A Risk-Based Fire and Rescue Management System

Fires in the UK kill about 800 people and cause non-fatal injures to 15,000 every year. For the past 60 years provision for emergency fire-fighting response (i.e. fire cover) in the UK has been based on the density of the built environment. These arrangements have been effective in reducing the incidents of fire in public places, with the result that there is now a tendency for the present system to over-provide fire cover in city centres, whilst there is evidence of under-provision in residential suburban areas, given that 75% of fire deaths currently occur in domestic dwellings. Against this background, it is necessary to develop a risk-based asset management system to reallocate rationally fire and rescue resources and to improve the operations based on risks to life, property and the environment. Previous studies indicate that some uncertainty inference/treatment theories have been used to facilitate fire risk assessment and management (risk-based decision-making). The detailed literature review indicates that there is a lack of a holistic risk-based asset management framework and appropriate supporting tools for use in the fire and rescue services. The available methods in other domains may not be directly tailored for use in risk-based asset management of fire and rescue activities investigated in this research, taking into account the unique nature of fire and rescue operations. To address such identified research needs, in this project, a risk-based asset management framework will be proposed and a set of supporting tools developed in order to deploy effectively available resources, and to improve/optimise inspection, fire-fighting and rescue strategies.This research will first conduct data collection and modelling in close collaboration with the industrial collaborator. Fire and rescue operational processes will be studied together with the characteristics of the fire and rescue services, the type of equipment used and the current strategies adopted. The cost benefit will also be investigated in terms of fire and rescue operational strategies. A generic risk-based framework will be proposed capable of accommodating the modelling of multiple criteria and also have a live database containing models of generic systems/operations. The risk-based framework will be developed to establish guidelines for adopting effective operational strategies in the fire and rescue industry. The framework will be capable of dealing with the risk associated with each operational strategy in terms of various criteria such as response time, operational cost and the level of risk. A formal assessment process of hazard identification, risk estimation, identification of risk control options, cost benefit analysis and decision-making will be used to develop this risk-based framework. The supporting models to be developed for the implementation of the risk-based asset management framework include a subjective risk estimation tool, a multiple attribute decision-making tool, a planning tool for risk-based inspection/maintenance of fire safety systems, a risk-based multi-objective optimisation tool and a marine rescue simulator model. Case studies will be used to demonstrate the proposed framework and the associated supporting tools, and to assess their applicability and effectiveness. The detailed case studies will include the modelling of the deployment of fire engines and the other resources in the industrial collaborator, marine rescue operations in River Mersey and inspection/maintenance scheme of fire safety systems. A prototype software package will be developed, which aims to transform the modelling and investigation work into a platform for interactive risk modelling and decision-making. The awareness of fire risks to the public will be promoted throughout the project.