Dealing with abnormalities and deviations to enhance resilience in engineering Assets: A critical review from human factors and decision-making perspectives under complex operational contexts

Abstract

With the growing scale of industrial demands, complexities, and uncertainties around asset engineering and operations due to advanced technology utilization, digitalization, sustainability, new operating models, etc., the sensitive role of abnormalities and deviations towards human safety, systems security, reliability and resilience of engineering assets and industrial systems are becoming even more significant for modern industrial sectors as well as societies in general. In these contexts, the abilities of operators to capture and sense-make early signals that emerge from engineering assets and systems need more attention since it enables them to enhance critical situation awareness (SA) during complex operations. This calls for proactive solutions that can integrate core data with operator knowledge using suitable logical approaches, particularly in a period where there is growing recognition that asset data can provide strong support for engineering and operational decisions in demanding contexts. Based on an ongoing research project, this paper sheds light on abnormalities and deviations; two specific attributes that should be better understood. The purpose is to explore how to capitalize them at very early sense-making stages to enhance situation awareness and thus resilience of dynamic and complex engineering assets and systems. Through a critical review of the current state of knowledge, together with industrial observations, this paper studies these core concepts in detail with due attention to the critical need of so-called priory contextual knowledge and hybrid contextual decision solutions. This R&D work explores proactive possibilities to mitigate inherent potentials for unwanted events and incidents to enhance resilience in the era of digital twins and cyber-physical systems, where complex technologies and operational demands generate new conditions for asset performance.