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Risk CDT - Fatigue Risk Management In The Workplace

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  • Full or part time
    Dr W Al-Nuaimy
    Prof I Donald
  • Application Deadline
    No more applications being accepted

Project Description


This is a project within the multi-disciplinary EPSRC and ESRC Centre for Doctoral Training (CDT) on Quantification and Management of Risk & Uncertainty in Complex Systems & Environments, within the Institute for Risk and Uncertainty. The studentship is granted for 4 years and includes, in the first year, a Master in Decision Making under Risk & Uncertainty. The project includes extensive collaboration with prime industry to build an optimal basis for employability.

Project Description:

In today’s 24/7 society workplace incidents resulting from excessive worker fatigue is ranked as one of the highest single risks. Fatigue related impairment has been cited as a significant contributing factor in major incidents involving significant loss of life and damage to infrastructure. For instance, Chernobyl & 3 Mile Island reactor meltdowns, Exxon Valdiz oil spill and the Challenger shuttle disaster to name a few. The global statistics for fatigue related fatal and serious road accidents for any country are anywhere between 20% and a staggering 40%. In the mining sector the percentile quoted is as high as 65%.

This project will require a multi-disciplinary approach between Electrical Engineering, Psychology and Engineering Dynamics in order to explore why the human mind recognizes and acknowledges the onset of fatigue but frequently continues to knowingly endanger themselves and others by failing to act upon that knowledge, often with fatal consequences. It will further examine methods of detecting and predicting the evolution of fatigue and its progressive impairment of cognitive and reaction ability.

Mathematical, physiological and psychological models of alertness, cognition and behavioural patterns will be proposed and tested with the objective of reliably and safely detecting and predicting the early signs of worker fatigue in a quantifiable manner. This information can then be used to manage work patterns in such a way as to minimise the risk to all parties involved. When deployed on a large scale, such information can be invaluable in ensuring the safety of those in the workplace (and the public) not only by providing the necessary insight into the dynamics of operator fatigue, but by the provision of the necessary technological solutions to enable employers to put in place intervention procedures to deal with situations before they become safety-critical. Prospective technologies will be tested on a vehicle simulator before deployment for real world trials.

The project will address the following goals:
1.Examine the psychology and physiology of fatigue.
2.Identify specific biomarkers that can be directly related to fatigue.
3.Research and develop technology to measure and cross- reference the biomarkers in order to create an absolute metric for fatigue which is both measureable in the workplace and scientifically rigorous.
4.Legal ramifications of the emergent technology in terms of possible legislative controls will also be examined.

The research will be principally focused on Operator fatigue in Road Haulage and Mining heavy vehicles. The potential for major incidents arising from fatigue related impairment being particularly high and widespread in these sectors. However the aim is to be able to use the new metric and technology to measure, quantify and predict the risk associated with the levels of fatigue exhibited by workers in different workplace settings and environments.

During the project span candidates will spend two periods on secondment in the industrial environment studying all aspects of the problem and testing of the technology in a real world setting.

This multi-disciplinary project builds on an existing and developing network of expertise, experience and active collaboration between the above partners in the areas of sleep and fatigue research, workplace risk and safety, flight and driving simulation, bio-sensor fusion and machine learning.

Funding Notes

The PhD Studentship (Tuition fees + stipend of £ 14,296 annually over 4 years) is available for Home/EU students. In addition, a budget for use in own responsibility will be provided.

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