An Intelligent Safety Prediction System for Rail Design and Maintenance
Supervisor: Dr Min An & Mr Alan Stirling; Researcher: Dr WanChang Lin
The primary aim is to investigate the principal safety issues in the railway infrastructure, devise and test a model and process for appraising new designs and maintenance schedules, also diagnosing, using artificial neural networks and approximate logic techniques. A secondary aim is to investigate how the intelligent safety analysis can provide insight into how risks contribute to accidents. The project will also provide an opportunity to transfer technologies already in the offshore oil & gas, nuclear, aerospace and aviation industries to rail.
Improving Rail Safety Risk Assessment
Supervisor: Dr Min An and Prof. Chris Baker; Researcher: Mr. Yao Chen
Railway safety risk analysis is a very complicated subject where safety is determined by numerous factors including human error. Many railway safety risk assessment techniques currently used are comparatively mature tools. However, in many circumstances, the application of these tools may not give satisfactory results due to the lack of safety risk data or the high level of uncertainty involved in the safety risk data available. This research project will apply Fuzzy Reasoning Methodology and Analytical Hierarchy Process to railway safety risk assessment process. This will provide railway safety risk analysts, operators and engineers and managers with a method and tool to improve their safety management and set safety standards.
Knowledge Management in Construction Projects
Supervisor: Dr Min An; Researcher: Mr Hesham S. Ahmad
Knowledge management (KM) is becoming increasingly important in the construction industry in order to satisfy the requirements of quality, cost and time. Knowledge management in construction projects is a challenging task because a large project often involves people from different companies with different professional background, e.g. clients, architects, project managers, designers, site managers, and workers. Furthermore, the project organization is unstable over time and becomes often completely exchanged from phase to phase in the period of a project life cycle. The aim of this research is to create a new knowledge management model that enables employee ideas and suggestions to be captured and shared, and to develop a knowledge management system for enhancing productivity and performance within the companies supply chain.
Managing Construction Industry Waste by Proactive Regulations in Developing Countries: A Case Study of Botswana
Supervisor: Dr Min An; Researcher: Mr BB Wilson
Construction and demolition waste does not only damage the environment but also contaminate the ground. The construction industry’s activities are also alleged to deplete natural un-renewable resources at an accelerated rate. The general perception is that retaining resources in the utility chain for their entire service lifespan would influence raw material consumption and also reduce environmentally load. The research project aims to develop an environmentally impact assessment model for construction and demolition water management. A case study of Botswana construction industry will be used to test the proposed assessment model.
Modelling Transportation and Land Use due to the Effect of Climate Change
Supervisors: Dr Jennaro B Odoki & Dr Min An; Researcher: Abdesslam Daoud
In the last decade the issue of climate change has become a subject of intense interest particularly the effect caused to the transportation networks. The aim of this research project is to develop a comprehensive model in which takes the variability of climate change into account in the transport and land use decision making process. This research programme includes literature review of techniques and methods of transport and land use modelling, investigation of the effects of climate change on the transportation infrastructures and land use in the area of Birmingham, development of appropriate strategies and organizational responses to effects of climate change and integration of the impacts of the climate change variability into transportation network and land use.
Reliability and Maintenance of Rail Vehicles
Supervisor: Dr Min An & Associate Professor Felix Schemid; Researcher: Mungyu Park
Maintenance and reliability management of railway vehicles plays an important role in the railway industry in order to reduce risks of accidents and incidents as low as reasonably practicably. The purpose of this study is to show the integrated maintenance and reliability model which can improve the overall problems and which can be prepared for the innovated change of rail vehicle maintenance through the analysis of the maintenance and reliability in the UK and South Korea rail vehicle maintenance systems. This research programme includes the literature review and the field study. Based on the investigations of the Intelligent train control and monitoring technology and the rail vehicle privatization and nationalization policy, a comprehensive and systematic maintenance and reliability model for rail vehicles will be developed to improve the rail vehicle reliability and human error. The rail vehicle safety and risk management policy will also be developed.
