Estimating production test properties from test measurement data
Citation:
Simon P. Wilson, Suresh Goyal, Estimating production test properties from test measurement data, Applied Stochastic Models in Business and Industry, 2011Download Item:
Estimating Production Test Properties from Test Measurement Data Using Gaussian Mixtures.pdf (Published (author's copy) - Peer Reviewed) 979.8Kb
Abstract:
A complex sequence of tests on components and the system is a part of many manufacturing processes. Statistical imperfect test and repair models can be used to derive the properties of such test sequences but require model parameters to be specified. We describe a technique for estimating such parameters from typical data that are available from past testing. A Gaussian mixture model is used to model the wide variety of statistical properties of test data, including outliers, multi-modality and skewness, from which test properties are derived. Model fitting
is through a Bayesian approach, implented by Markov chain Monte Carlo.
Sponsor
Grant Number
Science Foundation Ireland (SFI)
08/IN.1/I1879
Science Foundation Ireland (SFI)
03/CE3/I40,5
Author's Homepage:
http://people.tcd.ie/swilsonDescription:
PUBLISHEDOnline publication, November 2011. Awaiting journal publication.
Author: WILSON, SIMON
Type of material:
Journal ArticleCollections:
Series/Report no:
Applied Stochastic Models in Business and IndustryAvailability:
Full text availableKeywords:
Statistics, Imperfect repair, Imperfect test, Gaussian mixture model, parameter estimationSubject (TCD):
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