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Mechanical & Materials Engineering

Brian W. Surgenor, P.Eng

Intelligent Automation Laboratory.

The Intelligent Automation Laboratory (IAL) operates under the direction of Brian W. Surgenor. The basic research interest has been on the control of pneumatic servosystems. However, exposure to industrially based automation problems led to an applied research interest in the development of intelligent algorithms for machine vision systems as applied to inspection in manufacturing processes. 

A mechatronic systems design approach is taken, given that projects undertaken by the IAL require expertise in the disciplines of computing, electrical and mechanical engineering.

NAMRI

Recent Publications (selected)

Chauhan, V.D., Joshi, K.D. and Surgenor, B.W. (2017) “Object Detection and Classification using a Hybrid Approach of Semi-Supervised SVM”, 10th Int. Conf. on Machine Vision (ICMV), Nov. 13-15, 2017, Vienna, Austria.

Joshi, K.D., Surgenor B.W. and Chauhan, V.D. (2016) “Analysis of Methods for the Recognition of Indian Coins: A Challenging Application of MV to Automated Inspection”,  23rd Int. Conf. on Mechatronics and Machine Vision in Practice (M2VIP), Nov. 28-30, Nanjing, China.

Chauhan, V. and Surgenor, B.W.(2015). “A Comparative Study of Machine Vision Based Methods for Fault Detection in an Automated Assembly Machine”, Procedia Manufacturing (43rd Proc. North American Manufacturing Research Institution of SME), Vol. 1, pp.  416-428.

Fernando, H. and Surgenor, B.W. (2015) "An Unsupervised Artificial Neural Network Versus a Rule-Based Approach for Fault Detection and Identification in an Automated Assembly Machine", Robotics and Computer Integrated Manufacturing, http://dx.doi:10.1016/j.rcim.2015.11.006.

Fernando, J., Lounsbury, C. and Surgenor, B.W. (2014) “Integrating RFID Technology into a Course in Mechatronics”, Proc. Int. Conf. on Engineering Education and Research, (iCEER 2014) Hamilton, Ont., Aug. 24 to 26.

Hughes, K., Fernando, H., Szkilnyk, G., Surgenor, B.W. and Greenspan M. (2014) "Video Event Detection for Fault Monitoring in Assembly Automation", Int. Journal Intelligent Systems Technologies and Applications, Vol. 13, Nos. 1/2, pp. 103-116.