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  Exploiting the digital thread in micro machining.

   Department of Automatic Control and Systems Engineering

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  Dr Rob Ward  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Geometric tolerances of parts are becoming ever increasingly tighter within the high value (aerospace, space and medical) manufacturing industries. As the cutting tools become smaller to accommodate such tolerances (sub-micron level) the behaviour of the CNC machine tool and its effect on tool-workpiece interaction can significantly affect the machined part quality. For example, the trajectory generation process, housed within the CNC interpolator, distorts the actual position and velocity commands of the micro-milling tool from discrete position commands resulting in unattainable feedrates and part tolerances.

The effects of the machine tool CNC interpolator and closed loop control systems on the micro milling process are complex and not well understood. The proposed research aims to better understand the impact of micro milling CNC machine tool control systems and their effect on part quality in the micro-scale machining operations to embedded process knowledge in an optimised process design. Along the machining process chain there exists a wealth of digital information - termed the digital thread which can be accessed via sensorisation, controller data and process modelling. The digital thread forms closed loops between the digital and physical domains and it must be fully mapped in order to develop a better understanding of the micro-milling process.

The project is a collaboration with department of Automatic Control and Systems Engineering and the department of Mechanical Engineering. The candidate will use variety of process monitoring techniques, process and machine tool modelling and experimental methods to investigate the effect of the CNC micro milling process on part quality, and map the digital thread of the micro milling process.

The candidate will work closely with experts at the Advanced Manufacturing Research Centre (the University of Sheffield) and wider industrial engagement is also being targeted to ensure the project is complemented by case study driven industrial challenges in this space.

Engineering (12)

Funding Notes

This is a self-funded research project. We require applicants to have either an undergraduate honours degree (1st) or MSc (Merit or Distinction) in a relevant science or engineering subject. Prospective candidates for this project should have a background in manufacturing, engineering or embedded systems and good programming skills, ideally in MATLAB and/or C/C++. Full details of how to apply can be found at the following link:
Applicants can apply for a Scholarship from the University of Sheffield but should note that competition for these Scholarships is highly competitive:

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