Estimating the Probability of Human Error by Incorporating Component Failure Data from User-Induced Defects in the Development of Complex Electrical Systems.
Electrostatic discharge
failure rate
human error
human reliability assessment
mechanical overstress
risk management
self-induced failures
thermal overstress
Journal
Risk analysis : an official publication of the Society for Risk Analysis
ISSN: 1539-6924
Titre abrégé: Risk Anal
Pays: United States
ID NLM: 8109978
Informations de publication
Date de publication:
01 2020
01 2020
Historique:
received:
01
10
2015
revised:
22
11
2016
accepted:
09
02
2017
pubmed:
6
4
2017
medline:
6
4
2017
entrez:
6
4
2017
Statut:
ppublish
Résumé
This article proposes a methodology for incorporating electrical component failure data into the human error assessment and reduction technique (HEART) for estimating human error probabilities (HEPs). The existing HEART method contains factors known as error-producing conditions (EPCs) that adjust a generic HEP to a more specific situation being assessed. The selection and proportioning of these EPCs are at the discretion of an assessor, and are therefore subject to the assessor's experience and potential bias. This dependence on expert opinion is prevalent in similar HEP assessment techniques used in numerous industrial areas. The proposed method incorporates factors based on observed trends in electrical component failures to produce a revised HEP that can trigger risk mitigation actions more effectively based on the presence of component categories or other hazardous conditions that have a history of failure due to human error. The data used for the additional factors are a result of an analysis of failures of electronic components experienced during system integration and testing at NASA Goddard Space Flight Center. The analysis includes the determination of root failure mechanisms and trend analysis. The major causes of these defects were attributed to electrostatic damage, electrical overstress, mechanical overstress, or thermal overstress. These factors representing user-induced defects are quantified and incorporated into specific hardware factors based on the system's electrical parts list. This proposed methodology is demonstrated with an example comparing the original HEART method and the proposed modified technique.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
200-214Informations de copyright
© 2017 Society for Risk Analysis.
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