The School of Engineering

Profile

MEng, PhD, CEng, MIMechE

Eric is a Senior Lecturer in Mechanical and Design Engineering in the School of Engineering. Prior to him joining Portsmouth University in Feb 2011, he was at UWE and Bournemouth University. He received his MEng (Hons) degree in Mechanical Engineering from the University College London (University of London) in 1994 and a PhD in Mechanical Engineering from the University of Wolverhampton in 1998. After completing his PhD, he joined The Robert Gordon University in Aberdeen as a Research Fellow in the School of Mechanical & Offshore Engineering.

Eric is a Chartered Mechanical Engineer, and member of the IMechE. He has published and presented well over 20 papers at International Conferences/Symposiums and International Journals.

Primary research interests

• Experimental and computational work on condition & process monitoring. On-line metal cutting tool and bearing wear analysis/monitoring, applications of ANNs, GAs, fuzzy logic (classification, prediction, detection) in condition monitoring, predictive maintenance and fault diagnosis. Machine static/dynamic characterisation, noise, shock and vibration analysis.
• Principles & process understanding of cutting technologies, high performance machining, High-speed machining (micro/macro), machine tools (geometry, material & coatings), cutting mechanics and machining process dynamics and modelling. Characterization of the HSM microstructure and composition (including crystallography of materials) using a wide range of techniques including: SEM, ACPD, ACFM and image analysis.
• Electro-Discharge Machining: Deep narrow slot die/erosion machining, finishing of laser-sintered and HSM tools, parameter optimisation.
• Rapid product development (rapid prototyping, rapid tooling and rapid manufacturing) and associated technologies. Includes virtual and interdisciplinary team working for new product development, tooling, manufacturing processes, test of concept design/verification, virtual testing of process instruments, virtual reality for manufacturing and process planning, data modelling and optimisation, manufacturing environmental strategies.
• Development of optimisation methodologies, models and techniques for marine devices, structures and systems, knowledge management, parametric design, modelling, product assessment and optimisation. Cost models, project management.
• 3D CAD and Reverse Engineering, contact and non-contact 3D scanning, data cloud manipulation, 3D design (Pro-Engineer, Unigraphics, AutoCAD), NDT material inspection, geometrical modelling and part verification, manipulation and verification of CT/MRI data (Materialise’s Mimics).

Publications

Refereed papers

1. The Impact of Cutting Conditions on Cutting Forces and Vibration Signals: Part I - Turning with Plane Face Geometry Inserts. Special Issue of the Journal of Materials Processing Technology (To appear).
2. D E Dimla Snr., N Hopkinson and H Rothe. Investigation of complex rapid EDM electrodes for rapid tooling applications. To appear Int J Adv Manuf Tech.
3. Dimla D. E. Snr., The correlation of vibration signal features to cutting tool wear in a metal turning operation. International Journal of Advanced Manufacturing, 2000, 19(10), 705-713.
4. Dimla D. E. Snr., Correlation of cutting force features with tool wear in a metal turning operation. Proceedings IMechE, Journal of Engineering Manufacture Part B, 2001, 215(B3), 435-440.
5. Dimla D. E. Snr., Sensor signals for tool wear monitoring in metal cutting operations - a review of methods. Int. J. Machine Tools & Manufacture, 2000, 40(8), 1073-1098.
6. Dimla D. E. Snr. and Lister P. M., On-line metal cutting tool condition monitoring - Part I: Force and Vibration analyses. Int. J. Machine Tools & Manufacture, 2000, 40(5), 739-768.
7. Dimla D. E. Snr. and Lister P. M., On-line metal cutting tool condition monitoring - Part II: Multi-layer perceptron neural networks analysis. Int. J. Machine Tools & Manufacture, 2000, 40(5), 769-781.
8. Dimla D. E. Snr., Application of perceptron neural networks to tool-state classification in a metal-turning operation. Engineering Applications of Artificial Intelligence, 1999, 12(4), 471-477.
9. Dimla D. E. Jnr., Lister P. M. and Leighton N. J., Automatic tool state identification in a metal turning operation using MLP neural networks and multivariate process parameters. Int. J. of Machine Tools & Manufacture, 1998, 38(11), 343-352.
10. Dimla D. E. Jnr., Lister P. M. and Leighton N. J., Neural network solutions to the Tool Condition Monitoring problem - a critical review of methods. Int. J. of Machine Tools & Manufacture, 1997, 37(9), 1219-1242.

