Managing risks in maritime remote pilotage using the basis of the Formal Safety Assessment

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School of Engineering | Doctoral thesis (article-based) | Defence date: 2023-12-15
Degree programme
76 + app. 80
Aalto University publication series DOCTORAL THESES, 210/2023
Maritime pilotage is conducted in congested areas, where the risk of collision and grounding accidents is high. Hence, the pilotage operation is safety critical and has been established as a mandatory service in many countries. However, with Remote Pilotage (RP) and related technological transformation, there is a need to adapt risk management methods to address emerging risks. This thesis aims to develop a framework to manage risks in RP by identifying gaps in the Formal Safety Assessment (FSA) framework and proposes novel solutions to fulfill them. The thesis investigates Model-Based Systems Engineering (MBSE) for creating unambiguous system description models for the risk management process. Furthermore, this thesis addresses the selection challenge in MBSE by proposing a framework that assists system developers in choosing suitable MBSE language. Building upon the model, the thesis combines, System-Theoretic Process Analysis (STPA) and Bayesian Network (BN) for hazard identification and risk analysis. To reduce the limitations of other STPA-BN studies, the thesis explores the application of complexity reduction techniques such as the Parent Divorcing Technique, Noisy-OR gates, and the sub-models. Moreover, the thesis extends the STPA-BN method with a cost-benefit analysis using Influence Diagrams (IDs) for selecting a cost-effective Risk Control Option (RCO). Lastly, the thesis provides a methodology for the automatic generation of a BN risk model using an incident database and programming language, which facilitates real-time risk monitoring. The proposed frameworks and solutions are then applied to RP for managing risks in early design phases. System description models, developed with selected MBSE language, are used together with STPA to identify the RP risk events such as losses, accidents, hazards, and causal factors. For each of these risk events, the occurrence probability is determined using a BN model. The model shows that the losses with high occurrence probability are loss of customer satisfaction, damage to the ship, injury to people, and damage to the environment. Furthermore, the model shows that collision and contact accidents have a higher occurrence probability than grounding during RP in Finnish fairways. For controlling these risk events in RP, an ID is developed and numerous RCOs are evaluated based on cost-benefit analysis. As a result, a cost-effective RCO for RP is proposed in the thesis. Finally, an automatic generation of BN risk models using a pilotage incident database and Python is demonstrated. The developed tool generates and updates the BN model providing the occurrence probability of risk events for real-time risk monitoring. The results of this thesis demonstrate the applicability and effectiveness of the proposed framework. Furthermore, this thesis provides an essential foundation for managing risks in RP and facilitates its development. Last but not least, the thesis provides tools and methods supporting stakeholders in making risk-based decisions involving advanced systems.
Supervising professor
Valdez Banda, Osiris A., Prof. Aalto University, Department of Mechanical Engineering, Finland
Thesis advisor
BahooToroody, Ahmad, D.Sc., Aalto University, Marine and Arctic Technology, Finland
risk management, model-based system engineering, ship remote pilotage, systems-theoretic process analysis, Bayesian network, influence diagram
Other note
  • [Publication 1]: Basnet, S., Bahootoroody, A., Chaal, M., Valdez Banda, O. A., Lahtinen, J., & Kujala, P. (2022). A decision-making framework for selecting an MBSE language–A case study to ship pilotage. Expert Systems with Applications, 193, 116451. Full text in Aaltodoc/ACRIS: DOI 10.1016/j.eswa.2021.116451
  • [Publication 2]: Basnet, S., BahooToroody, A., Chaal, M., Lahtinen, J., Bolbot, V., & Valdez Banda, O. A. (2023). Risk analysis methodology using STPA-based Bayesian network-applied to remote pilotage operation. Ocean Engineering, 270, 113569. Full text in Aaltodoc/ACRIS: DOI 10.1016/j.oceaneng.2022.113569
  • [Publication 3]: Basnet, S., BahooToroody, A., Montewka, J., Chaal, M., & Valdez Banda, O. A. (2023). Selecting cost-effective risk control option for advanced maritime operations; Integration of STPA-BN-Influence diagram. Ocean Engineering, 280, 114631. Full text in Aaltodoc/ACRIS: DOI 10.1016/j.oceaneng.2023.114631
  • [Publication 4]: Basnet, S., BahooToroody, A., Bolbot, V., &. Valdez Banda, O. A. (2023). Real-time risk monitoring of ship pilotage operations: Automating BN risk model development. In Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023)
    DOI: 10.3850/978-981-18-8071-1_P284-cd View at publisher