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Rob Ward

Project Title: Intelligent Adaptive Control of Manufacturing Machining Processes

Academic Supervisor: Dr Bryn Jones

AMRC Supervisor: Dr Tom McLeay

After an interesting career as an Engineering Officer in the military, I decided to change career path and have embarked on the journey into research. The EngD combines the academic rigour of a doctorate whilst closely aligning the research to industry. I enjoy the freedom that conducting independent research brings and I have a passion for teaching. I bring a different set of skills and experience to the IDC which complements the skills brought by the researchers who come straight from graduate entry. I chose the EngD because the AMRC offers some of the best manufacturing research facilities in the world and the University of Sheffield has the only dedicated Automatic Systems & Control Department in the UK.


My current research involves applying the use of active and adaptive control to machining processes with a view towards significantly improving production speed and performance. Specifically, the research project seeks to design control algorithms that will enable machining processes to adapt in a beneficial fashion, in response to measurement data from existing sensors. In other words, this project is about improving the performance of existing hardware by improving the operating software. The key enabler in this respect will be the use of continuous feedback from sensors through to machine actuators. Such feedback will be fundamental in enabling machining processes to achieve high-quality output in spite of variations in component hardness, tool wear, thermal expansion, etc.

Many numerically controlled (NC) machine tools carry out milling and turning tasks. The AMRC observes that such processes running in production facilities typically have the opportunity to improve productivity by 10-50% by optimising cutting feed rates. Furthermore, tool life can be at least doubled by avoiding chatter vibration and reducing high rates of change of the cutting forces. To optimise feed rates, reduce cutting times and avoid chatter vibration, an understanding of machining process fundamentals, chip formation, machining dynamics and tool path programming is required.

My research investigates control algorithms that optimise the performance of the machines via the NC codes and other methods used to drive the machine. It combines machining science with control engineering in order to optimise system processes. 


The IDC supports my language learning and therefore my spare time involves German language evening classes and doing homework! When not learning German grammar tables I can be found watching foreign movies, travelling around Europe and trying to maintain some kind of fitness whilst embellishing in my love of good food and Spanish red wines.