Prof Theo van Niekerk


Professor
Department of Mechatronics
theo.vanniekerk@mandela.ac.za
041 504 3103
North Campus, E-Block, Room E22

Biography / Background

Theo is a senior lecturer within the Mechatronics Engineering Department at Nelson Mandela University and a researcher within the Advanced Mechatronics Technology Centre. Since starting at the then Port Elizabeth Technikon over 30 years ago, his teaching and research interest have been within the field of Mechatronics. He teaches classical and modern continuous and discrete control theory, process control, sensors and instrumentation. His teaching strategy is grounded in action research, a continuous systematic enquiry to help develop teaching actions that enable learners to improve learning engagement and professional development. His research interest and focus is on continuous improvement through providing mechatronic solutions to a range of challenges in the manufacturing and related engineering industries.   He manages and provides technical leadership to the NMU-Siemens training centre.  The training centre runs Siemens accredited courses into Factory Automation, Drives and Control Systems to the Manufacturing and related Engineering Industry within the Eastern Cape. 

Qualifications
NH Dip: Computer Data Processing
BEng Electrical and Electronic Engineering
MTech Information Technology
DTech Electrical Engineering

Professional Activities
• Professional Engineer.
• Assessor within the ECSA University Accreditation Team into the Mechatronic Engineering programme.

Teaching Interests


My primary teaching challenge and interest is to guide engineering students to apply fundamental mathematics and science taught within their first two years of study to perform problem-solving, analysis and design within a modern control systems engineering context.  Modern control systems techniques advance fundamental knowledge to an advanced level, therefore this is both challenging and rewarding to experience the progress of learners.  Whilst understanding the importance of complex problem-solving, a key practical component and learning strategy is to blend engineering practice so as to prepare students for the real world.  Given the socio-economic challenges within our automotive engineering and related manufacturing environment, an interest into German engineering programmes, applied teaching methodologies and university-industry collaborative models led to a collegial collaboration between German higher educational institutions: Ingolstadt University of Applied Sciences, Ostfalia University of Applied Sciences, Reutlingen University and Siemens Cooperates with Education.

 

Research Interests


Intelligent Mechatronic Systems applied to Advanced Manufacturing and related Engineering Systems - Within our research team the concept of intelligent mechatronic systems is simply described as: An electrical - mechanical device or system integrated with a microcomputer that has artificial intelligence-based capacity to analyze sensor data and take action.  Artificial Intelligence (AI) - based techniques may include: Expert systems, neural networks, fuzzy logic and genetic algorithms. 


 

