On the Use of Hybrid Contextual Decision Solutions (HCDS) for Ensuring Resilience in Complex Engineering Assets and Systems

With the growth of complexity in modern engineering assets and systems, the operators are directly challenged by their level of awareness of varying situations in dynamic industrial settings. Operators in high-risk industrial sectors in particular look for new solutions that can help enhancing their situation awareness such that reliability, safety, and security characteristics can be kept in good control. This calls for data-driven decision-support applications that can particularly make sense of deviations, potential root causes, suitable counteraction plans, etc. for mitigating unwanted situations at the earliest possible times. However, most decision support systems available today have technical, functional, and operational limitations in capturing and sense-making of deviations in complex engineering and operational contexts. Based on an ongoing research project in close cooperation with industry, this paper aims at addressing this need by focusing on Contextual knowledge (CK) as a foundation for a higher level of situation awareness the so-called Advanced situation awareness (Ad-SA). The paper argues that managing unwanted situations in complex engineering assets and systems requires hybrid abilities to handle a large amount of dynamically changing data. To respond effectively, operators should have a support system that can enhance their level of vigilance toward what’s going on and help improve the level of sensitivity to capture early signals to ensure resilience of complex settings. With a specific focus on remote surveillance and remote support centers of complex engineering assets, this paper elaborates on a novel Hybrid contextual decision solution (HCDS) approach as a means to address the current need.