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Details of Grant 

EPSRC Reference: EP/S013377/1
Title: Creation of an intelligent machining system to adapt to structural variability in safety critical titanium alloy components
Principal Investigator: Jackson, Professor M
Other Investigators:
Crawforth, Dr P Wynne, Professor BP
Researcher Co-Investigators:
Project Partners:
Iowa State University Rolls-Royce Plc Sandvik (Cormant/Steel)
Seco Tools Timet UK Ltd
Department: Materials Science and Engineering
Organisation: University of Sheffield
Scheme: Standard Research
Starts: 01 April 2019 Ends: 31 March 2022 Value (£): 665,612
EPSRC Research Topic Classifications:
Manufacturing Machine & Plant
EPSRC Industrial Sector Classifications:
Manufacturing
Related Grants:
EP/S013385/1
Panel History:
Panel DatePanel NameOutcome
07 Aug 2018 Engineering Prioritisation Panel Meeting 7 and 8 August 2018 Announced
Summary on Grant Application Form
This work will change the way we think about machining high value titanium components - for example, turning an aeroengine shaft on a lathe. Rather than apply global rules about how much metal we can remove and how fast we can rotate the part, we will develop a technique that can monitor - in real time - the "microstructure" of the part, in order to determine how much pressure we apply with the cutting tool. Microstructure in metals is analogous to the different parts of timber - heartwood, sapwood, knots, how the grain runs - but on a much smaller scale (usually fractions of a millimetre). A master carpenter will see and feel these features of the timber by sight and touch, and instinctively work the wood with their tools in such a way as to maximise strength and/or visual appeal whilst using the least amount of effort. Such finesse has not been possible in metal working as - until now - there has not been a technique available that can "see" the microstructure.

A technique called spatially resolved acoustic spectroscopy (SRAS for short) uses lasers to generate and detect very high frequency ultrasonic waves that travel on the surface of the metal component. These waves interact with the microstructure, and this allows us to "see" it. By relating this information to knowledge of how machining the metal affects its performance - which is another part of the work - opens up the possibility of intelligently crafting the cutting process. Not only will this lead to faster machining processes and less damage, it will also mean that a map of the microstructure of the final part is available - this will be invaluable for confirming quality.

Key Findings
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Organisation Website: http://www.shef.ac.uk