NTU's Fully-funded PhD Studentship Scheme 2022
Project ID: S&T67
During the last decades, there has been wide interest towards creating more agile and reconfigurable automation systems. This includes the research interest towards smart factory, human–robot collaboration (HRC) solutions and cyber physical production systems, where automated process could be combined with human dexterity and flexibility without complexity. Smart factories are the future of manufacturing in which humans will be collaborating with automated industrial modules, robots and raw materials. This is an active safety industrial environment, in which occupational health and safety issues will come up with new challenges, which will also include mental health. Mental stress at work is a major challenge in worker well-being in the European manufacturing industry. According to the estimates provided by European Agency for Safety and Health at Work, the 2013-14 survey estimated that out of all the work-related illnesses, 39% of cases were due to work related stress and depression and the trend is rising.
It is important to cater for stress in designing operations in industrial processes for the conditions, where human presence is interactive with smart robotics and smart machine systems at the factory floor, generating mental stress. Measures like mental stress and fatigue conditions can be correlated using neuroimaging data acquisition techniques, supported by standard questionnaire surveys. The measured data can be instrumental in developing stress limits and guidelines for safety evaluation and well-being of futuristic industrial worker. Another aspect of this research is to develop neuroimaging correlates with psychological and emotional safety and anxiety reduction. The project will be developed by designing experiments both inside and outside the lab environment. The outside portion will be an actual industrial setting, possibly having multiple process designs where subjects would be monitored over a long period.
The project will also involve development of an application/tool to quickly identify under stress workers in industrial setting by quantifying stress. This will result in device/system development for monitoring of worker mental health, early warning for stress related illnesses or work disruptions, improvements in worker well-being and efficiency. The part of the research can suggest use of some stress-reduction technique, e.g., neurofeedback or mindfulness as an effective way of risk mitigation. The project outcome will support in the identification of cognitive/emotional bottlenecks for better manufacturing process design. The outcome of the project will pave the way towards updating of industry standards based on our new discoveries on stress management in smart factory.
For the eligibility criteria, visit our studentship application page.
How to apply
For guidance and to make an application, please visit our studentship application page. The application deadline is Friday 14 January 2022.
Fees and funding
This is part of NTU's 2022 fully-funded PhD Studentship Scheme.
Guidance and support
Download our full applicant guidance notes for more information.