Jane M.); Dolin, Ronald M.; Faust, C. L. (Cheryll L.) & Hamada, Michael,. Engineering index : the quantification of uncertain margins and reliabilities with sparse data /, article, January 1, 2002; United States. (digital.library.unt.edu/ark:/67531/metadc927607/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.