Representitive Publications

• van Niekerk T., Le Roux V, 1994. Control/SPC software for bore and outside measuring apparatus for ball bearings, Conference Proceedings of the International Conference: Intelligent Systems of the AMSE, Pretoria, September, pp265-272.
• van Niekerk T, Thomas T. 1994. Knowledge Acquisition in a Manufacturing Environment, Conference Proceedings of the International Conference: Intelligent Systems of the AMSE, Pretoria, September, pp346-358.
• van Niekerk T, Fourie C. 1995. Manufacturing Knowledge Acquisition and Utilization by Means of Expert Systems, Proceedings of the 13th International Conference on Production Research, Jerusalem, August, pp44-46.
• Van Niekerk T, du Toit R, 1998, Developing a Skills Orientated Course in Engineering Software Principles for a Changing Technologist Environment, 4th WFTO International Symposium on Technology Education and Training: On the Threshold, 27 June - 1 July 1998.
• van Niekerk T. I., Katz Z,  Huang J., 1999, Integration of Human Knowledge and Sensor Fusion for Machining, Proceedings of 2nd International Conference on Information Fusion, California USA, pp.1107-1112. 
• van Niekerk T.I., Katz Z., Huang J., 2000, Analysis and Implementation Aspects of Intelligent Machining, International Conference on Manufacturing Systems for the New Millennium, Hong Kong. 2000
• van Niekerk T. I., Katz Z., Huang J., 2001, Monitoring of Machining Process Based on Intelligent Diagnosis by Using a Fuzzy Relation, International Conference on Agile, Reconfigurable Manufacturing, Michigan, USA
• Van Niekerk et al, 1999, VRML to Monitor and Control an Industrial Robot via the Internet, Proceedings of IEEE Africon 99, Cape Town.
• Van Niekerk T.I., Katz Z., Huang J., 1999, Integration of Human Knowledge and Sensor Fusion for Machining, Proceedings of the 2nd International Conference on Information Fusion (Fusion'99). Sunnyvale, CA, 6-8 July, 1999.
• Van Niekerk T.I., Katz Z., Huang J., 2000, Analysis and Implementation Aspects of Intelligent Machining, International Conference on Manufacturing Systems for the New Millennium, Hong Kong.
• Kruger G.H.; van Niekerk T.I.; Blignault C.; Hattingh D.G., 2004, Software Architecture for Real-time Sensor Analysis and Control of a Friction Stir Welding Process, IEEE Africon 2004, September, Gaborone, Botswana
• Van Niekerk T.I., Hua T., Hattingh D.G., 2006, A Neuro-Fuzzy Scheme for Process Control During Complex Curvature Friction Stir Welding, 112th IFAC Symposium on Information Control Problems in Manufacturing, Saint-Etienne, France.
• Van Niekerk T.I., Hua T., Mafara K.E., 2007, Adaptive Fuzzy Force Regulation in Friction Stir Welding Process, International Conference on Competitive Manufacturing – COMA’07: The Challenge of Digital Manufacturing, 31 Jan – 2 Feb, University of Stellenbosch, South Africa.
• van Niekerk T.I., Buys S., 2013, Genetic Algorithm for Artificial Neural Network Training for the Purpose of Automated Part Recognition, International Conference on Competitive Manufacturing COMA 13,  IISBN Nr:: 978-0-7972-1405-7, 30 Jan – 1 Feb, University of Stellenbosch, pp.235-242.
• Mercorelli P., Werner N., Becker U., Harndorf H., van Niekerk T.I., 2014, Digital Control of a Camless Engine Using Lyapunov Approach with Backward Euler Approximation, IFAC, Cape Town.
• Mercorelli P., Werner N., van Niekerk T., Behre L., Becker U., 2015, Switching Cascade Controllers Combined with a Feedforward Regulation for an Aggregate Actuator in Automotive Applications, 2015 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech) November 26-27, Port Elizabeth, South Africa.
• Zindove T., van Niekerk T., Wilm T., Mercorelli P., 2015, Development of a temperature controlled weathering test box to evaluate the life cycle behaviour of interior automotive components, IFAC Conference on Programmable Devices and Embedded Systems, 13-14 May, Poland, ISSN: 2405-8963. 
• van Niekerk, T. & Fernandes, J.   – “Effective methods for Learning Functional Safety within Automated Manufacturing Systems”. Submitted to the International Conference on Competitive Manufacturing (COMA), Cape Town, South Africa, February 2016.
• John Fernandes, Theo van Niekerk, Ngonidzashe Zata, A Web Based Learning Platform for Remote Engineering Laboratories, SASEE Fourth Biennial Conference, 13-15 June 2017, Cape Town.
• van Niekerk T.I., Katz Z., 2003, Implementation Aspects of Intelligent Machining, International Journal of Engineering Manufacture: Proceedings of the Institution of Mechanical Engineers Part B, UK.
• van Niekerk, T.I., Hattingh D.G., 2004, Multi-Sensor Fusion Model for On-line Surface Roughness Prediction, Research and Development Journal, 20 (2) incorporated into the SA Mechanical Engineer, July.
• T.I. van Niekerk1, T. Hua2 and D.G. Hattingh1 , 2007, Experimental Implementation of Complex Curvature Friction Stir Welding, R & D Journal, 2007, Volume 23 , Number 2, July,  South African Institution of Mechanical Engineering
• van Niekerk T.I., D.G. Hattingh, T. Hua, and J-Q. Wang, 2008,  Knowledge-based robot vision system for automated part handling, June, South African Journal of Industrial Engineering, ISSN 1012-277X,
• Vusisizwe Mancapa, T.I van Niekerk, and T. Hua,  2009, A Genetic Algorithm for the Two Dimensional Strip Packing Problems, South African Journal of Industrial Engineering, SAIIE, Vol 20, No 2, November 2009,  ISSN 1012-277X.
• Kranz J., van Niekerk T.I., Holdack-Janssen H., Gruhler G., 2011,   Automotive Thermal Comfort Control – A Blackbox Approach, South African Institute of Electrical Engineers (SAIEE) Africa Research Journal, November.
• Fernandes J.M., van Niekerk T., 2015, A programmable logic controller based laboratory -analysis of conventional and intelligent control schemes for non-linear systems, Journal for New Generation Sciences: Volume 13 Number 3.
• Cumberlege A., van Niekerk TI., 2015, Wireless fault monitoring of robotic cells using android tablet pcs within automotive production, Journal for New Generation Sciences: Volume 13 Number 3.
• Behre L., Becker U., van Niekerk T., Harndorf H., Mercorelli P., Werner N.,2015, An indirectly controlled high-speed servo valve for IC engines using piezo actuators, R & D Journal of the South African Institution of Mechanical Engineering 2015, 31, 35-45 http://www.saimeche.org.za (open access) © SAIMechE All rights reserved.
• Barnard M., van Niekerk T.I., 2018,   Neural Network Fault Diagnosis System for a Diesel-Electric Locomotive’s Closed Loop Excitation Control System, South African Institute of Electrical Engineers (SAIEE) Africa Research Journal, February.
• Oliver Raffler, U. Becker, T. van Niekerk,  Lucas Kohler, 2018, Novel mechatronics based highspeed piezo actuator, IFA Research Reports, ISBN: 978-3-8440-5015-8, Germany.