436-434 Mechatronic Systems and Data Fusion

This is an advanced final-year elective. Familiarity with the content of prescribed subjects in the first four years of the mechatronics or manufacturing course will be assumed.

Upon completion, students should have gained an overview of systems engineering concepts and their relevance to mechatronics, and their application in intelligent machines and manufacturing systems. Students should also have gained an overview of basic concepts of data mining and data fusion in their relevance to mechatronic systems.

Topics covered include general systems concepts, overview of mechatronic system design methods, system architectures; concurrent engineering; hardware-software co-design, embedded systems; mechatronic system modelling techniques, systems engineering approaches in computer-integrated manufacturing and flexible manufacturing systems; concepts of data fusion and data mining with particular emphasis to robotics and automotive applications; integration in micro-electromechanical systems; introduction to nano-technology; and case studies.

One 3-hour examination (70%); assignments and seminar presentations not exceeding the equivalent of 20 pages including computations, diagrams, tables and computer output (30%). Students will be notified of the weighting of the non-examination assessment components at the beginning of semester.