Details of Grant 

EPSRC Reference:	GR/S85498/01
Title:	A Novel and Advanced Decision Support Tool for Offshore Operations.
Principal Investigator:	Yang, Professor J
Other Investigators:	Dale, Professor B jenkinson, Professor ID Wang, Professor J
Researcher Co-Investigators:
Project Partners:	Health and Safety Executive Shell
Department:	Manchester Business School
Organisation:	University of Manchester, The
Scheme:	Standard Research (Pre-FEC)
Starts:	01 June 2004	Ends:	30 November 2006	Value (£):	113,752
EPSRC Research Topic Classifications:	Oil & Gas Extraction Safety & Reliability of Plant
EPSRC Industrial Sector Classifications:	Energy
Related Grants:	GR/S85504/01
Panel History:
Summary on Grant Application Form
Describe the proposed research using (about 200) words geared to the non-specialist reader.Safety is of paramount importance in offshore operations. Human and organisational factors (HOFs) play a critical role in offshore operations and are often at the root of many major failures with disastrous consequences. Research in this area poses a significant challenge and is very much limited so far. This may be due to the unique characteristics of offshore operations in harsh environments and with many innovative features, the high level of uncertainty in failure data, and the difficulties of integrating HOFs into overall risk assessment together with other failure events as well as factors in finance, the environment, etc. This project is proposed to deal with such problems in a rational and integral manner.The project is aimed to develop a novel decision support tool for offshore operations. The project will include an initial investigation into the generation of best operation strategies. An advanced risk based framework will be developed and techniques for modelling HOFs will be explored. Bayesian networks will be developed for modelling failure interactions in a hierarchy of offshore operations. A linguistic approach will be proposed to process qualitative assessment information inherent to HOFs. To treat uncertainties common in failure data, a new uncertain rule base and its inference methodology will be developed together with self-learning algorithms. A novel group decision analysis methodology will be developed to support overall multiple criteria assessment of offshore operation strategies.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Project URL:
Further Information:
Organisation Website:	http://www.man.ac.uk