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Measuring Uncertainty in Use of Digital Technologies Using Human Factors Methodology

   Wolfson School of Mechanical, Electrical and Manufacturing Engineering

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  Dr R Grant, Dr Yee Mey Goh  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Measurements within digital technologies can still have enormous variability in setup, use and result processing yet it is highly prevalent for optimisation and throughput in manufacturing and control scenarios. Differences in measurements have a huge impact on quality data and business decisions, with variable measurements contributing a large effect on the quality of manufacturing decisions made for future processes and product release. There is huge variety in how manufacturing quality measurements are setup and optimised, which can vary as a function of the operator and environment. Machine vision and embedded intelligence are becoming more popular options to include to reduce processing times, however, the inherent parameters that define how these are used can cause additional variance due to lack of operator understanding.

This project will use uncertainty principles and human factors assessment methods to compare how people interact with digital interfaces, with a quantified contribution to an uncertainty budget. This can define where and what standards can be used to reduce variability.

The successful applicant will become a member of the growing Human Factors Engineering Research Group (HFERG), within the Wolfson School. The HFERG brings together a multi-disciplinary team of specialists in cognitive, physical and organisational ergonomics, taking a systems and data led approach. Our focus is on the role of people in a variety of industrial systems, supporting and enhancing wellbeing and effectiveness of the whole system. The post will align to the EPSRC-funded Made Smarter Innovation Centre for People-led Digitisation. The vision of the Centre is to be the world-leaders in providing people-led solutions to support manufacturing to have right-first-time digitalisation. The post will be based at Loughborough, but will align to work at the Universities of Bath and Nottingham, with the potential to engage with a range of industry partners to deliver transformative research to unlock digitalisation potential through people-led solutions.

Within manufacturing scenarios, many factors can cause variation within a system, from product, process, environment and equipment to name a few. The operator is often overlooked as a source of variance within the system, especially since the increase in automation and digitalisation within manufacturing has ‘removed’ the person from the process. However, the human is still at the centre of the operation, making more high-level decisions around optimisation, setup and override control procedures. People are still required to check and validate automated decisions, and this interaction is not as well understood as to how these situational elements effect process parameters, quality of results and decision making as a result.

This PhD will use human factors methods to identify opportunities for improvements within digital technology interfaces used within manufacturing scenarios. Measurement uncertainty principles will be utilised within the analysis of human-computer interaction to find where variabilities are apparent when using digital interfaces, aiming to quantify the effect of these towards a measurement uncertainty budget. There is an opportunity to engage with up to 15 industrial partners on this PhD through alignment to the Made Smarter Innovation Centre for People-led Digitalisation, to have maximum impact for this research.

Manufacturers have highlighted the need to have digitally engaged people to realise the full potential of digitalisation. They know that the adoption and uptake of appropriate digital technologies will enable their manufacturing business to thrive. However, much of industry and academic activities have tended to have a single focus such as new technology/tools or digital interfaces. The industrial partners of our Centre stated they needed more – they wanted to place people at the centre and move from a mindset of people ‘operating the equipment’ to one where we are ‘equipping the operator’ and in doing so empowering and unlocking their potential.

Funding Notes

Please note that studentships will be awarded on a competitive basis to applicants who have applied to this project and other advertised projects starting with advert reference ‘SAM22'
If awarded, the studentship is for 3 years and provides a tax-free stipend of £15,609 per annum for the duration of the studentship plus tuition fees at the UK rate. While we welcome applications international students, please be advised that it will only be possible to fund the tuition fees at the international rate and no stipend will be available. Successful candidates will be notified end of March 2022.
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