Control theory-based fuzzy Fine-Kinney risk assessment for boiler automation system from the maritime autonomous surface ships (MASS) perspective

Vessel automation technologies are prevalent in today's industry, and Marine Autonomous Surface Ships (MASS) are being recognized as a potential future trend. Although certain commercial ships presently possess autonomous control capabilities, they are not designed for entirely unmanned operations. To effectively navigate this trajectory, a comprehensive analysis of complex ship systems, encompassing human, machine, and software components, is imperative for risk assessment. This study proposes an innovative approach that integrates control theory, Fine-Kinney, and fuzzy logic concepts to evaluate the risks of ship automation systems. The study focused on ship boilers with advanced automation, minimal human intervention, and potentially catastrophic risks for illustrative purposes. Initially, the ship boiler automation system was analyzed through the lens of control theory, followed by identification and expert scoring of system hazards. Subsequently, the fuzzy model was constructed to compute hazards within the system quantitatively and associated Fuzzy Risk Scores (FRS). Accordingly, EH1: Ignition burner electrode failure (2.280 Fuzzy Risk Score), FH1: HFO regulating valve failure (2.250), and FH7: HFO supply and booster pump failure (2.150) emerged as the most critical system hazards. The proposed methodology and findings offer a valuable blueprint for the future of automation within the shipping industry, facilitating safer, more efficient, and ultimately autonomous maritime operations.