Safety and Risk Management in the Offshore Platform Design Process
Supervisor: Dr Min An; Researcher: Mr. Abubakar A. Umar
The design and installation of offshore platforms involve a very complicated process with attendant risks to people, environment and economic assets. The traditional method of carrying out risk assessments during installation and construction or after occurrence of accidents proved to be costly and often saddled with lack of flexibility for alternative remedial options. This research project will investigate how safety and risk management can provide insight into how design for safety methodology can be applied to the offshore platform design process
Development of Risk Assessment Models and Tools for Rail Construction and Maintenance
Supervisor: Dr Min An & Professor Chris Baker; Researcher: Mr Sheng Huang
The rail construction and maintenance industry is associated with a high degree of risk, which comes from the process of design, construction and maintenance. Construction projects are becoming more and more complicated with growing techniques. The aims of the project will classify and identify the risks in rail construction and maintenance projects, and develop risk analysis models and computer tools using approximate reasoning approach to facilitate risk assessment.
Prediction of Traffic Noise Risk Using GIS
Supervisor: Dr Min An & Professor KB Madelin; Researcher: Harmanjit Kaur
The design and development of large infrastructure projects, like rails and highways, demand good environmental management. Geographical Information Systems (GIS) is increasingly important in the study on the possible effects of planned infrastructure on the environment. When planning new infrastructure, noise is one of most important risk factors to be considered. Noise has a widespread spatial influence and the effects can be very drastic. GIS can be a very useful tool to monitor the noise risk effects on the environment. The use of GIS can increase the quality of study on noise pollution. The aim will be to improve the study on noise effect supporting the environmental management and to reduce the costs of these studies as well. The purpose of the project is to develop noise risk models combined with GIS. This includes increasing the quality and efficiency of noise effect studies, integration of GIS and noise risk models, indisputably quantify the noise effects, detailing of input data and dealing with uncertainties and inaccuracies.
Managing Risks in the Construction Projects
Supervisor: Dr Min An & Dr Andrew Chan; Researcher: JiaHao Zeng
The aim of this research project is to benchmark the current approaches and techniques of risk management as used in practice in construction industry and develop a comprehensive and continuous risk assessment framework in order to mange risks more effectively and efficiently., which includes to (1) investigate the current development and innovation of risk assessment tools and techniques and identify the major strengths and weakness of these tools and techniques; (2) determine the critical risk factors affecting construction project and develop and test-evaluate a fuzzy decision framework for handling risk factors; (3) develop a risk assessment model using probability analysis and risk impact assessment centred on the developed fuzzy decision framework; (3) develop a construction strategy and best practice guidelines into an integrated risk management framework for enhancing the chance of project success in the construction industry. This framework should be well grounded on the consideration of time, quality, cost and profitability of the business.
A Risk Assessment Based on Decision Making at the Construction Planning Stage
Supervisor: Dr Min An & Mr David Hoare; Researcher: Yangyany Lin
Construction risk analysis is a very complicated subject where risk is determined by numerous factors including human error. Many construction risk assessment techniques currently used are comparatively mature tools. However, in many circumstances, the application of these tools may not give satisfactory results due to the lack of data or the high level of uncertainty involved in the risk data available, specially at the construction planning stage. It is therefore essential to develop new risk analysis methods to identify major hazards and assess the associated risks in an acceptable way in various environments where such mature tools cannot be effectively or efficiently applied. In the project, a practical construction project will be investigated in detail. The major parameters that influence the decisions on which construction option to select will be studied. The techniques that have been used in selecting a most favourite construction option based on risk analysis will be reviewed.
Cost-reliability improvement of automotive products and components
Supervisor: Dr Min An & Professor Ian Wright; Researcher: Mpundu Mukanga
The purpose of this project is to develop cost-reliability based decision-making support models and tools to support automotive engineering decision-making related to products and components design and manufacture in order to show compliance with cost and reliability targets and to make future investment decisions. This research project will investigate the principal reliability issues in the automotive products and components and test a model and process for appraising new designs using statistical engineering techniques, fuzzy set theory and optimisation techniques. This will provide automotive engineers with a method and tool to improve their design and manufacture.
Risk assessment in road/rail interfaces
A risk assessment system will be developed in this project which will allow Highway authorities to prioritize between remedial action required at road/rail interface sites and give guidance on appropriate measures to road/railway designers, construction engineers and maintenance engineers.
Reliability Prediction Models for Reliability Assessment of Ageing Bridges
This project will develop reliability prediction models of ageing railway bridges, in conjunction with maintenance decision models, to provide a rational decision-making tool for the infrastructure assessment of bridges including risk assessment and life-cycle cost analysis.