Development of a model for integrating resilience engineering principles to ship management system [sic] to enhance navigational bridge operation

Analysis of the MAIB (Marine Accident Investigation Branch) accidents reports show that out of 127 recorded incidents between 2010 and 2015, 56 ship accidents were caused by operational failures on the navigation bridge. Setbacks on a ship's bridge led to three types of accidents: collision, grounding and contact. The analyses classified the reasons of the bridge deficiencies to task failures (causes of accidents), Sub-factors, mitigation deficiencies and accident impacts. This fact illustrates the need to improve safety standards with the bridge operation. This research work aims to address a new approach to barrier management concerning the operation of the navigation bridge system in a framework that incorporates the principles of resilience engineering to enhance shipping safety. The work process contains navigation bridge description, the definition of the safety performance, including fundamental resilience, developing application methods and a design scheme for control and maintenance. The approach introduces resilience-engineering elements: anticipation, monitoring, learning, and responding. The bow-tie model supports the approach by visualising the barrier system in a constructive perspective. The downside of this approach is the large amount of data received during the process, forcing the implementer to select the relevant information and to be specific when choosing the application area. Also, not all accidents have linear steps for the event, potentially forcing the implementer to be selective and bring the function elements and resilience resources effectively in line to be manageable and applicable. All these obstacles can be overcome by continuous application of the method. The benefits of this approach are minimising the errors of the bridge operator by improving the anticipation, enhancing the operation performance via the learning technique, improving the monitoring system and the efficiency of the safety planning, increasing the system reliability by maintaining a strong and flexible system able to response during changing conditions.Analysis of the MAIB (Marine Accident Investigation Branch) accidents reports show that out of 127 recorded incidents between 2010 and 2015, 56 ship accidents were caused by operational failures on the navigation bridge. Setbacks on a ship's bridge led to three types of accidents: collision, grounding and contact. The analyses classified the reasons of the bridge deficiencies to task failures (causes of accidents), Sub-factors, mitigation deficiencies and accident impacts. This fact illustrates the need to improve safety standards with the bridge operation. This research work aims to address a new approach to barrier management concerning the operation of the navigation bridge system in a framework that incorporates the principles of resilience engineering to enhance shipping safety. The work process contains navigation bridge description, the definition of the safety performance, including fundamental resilience, developing application methods and a design scheme for control and maintenance. The approach introduces resilience-engineering elements: anticipation, monitoring, learning, and responding. The bow-tie model supports the approach by visualising the barrier system in a constructive perspective. The downside of this approach is the large amount of data received during the process, forcing the implementer to select the relevant information and to be specific when choosing the application area. Also, not all accidents have linear steps for the event, potentially forcing the implementer to be selective and bring the function elements and resilience resources effectively in line to be manageable and applicable. All these obstacles can be overcome by continuous application of the method. The benefits of this approach are minimising the errors of the bridge operator by improving the anticipation, enhancing the operation performance via the learning technique, improving the monitoring system and the efficiency of the safety planning, increasing the system reliability by maintaining a strong and flexible system able to response during changing conditions