Innovative solutions to reduce risk in the industrial sector
Performing effective risk assessment of large-scale and complex engineering systems is vital to design and operations. This task becomes challenging and problematic when data is lacking or unreliable. Innovative and flexible approaches to data modelling, risk estimation and cost-benefit analysis are required. With EU funding, the REFERENCE (Research network on flexible risk assessment and decision science) project is bringing together a multidisciplinary research team through doctoral and postdoctoral student exchange and training activities to design cutting-edge tools for the marine, oil and gas, supply chain management, nuclear and transport sectors. Overall, the aim is to carry out cost-efficient decisions given certain technical and economic limitations in order to reduce risks in the designated sectors and render them sustainable. Halfway through its four-year period, the project has worked on the creation of a formal safety assessment (FSA) framework with associated support models for use in the inland waterway, offshore and energy areas. A hazard identification and data modelling method was developed, and two models for risk estimation and uncertainty treatment were also devised and tested in inland ship operations and ship trajectory control. REFERENCE examined risk control methods and measures by focusing on inland shipping, maritime piracy and port facilities. Case studies on FSA have been conducted in ship navigation and trajectory control, port security and inland shipping along the Yangtze River – China's largest water system. To date, the project has published 13 papers and organised 5 workshops. REFERENCE is developing a structured and systematic methodology aimed at enhancing safety and facilitating proactive risk control in various industrial sectors. By advancing the state of the art in risk assessment, more effective risk-based assessment decisions will be carried out throughout the development and operational phases of large and intricate engineering systems.
Keywords
Industrial sector, risk assessment, engineering systems, decision science
