S Matsubara

A Risk Assessment of a Novel Bulk Cargo Ship-to-Ship Transfer Operation Using the Functional Resonance Analysis Method

Risk assessments underpin a maritime operation’s safety management system. When applied to an untested concept a risk assessment can also assist with overcoming resistance to new technology. This paper proposes the functional resonance analysis method (FRAM) as a tool for developing design recommendations and fulfilling the safety management objectives of the ISM Code. The FRAM is applied to benefit the floating harbour transhipper (FHT), a novel concept for the transhipment of bulk commodities. The FHT acts as a large floating warehouse with an aft well dock that provides shelter for a feeder vessel. The FHT’s materials handling equipment transfers bulk cargo from the feeder vessel onto its own stockpile or directly to an export vessel moored alongside, or from its stockpile to the export vessel. Most risk assessment tools focus on identifying and addressing system components that can potentially fail. With the FRAM however, the scope, direction and recommendations are guided by a practical understanding of the variability of work undertaken rather than preconceived notions of potential failure modes. Adopting a method based on maximising resilience rather than minimising the causes of accidents promotes a shift from a blame culture to a safety culture. Applying the FRAM generated a deeper, broader and more transparent understanding of the FHT transfer operation than what would have been achievable using traditional risk assessment tools. This understanding was used to develop recommendations designed to improve the resilience of the FHT operation.

Safety analysis of a new and innovative transhipping concept: a comparison of two Bayesian network models

The floating harbour transhipper (FHT) is a new and innovative concept designed to improve the efficiency of bulk commodity export. As with all new and untested maritime systems, a rigorous safety analysis is essential prior to the operation’s launch. Sophisticated tools, such as Bayesian networks, are increasingly being adopted for safety analysis in the maritime industry. Bayesian networks have predominately been used to replace fault trees due to their flexibility and improved handling of uncertainty. However, when applied to complex socio-technical systems Bayesian networks, as currently used, inherit many of the same shortcomings as traditional risk-based methodologies. These limitations are not indicative of the methods potential. This paper compares the traditional approach for developing Bayesian networks with an approach based on a foundation of resilience engineering. Both models were applied to an aspect of manoeuvring during the FHT’s operation. The resilience-based approach successfully developed a representative network. The two approaches led to vastly different models, both in terms of structure and parameters. However, the descriptive approach of resilience-based model produced more proactive safety recommendations and, unlike the traditional model, serves as a knowledge base for future investigation.