Hinojosa Herrera, Ana Elsa ORCID: https://orcid.org/0000-0002-0636-1881, Walshaw, Chris ORCID: https://orcid.org/0000-0003-0253-7779, Bailey, Chris ORCID: https://orcid.org/0000-0002-9438-3879 and Yin, Chunyan ORCID: https://orcid.org/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, pp. 100-105. ISBN 978-1728121383 (doi:10.1109/iCCECE46942.2019.8941849)

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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 / School / Research Centre / Research Group:	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) Faculty of Engineering & Science
Related URLs:	Organisation
Last Modified:	04 Mar 2022 13:06
URI:	http://gala.gre.ac.uk/id/eprint/24890

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