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Human factors (HF) are little understood, and particularly in non-destructive testing (NDT) experimental data is rare, samples are often small, and statistical methods are rarely used to evaluate results. HF have been widely implicated in major occurrences of technical failure, for example at North Anna Power Plant and on United Airlines Flight 232. Understanding HF is vital for reliable detection and prevention of failures. Reliability assessments, though known to be affected by intrinsic capability, application factors, and HF, have thus far only concentrated to a sufficient degree on intrinsic capability. The addition of HF to that assessment has proven difficult due to the lack of a method of quantifying HF. This paper presents the first attempt from a psychological perspective to quantify HF from qualitative data.
HF data was derived from qualitative human-oriented Failure Modes and Effects Analysis (Human-FMEA) workshops for visual inspection of tunnels by laser scanning and for ultrasonic testing of welds. Data was collected on human failure modes, causes, consequences and preventive measures, as well as eliciting a risk priority number (RPN). Using this data, a system of quantitative weightings was created to allocate errors to inductively derived HF categories for further allocation to existing HF categorisation models.
This weighting model proved useful for creating quantitative summaries of HF, informing and validating qualitative FMEA results, and comparing existing HF categorisation models. Further potential lies within a planned interface to quantitative reliability assessment methods such as POD (Probability of Detection). While providing quantifications, the method retains a qualitative and holistic nature, can, thus, bridge the gap between psychological and engineering concerns of HF and reliability, contributing to future interdisciplinary work.
Im vorliegenden Artikel werden die Ergebnisse des Fragebogens der DGZfP zur Thematik „ZfP 4.0“ vorgestellt und diskutiert. Die Befragung zielte darauf ab, das allgemeine Verständnis der ZfP-Community zur Begrifflichkeit „ZfP 4.0“ herauszuarbeiten und daraus Bedarfe und Handlungsempfehlungen für die identifizierten Herausforderungen abzuleiten. Außerdem zeigt sich aus Sicht der Autor*innen, dass relevante Terminologien zu dem Themenkomplex Digitalisierung einer weiteren Klärung bedürfen, was im Bericht aufgegriffen wird. Im Ausblick zu den angelaufenen Arbeiten im nationalen Fachausschuss ZfP 4.0 und in den sich etablierenden internationalen Fachkreisen werden daraus abgeleitete Perspektiven für die Zukunftsgestaltung vorgestellt.
In comparison to manual NDT methods, mechanized NDT is considered to be more reliable for a number of reasons, one of which being that the role of the inspectors and, therewith, the potential for human error, have been reduced. However, human-automation interaction research suggests that in spite of its numerous benefits, automation can lead to new yet unknown risks. One of those risks is inappropriate reliance on automation, which can result in automation misuse and disuse. The aim of this study was to investigate the potential inappropriate use of automation (specifically - the automated aids) in NDT addressing therewith the prevalent belief in the high reliability of automation held by the NDT community. To address this issue, 70 NDT trainees were asked to control the results of an eddy current data evaluation, allegedly provided by an automated aid, i.e. indication detection and sizing software. Seven errors were implemented into the task and it was measured to what extent the participants agreed with the aid. The results revealed signs of both misuse (agreeing with the aid even though it is incorrect) and disuse (disagreeing with the aid even though it is correct) of the aid that can affect the reliability with which inspections are carried out. Whereas misuse could be explained by a lower propensity to take risks and by a decreased verification behaviour-possibly due to bias towards automation and complacent behaviour-, disuse was assigned to problems in establishing the sizing criterion or to general difficulties in sizing. The implications of these results for the NDT praxis including suggestions for the decrease of automation bias are discussed.