Hinojosa Herrera, Ana ORCID: 0000-0002-0636-1881, Walshaw, Chris ORCID: 0000-0003-0253-7779 and Bailey, Chris ORCID: 0000-0002-9438-3879 (2020) Failure mode & effect analysis and another methodology for improving data veracity and validity. Annals of Emerging Technologies in Computing (AETiC), 4 (3). pp. 9-16. ISSN 2516-0281 (doi:https://doi.org/10.33166/AETiC.2020.03.002)

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Abstract

Failure Mode & Effect Analysis (FMEA) is a method that has been used to improve reliability of products, processes, designs, and software for different applications. In this paper we extend its usage for data veracity and validity improvement in the context of big data analysis and discuss its application in an electronics manufacturing test procedure which consists of a sequence of tests. Finally, we describe another methodology, developed as a result of the DVV-FMEA application which is aimed at improving the tests' repeatability and failure detection capabilities as well as monitoring their reliability.

Item Type:	Article
Additional Information:	© 2020 by the author(s). Published by Annals of Emerging Technologies in Computing (AETiC), under the terms and conditions of the Creative Commons Attribution (CC BY) license which can be accessed at http://creativecommons.org/licenses/by/4.0.
Uncontrolled Keywords:	Big Data; Data Veracity; Data Validity; FMEA; Statistics; Electronics Manufacturing; Quality Assurance; Test Limits Optimisation
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Centre for Numerical Modelling & Process Analysis (CNMPA) Faculty of Engineering & Science > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Mechanics & Reliability Group (CMRG) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	23 May 2022 09:56
URI:	http://gala.gre.ac.uk/id/eprint/32293

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