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© The University of Sheffield

Dr Nicolas Duboust

Graduated 2019

I moved to Sheffield to work on this EngD project in 2013, and completed my Viva in December of 2018. My EngD was a jointly sponsored project between the EPSRC and Rolls-Royce, and the project has developed research with the AMRC, (University of Sheffield) and Rolls-Royce into the machining of carbon fibre composite materials. The EngD program has been, in my opinion, a great platform for joint partnership between academic and industrial research, and it has allowed me an excellent opportunity to work on interesting research projects which has helped to develop my future career. The project also provides the flexibility to develop a career path which will continue in an academic or industrially focussed route.

During my EngD project I was able to work on industrial research into carbon fibre composite fan blades with Rolls-Royce. This has also lead into my future career as a research engineer with the AMRC, working on leading research into carbon fibre reinforced plastic (CFRP) machining. During this project I have been able to develop new research methods into the surface quality measurement and predictive methods for quantifying surface roughness in a machined composite surface. The generated tools have been able to make an impact on processes which will be applied by industry.

Project Summary:

CFRP composites are being increasingly used in the aerospace industry due to their excellent mechanical performance, resistance to fatigue, corrosion, and a high strength-to-weight ratio. The near-net shape production of composite parts is desirable during manufacturing, however conventional machining operations like drilling and milling are still often required for assembly of parts and to maintain geometrical tolerances. It has been found that fibre composites have a different machinability to metals and can suffer from a number of different machining-induced surface defects like delamination, matrix burning and fibre pull-out. Additionally, the hard and abrasive fibres will rapidly wear the cutting tool, which contributes to increased cutting forces and poor surface quality. These machining defects (which are generated during machining) can negatively affect the mechanical performance and surface integrity of CFRP components. Consequently, this project has researched CFRP milling process, quantifying the surface damage produced during machining, along with the development of FE predictive modelling tools.

The main aims of the project were to develop new FE modelling techniques for the prediction of surface roughness generated during milling, and to investigate the effects of tool wear and machining parameters on the machined surface roughness. Experimental edge trimming trials were completed and compared with FE models. Novel 2D and 3D FE models were compared with experimentally proven regression models to see the effects of different machining parameters on the surface roughness and machining forces, including feed rate, cutting speed and tool wear.

New roughness measurement strategies were established using optical focus variation device, applying areal roughness parameters. This has increased the reliability of roughness measurements and understanding of the damage modes caused during CFRP machining. During this EngD project I have also been given the opportunity to publish my findings in journal papers and travel to present and participate at international conferences. The EngD scheme has also allowed me to learn many different skills as a researcher and take part in a range of training activities. I would recommend the EngD to anyone who would like to work on new and interesting academic engineering research, and to work with other skilled researchers and engineers across different disciplines.

The main aims of this project are to develop new FE modelling techniques for the prediction of surface roughness caused during milling and to investigate the effects of tool wear and machining parameters on the surface roughness. New surface roughness measurement techniques have also been developed in order to increase the reliability of these measurements. Experimental edge trimming trials have been performed using PCD cutting tools and compared with FE models. 2D and 3D FE models have been developed along with experimental regression models to see the effects of different machining parameters on the surface roughness and machining forces, including feed rate, cutting speed and tool wear. It has been found that the surface roughness caused during machining is strongly affected by fibre orientation, tool wear and feed rate. Cutting tests have been performed in wet and dry cutting conditions and it has also been found that standard roughness measurement techniques using a stylus can be problematic. The use of areal roughness parameters has been investigated along with the use of Skewness and Kurtosis roughness parameters; which have been found to give a more thorough description of machining damage. 

 

New findings include the development of new roughness measurement strategies using optical focus variation device, along with the use of new areal and roughness parameters. This has increased the reliability of roughness measurements and understanding of the damage caused during machining.

 

Regression models have been created which show the contribution of different machining parameters and tool wear on carbon fibre surface roughness and machining forces during milling.


The use of different CVD and PCD cutting tools have been compared in wet and dry cutting conditions- with different feed rates and cutting speeds, and increasing levels of tool wear; to see their effects on surface roughness and machining forces.

 

2D and 3D composite milling finite element models have been developed and compared with experimentally obtained machining forces at different levels of tool wear to see which will more accurately predict machining forces and surface roughness.

Publications: