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Details of Grant 

EPSRC Reference: EP/F024606/1
Title: Enabling Security and Risk-based Operation of Container Line Supply Chains (CLSCs) under High Uncertainties
Principal Investigator: Yang, Professor J
Other Investigators:
Xu, Professor D
Researcher Co-Investigators:
Project Partners:
ABS Consulting CMA CGM UK Shipping Ltd Lloyds Register Group
Mersey Maritime Limited Peel Ports Group
Department: Manchester Business School
Organisation: University of Manchester, The
Scheme: Standard Research
Starts: 01 October 2008 Ends: 31 January 2012 Value (£): 315,557
EPSRC Research Topic Classifications:
Manufact. Enterprise Ops& Mgmt
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
Related Grants:
EP/F024436/1
Panel History:
Panel DatePanel NameOutcome
20 Sep 2007 Engineering Socio-Technical Systems Announced
Summary on Grant Application Form
Over the past several years, there has been a growing international recognition that security and risk issues of marine systems such as container line supply chains (CLSCs) need to be reviewed urgently. Serious accidents such as the 9/11 terrorist attacks in 2001, the lock-out of the American West Coast Ports in 2002, the blast on the Madrid commuter trains in 2004 and the blast on the London commuter buses and underground trains in 2005 have shocked the whole international shipping and logistics supply industries and prompted this urgency. CLSCs, with many complex physical and information flows, have not only contributed to economic prosperity but also rendered themselves uniquely vulnerable to many risks ranging from delay of cargo delivery to environmental pollution and from terrorist attacks to damage of economic stability. Security is becoming one of the most important criteria for measuring the performance of the design, control and management of marine systems. The term security may in general be defined as freedom from vulnerability which is an exposure to serious disturbances arising from threats. In this research, risks associated with threats will be referred to as security risks. Whilst conventional hazard-based risk is a combination of the probability of occurrence of an undesirable event and the degree of its possible consequences, security risks are different from hazard-based risks and need to be modelled differently. As a result, security and risk assessment is a process of analysing both threats and hazards in a system and making respective decisions on suitable strategies against the potential vulnerability of the system. Previous research in this and related areas has greatly increased our understanding of vulnerability, risks, threats and hazards. However, few studies have generated appropriate supporting tools for security and risk studies in CLSCs from both the engineering and managerial viewpoints. This project is aimed at developing a security and risk-based framework and also assessment models suitable for marine operations. To achieve this aim, several challenging research questions need to be investigated. First of all, most relationships among different security and risk variables may emerge at a variety of spatial, temporal or functional scales, which might be better represented if each relationship were described at or between the dynamic and interactive levels of detail, rather than treating static and steady scale processes identically. In this project, a novel hybrid reasoning network combining Bayesian networks, fuzzy sets and evidential reasoning, referred to as the ER-RN model, will be developed in order to estimate the occurrence likelihoods of threats and hazards in CLSCs. Secondly, information for security and risk assessment in CLSCs is inherently uncertain, caused by imperfect understanding of the domain of a CLSC, incomplete knowledge about the state of the domain, randomness in the mechanisms governing the behaviour of the domain, or a combination of them. It is therefore a great challenge to handle such uncertain information. In this project, a novel belief rule based (BRB) system approach will be investigated in order to use such uncertain information for estimating risks associated with both threats and hazards by modelling the damage capability, recall difficulty and damage probability of threats as well as the possible consequences of hazards. Thirdly, the assessment of security and risk control measures (SRCMs) requires the simultaneous consideration of multiple criteria such as system risk, the costs of implementing a SRCM and the benefits from reduced risk and cargo transfer delay. In this research, a multiple attribute decision-making method will be developed, which can process various types of information with uncertainty generated from the proposed ER-RN and BRB models. Case studies will be conducted to demonstrate the proposed network, models and analysis methods.
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