Dr James M Griffin | Engineering, Environment and Computing
Dr. James Griffin Experienced Senior Lecturer/Principal Engineer with over 20 years experience in designing, implementing and advancing automated control and monitoring of manufacturing systems. Posts ranging from Rolls Royce Research Fellowship to senior engineering within MBDA and QinetiQ affords James very well in advancing intelligent monitoring and control of manufacturing systems. James restarted his academic career with an international post at the University of Chile, mechanical engineering department. Here James made considerable impact where research calls now look into intelligent manufacture (He is now part of CORFO/Conicyt Reviewing Panel as well as Visiting Professor to several universities). James is a reviewer for 8 international journals and is an Airbus UK Studentship winner at an International conference in manufacturing (ICMR 2006). In James's short time publishing publically he has: 18 International Journal with 12 conference publications.
- Griffin J, Chen X, (2009), Multiple Classification of the Acoustic Emission Signals Extracted During Burn and Chatter Anomalies Using Genetic Programming, International Journal of Advanced Manufacturing Technology, 45 (11-12) pp 1152-1168.
- Calderon, A.A., Griffin, J. and Cristobal, J.Z. (2014), An Open Hardware High Resolution Digital Fabricator for the Masses, Rapid Prototyping Journal. Vol. 20 Iss: 3, pp.245 – 255.
- Griffin, J. and Chen X., (2014), Real-time Neural Network classifications of characteristics from emitted Acoustic Emission during Horizontal Single Grit Scratch Tests, Journal of Intelligent Manufacturing, Volume 27, Issue 3, pp 507-523.
- Griffin, J. (2014), Traceability of Acoustic Emission measurements for a proposed calibration Method – Classification of Characteristics and Identification using signal analysis, Mech. Syst. Signal Process. Volumes 50–51, January 2015, Pages 757–783.
- Griffin, J. and Torres, F. (2015), Dynamic precision control in single-grit scratch tests using acoustic emission signals, International Journal of Advanced Manufacturing Technology, Volume 81, Issue 5, pp 935–953.
- Griffin, J. (2015), Traceability of acoustic emission measurements for micro and macro grinding phenomena—characteristics and identification through classification of micro mechanics with regression to burn using signal analysis, International Journal of Advanced Manufacturing Technology, Volume 81, Issue 9, pp 1463-1474.
- Griffin, J. (2015), The prediction of profile deviations from multi process machining of complex geometrical features using combined Evolutionary and Neural Network Algorithms with embedded simulation, Journal of Intelligent Manufacturing, pp 1-19, In press.
- Griffin, J., Fernadez D., Geerling E., Clasing M., Ponce V., Taylor C., Turner S., Mena. P., Michael E., and Bronfmann L., (2016), Control of deviations and prediction of surface roughness from micro machining of THz waveguides using acoustic emission signals, Mechanical Systems Signal Processing, In Press.
- Kanarachos S., Griffin, J., Fitzpatrick M. (2016), Efficient multi-parameter optimisation using Contrast-based Fruit Fly Optimisation, Computers and Structures, In Press.
- Non-Destructive Evaluation of Stress and Heterogeneity using Acoustic Methods: NDE method for detecting RS verified by DE technqiues
- Investigations into the vibration effects when materials are subjected to damage: for 3D Vibrometer equipment
- Processing of an Advanced Nickel Alloy for Critical Engine Applications (PANACEA): novel machining methods applied to producing a regional jet turbine disk
- Early Career Researcher Funding Schemes: 2016-17 Coventry University: for supporting equipment
- Automated machining platform through sensing technologies: the University of Chile regular research support grant: Departamento de Ingeniería Mecánica (for equipment)