Estimating the Probability of Human Error by Incorporating Component Failure Data from User‐Induced Defects in the Development of Complex Electrical Systems. Issue 1 (5th April 2017)

• Record Type: Journal Article
• Authors: Majewicz, Peter J.; Blessner, Paul; Olson, Bill; Blackburn, Timothy
• Is Part Of: Risk analysis. Volume 40:Issue 1(2020)
• Page Start: 200
• Page End: 214
• Publication Date: 2017-04-05
• Subjects: Electrostatic discharge -- failure rate -- human error -- human reliability assessment -- mechanical overstress -- risk management -- self‐induced failures -- thermal overstress; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.12798
• Languages: English
• ISSNs: 0272-4332

Abstract

Abstract: 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.