System Reliability at the Crossroads

Abstract

This paper surveys the current state of research related to the modeling and prediction of failures of engineering systems. It is argued that while greater understanding of the physics of failure has led to significant progress at the component level, there are significant challenges remaining at the system level. System reliability, a field of applied mathematics that addresses the latter challenges, is at a juncture where fundamental changes are likely. On the one hand, the traditional part of the field entered a phase of diminishing returns, largely having followed the trajectory of the ColdWar era technology development: golden years of rapid growth in the 1950s and 1960s, followed by maturation and slowing down in the ensuing decades. On the other hand, the convergence of several technologies related to data collection and processing, combined with important changes in engineering business and government priorities, has created the potential for a perfect storm that can revive and fundamentally transform the field; however, for this transformation to occur, some serious obstacles need to be overcome. The paper examines these obstacles along with several key areas of research that can provide enabling tools for this transformation.

Predicting Human Reliability based on Individual’s Resting Period: Effect of Physical Workload Rate

“…These variables were used to assess a person's response to workloads or to assess demands applied by experiments [17]. The Stroop test in this research with color-words stimulus and interference were included in high cognitive load category [37].…”

“…Not every system component works as intended; therefore, individual components can contribute to system failure through errors of omission and commission by doing an unexpected act [37].…”

“…Conceptually, reliability engineering includes calculation/qualification of the possibility of individual error/component failure and the possible correlations, determining the effect of individual error/component failure on a system, and developing a strategy to avoid said error/failure or to reduce the error/failure and/or its effect [37]. In this research, the resting period prediction is one effort to avoid errors, assuming operators are making proper recovery after fatigue during the resting period.…”