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Failure mode & effect analysis for improving data veracity and validity

Failure mode & effect analysis for improving data veracity and validity

Hinojosa Herrera, Ana Elsa ORCID: 0000-0002-0636-1881, Walshaw, Christopher ORCID: 0000-0003-0253-7779, Bailey, Christopher ORCID: 0000-0002-9438-3879 and Yin, Chunyan ORCID: 0000-0003-0298-0420 (2019) Failure mode & effect analysis for improving data veracity and validity. In: Proceedings of the IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19). IEEE Xplore, pp. 100-105. ISBN 978-1728121383 (In Press)

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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, including electronics manufacturing. In this paper we propose a modification of this method to extend its application for data veracity and validity improvement. The proposed DVV-FMEA method is based on engineering features and in addition, provides transparency and understandability of the data and its pre-processing, making it reproducible and trustful.

Item Type: Conference Proceedings
Title of Proceedings: Proceedings of the IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19)
Additional Information: The Second IEEE International Conference on Computing, Electronics and Communications Engineering (IEEE iCCECE '19) 2019, was held from 22nd - 23rd August, 2019, at London Metropolitan University, London, UK.
Uncontrolled Keywords: FMEA, Feature Engineering, Big Data, Data Veracity, Data Validity, Electronics Manufacturing
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Centre for Numerical Modelling & Process Analysis (CNMPA)
Faculty of Architecture, Computing & Humanities > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Mechanics & Reliability Group (CMRG)
Faculty of Architecture, Computing & Humanities > Department of Mathematical Sciences
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Last Modified: 20 Aug 2019 12:24
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/24890

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