Conference papers

1. Dimla D E. The Impact of Cutting Conditions on Cutting Forces and Vibration Signals When Turning with Plane Face Geometry Inserts. AMPT 2003, Dublin City University, 7-11 July 2003.
2. Dimla D E, Singh H and May M. (2002) Fabrication of functional metal parts using the direct metal laser sintering technique: A Case-Study. 3rd National Conference on Rapid Prototyping, Tooling, and Manufacturing. CRDM, Chalfont, BCUC, UK, 20-21 June.
3. Dimla D E (2002) A new approach to the use of vibration signals in tool wear monitoring in high speed metal turning. 6th International Conference on Advanced Manufacturing Systems and Technology, UDINE (ITALY) - JUNE 20-21.
4. Dimla D. E. Snr., Bryden I. G. and Rados K. G., (2000) Site assessment methodology for offshore tidal current plants: A preliminary investigation. The 10th International Offshore and Polar Engineering Conference (ISOPE-2000), Seattle, USA., May 28-June 2.
5. Rados K G, Pitt D, Macfarlane D M and Dimla D E Snr. (2000) On the interaction of pipelines on the seabed. The 10th International Offshore and Polar Engineering Conference (ISOPE-2000), Seattle, USA., May 28-June 2 Dimla D. E. Snr. (1999) Tool wear monitoring using cutting force measurements. In Proc. 15th NCMR: Advances in Manufacturing Technology XIII, University of Bath, 6-8 September, pp. 33-37.
6. Dimla D. E. Snr. (1999) Neural network applications in metal cutting tool wear monitoring - a brief survey. In Proc. International Symposium on Manufacturing Technology (ISMT’99), 2nd World Manufacturing Congress, University of Durham, September 27-30, pp. 517-524.
7. Dimla D. E. Snr. (1999) Artificial neural networks approach to tool condition monitoring in a metal turning operation. In Proc. 7th IEEE Int. Conf. on Emerging Technologies and Factory Automation (ETFA’99), UPC Barcelona, Spain, October 18-22, pp. 313-320.
8. Dimla D. E. Jnr. (1998) Tool wear monitoring in a metal cutting operation using percetron neural networks and multivariate process parameters. In Proc. Int. ICS/IFAC Symposium on Neural Computation, TU Vienna, Austria, September 23-25, pp. 807 – 810.
9. Dimla D. E. Jnr. (1998) A modular tool wear monitoring system for metal cutting operations using MLP neural networks and multivariate process parameter. In Proc. UKACC Int. Conf. CONTROL ’98, University of Wales, Swansea, 1-4 September, IEE Conf. Publication No. 455, pp. 296 – 301.
10. Dimla D. E. Jnr., Lister P. M. and Leighton N. J. (1997) Sensor fusion for cutting tool state identification in metal turning through application of perceptron neural networks. In Proc. IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes- SAFEPROCESS '97, Hull, 9-11 August, Vol. 2, pp. 1144-1147.
11. Dimla D. E. Jnr., Lister P. M. and Leighton N. J. (1997) Application of a back-propagation neural network to Tool Condition Monitoring in a metal turning process. In Proc. International 32nd MATADOR Conf., UMIST, 10-12 July, pp. 287-292.
12. Dimla D. E. Jnr., Lister P. M. and Leighton N. J. (1997) A multi-sensor fusion method using multiple layered perceptron neural networks in a metal turning process. In Proc. 5th IEE Int. Conf. on Artificial Neural Networks, Cambridge, 7-9 July, pp. 306-311.
13. Dimla D. E. Jnr., Lister P. M. and Leighton N. J. (1997) A back-propagation neural networks solution to Tool Condition Monitoring in a metal cutting process. IEE Colloquium on Fault Diagnosis in Process Systems, York University, 21st April, Digest No: 97/174, pp. 9/1-9/3.
14. Dimla D. E. Jnr., Lister P. M. and Leighton N. J. (1996) Investigation of the sensitivity of single layer perceptron neural networks to tool wear inception during a metal turning operation. In C. H. Dagli et al. (eds.): Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 6 (ANNIE '96), ASME Press New York, pp. 867-873.
15. Dimla D. E. Jnr., Lister P. M. and Leighton N. J. (1996) Using single layer perceptron neural networks in tool wear identification. IEE Colloquium on Modelling and Signal Processing for Fault Diagnosis, University of Leicester, Sept. 17-18, 1996, IEE Digest Reference Number 1996/260 pp 3/1-3/4.
16. M Ring, D E DIMLA, W I Wimpenny ‘An Investigation of the effectiveness of Conformal Cooling channels and Selective Laser Sintering material in injection moulding tools’ RPD 2002 Advanced Solutions in Product Development, October 2002, Miranda Grande, Portugal.

Consultancy services offered

• Strategy determination in conventional & non-conventional machining, high speed machining, finishing of sintered powder tools, design optimisation and innovation application in mould & die manufacture.
• Multivariate data analysis and intelligent sensor fusion for condition monitoring and predictive maintenance (bearings, electrical motors, machinery/manufacturing systems) e.g. time/frequency, autocorrelation/regression, wavelet and GA analyses
• Instrumentation, data acquisition and processing for condition monitoring and maintenance (vibration and flow analysis)
• Materials processing (working/finishing/high speed cutting) for tooling applications and Rapid Prototyping techniques i.e. injection moulding, die & investment casting, and medical applications.
• Features based analysis - knowledge extraction (data mining, pattern recognition & classification) for manufacturing, condition based monitoring and fault diagnostics.
• Project management - technical aspects: design, manufacture and testing.
• Design Parameterisation and optimisation (e.g. tidal current turbines) and their integrity through modelling - FEA, geometrical analyses.