Computational Functional Failure Analysis to Identify Human Errors During Early Design Stages

Abstract

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced functional failure identification and propagation (FFIP), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed toward the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. The capabilities of the proposed method is presented via a hold-up tank example, and the results are coupled with digital human modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

Preemptive Failure Detection using Contamination-Based Stacking Ensemble in Missiles

“…Identifying potential failures, specifically missile that will fail, at the production phase is crucial for equipment support capabilities and assessing combat mission performance. Moreover, identifying potential failures early can lead to design modifications or quality improvements, reducing additional costs that may arise and preventing system failures and safety incidents that may occur over time [13,14]. In response to these challenges, this study statistically examines quality inspection management (QIM) data acquired from the missile production phase and proposes a new methodology for detecting missiles that will fail based on the statistical analysis of this data.…”

Fmdtools

“…fmdtools is intended specifically to provide fault analysis methods that enable the consideration of risk in early conceptual design processes called functional hazard assessment and follows the ARP4761 guideline (ARP, 1996;Allenby & Kelly, 2001). Model-based functional hazard assessment has been an active research area (Krus & Lough, 2009;Kurtoglu & Tumer, 2008;Noh, Jun, Lee, Lee, & Suh, 2011), with many new methods focusing on how to model different aspects of the system, such as human errors (Irshad, Ahmed, Demirel, & Tumer, 2019), dynamic behaviors, new flows resulting from failures (Jensen, Tumer, & Kurtoglu, 2009), and operational decision-making (Short, 2016). However, there has been less demonstration of how to use this information to compare design alternatives, and the research codes underlying these methods have not been shared within the research community.…”

An Improved FFIP Method Based on Mathematical Logic and SysML

“…Reference [22] shows that the FFIP method can effectively evaluate software and hardware. Additionally, in reference [23], human factors are considered, and the impact of human error on system failure is analyzed by using FFIP. In reference [24], external events are considered, the Time-Based Failure Flow Evaluator (TBFFE) is developed based on FFIP method.…”