EPSRC ICASE Studentship with Siemens: Automated, Adaptive, Intelligent Assembly of Complex Electronics Products Using Modular-Collaborative Robot Technology at University of Sheffield on FindAPhD.com

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Prof A Tiwari Applications accepted all year round Competition Funded PhD Project (UK Students Only)

Sheffield United Kingdom Artificial Intelligence Control Systems Internet Of Things Manufacturing Engineering

Department of Automatic Control and Systems Engineering, University of Sheffield

About the Project

This project aims to enable modular-collaborative robots to autonomously deal with part and process variations in complex electronics assembly.

Final assembly of complex electronics products is a challenging task that is still largely performed by human workers. For example, components found in a motor drive are small, complex and irregular in shape. Fully automating their assembly is currently only possible through costly bespoke automation. In addition, automation may require changes in product design or in methods for part delivery, increasing the overall product cost.

An alternative approach is through modular-collaborative robots, which are capable, flexible and yet low-cost. In lab environments, they have been shown to successfully collaborate in order to assemble complex electronics components. However, the industrialisation of such robots is challenging due to the reality of day-to-day shop floor operations that introduce numerous part and process variations. These variations, when combined with the complexity of the assembly tasks and the limitations of existing end-effectors, form a barrier that stops the modular-collaborative robot concept from being exploited further. The proposed research seeks to address this barrier by utilising recent advances in low-cost sensing, control systems and artificial intelligence.

This project will be undertaken in collaboration between the University of Sheffield and Siemens. The Siemens Congleton facility will be available for the selected PhD candidate to be used for their development work. The student will also get the opportunity to work with the Productivity through Automation (PtA) team within Siemens, Congleton getting the exposure to cutting edge robot integration technologies and Siemens hardware and software.

Funding Notes

The funding for this position is from an EPSRC Industrial CASE PhD studentship in partnership with Siemens. The award will pay full tuition fees and maintenance grant for 4 years.
Quoting EPSRC website: "Student eligibility requirements for EPSRC Industrial CASE funding are the same as for our other studentship awards. They are: (i) a relevant connection with the UK, usually established by residence; (ii) first class honours degree, or a combination of qualifications and/or experience equivalent to that level."

Where will I study?

University of Sheffield

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