Risk and Reliability
When it comes to working with expensive equipment at sea, calculating the risk and reliability associated with systems is vital. The NOC develop and implement novel statistical methods to support risk and reliability management of underwater systems.
Risk management process tailored to AUV operations
We have developed a Risk Management Process for AUVs that is based on targeted reliability. An accepted risk is defined by the AUV owner. This acceptable risk converts into a reliability target that must be met by the AUV operators. We have developed extensions to existing statistical survival methods that allow us to assess the risk of loss for an AUV undertaking a mission in a defined environment, for example, under sea ice.
One of the most important requirements for AUV operation is to know the probability of the vehicle being ready for deployment when required; this is denoted as the vehicle’s availability. We develop Markov chains, a graphical probabilistic model, of the AUV deployment to predict AUV availability. The approach has also been applied to other marine sensors.
Expert judgement elicitation
Risk assessment is based largely on expert subjective judgement. Over the years, we have been applying and tailoring formal expert judgement elicitation processes to the underwater technology development community. We have conducted numerous expert judgement elicitation exercises.
Most of our equipment is deployed in extreme conditions. When these conditions can be recreated in the lab, we work with engineers to devise reliability testing plans for mechatronics (intelligent machine) components and software modules.
As a part of our programme we offer a no-fee service to those in the NERC marine science community with a risk or reliability problem or incident. Our aim is to help owners and operators establish the root cause, or the most likely cause or causes, without the attribution of blame. We can call upon our own experience in risk analysis and management, and also the engineering expertise in the Underwater Systems Laboratory (USL).