NDLI: Bayesian reliability prediction of a medical device system

Content Provider	IEEE Xplore Digital Library
Author	Yan Liu Berg, R. Xignfu Chen Abeyratne, A. Xiaobo Wang Haddad, T.
Copyright Year	2015
Description	Author affiliation: Medtronic, Inc., Minneapolis, MN, USA (Yan Liu; Berg, R.; Xignfu Chen; Abeyratne, A.; Xiaobo Wang; Haddad, T.)
Abstract	High product quality and reliability are critical in the medical device industry. Accurate reliability prediction during the product development stage provides inputs for the design strategy and boosts understanding and confidence in product reliability before products are released to the market. A Bayesian framework provides a straightforward solution for product system reliability prediction with uncertainty quantified as confidence intervals. This is achieved by propagating the uncertainty of model parameters and component-level reliability to the system level. In this work, Bayesian models are applied in the Design for Reliability process to assess medical device system reliability with confidence. In cases where a single data source is insufficient due to sample size limitations, Bayesian models are flexible to aggregate various sources of data to reduce uncertainty.
Starting Page	1
Ending Page	6
File Size	321236
Page Count	6
File Format	PDF
e-ISBN	9781467385572
DOI	10.1109/ICRSE.2015.7366449
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Design for reliability Uncertainty Shape Bayesian Reliability engineering System reliability prediction Data models Bayes methods Statistical analysis of uncertainty
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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