Accelerate your Career with a Master of Engineering in Design and Manufacturing
A course that sets out to develop a basic understanding of machine intelligence and explore modern intelligent manufacturing systems. Through lectures, group discussion, assigned readings, and projects the course participants will examine how knowledge-based systems (KBSs) and artificial neural networks (ANN) can improve the performance of machine tools, work cells, and overall manufacturing enterprises. Students will also explore new fabrication processes that have emerged because of advances in software.
Course Leader: George Knopf, PhD, P.Eng., Western University
Intelligent Manufacturing involves a variety of software technologies and novel flexible fabrication processes that enable efficient and cost effective automation for small, medium and large-scale discrete product manufacturing. These advanced technologies provide opportunities and introduce challenges to traditional product development engineers, system designers, and manufacturing personnel. The first module will focus on intelligent systems in manufacturing and the application of artificial intelligence on improving product design, system control, process planning and fault diagnostics. Through lectures, group discussions, assigned readings, and group midterm project the participants will develop a basic understanding of machine intelligence and explore how knowledge-based systems and adaptive artificial neural networks can improve the performance of machine tools, work cells, and overall manufacturing enterprises. The second module will explore automated fabrication and manufacturing processes that have emerged because of advances in software and computing hardware. The students will exploit the principles of machine intelligence and flexible manufacturing by undertaking an individual final project.
At the end of the course, each student should be able to:
Each student is expected to attend all sessions and participate fully in all discussions, assignments and projects. Active participation is critical because a significant portion of class time has been allocated towards group discussions and assignments. Students require a laptop each day of each module and may be required to access interactive tools for simplified AI programming.
Midterm project report (group) and preparation of presentations on the implementation of an AI technique (KBS, FL, ANN) for an engineering design or manufacturing application.
Final project report (individual) on an advanced fabrication technology or automated system that improves the efficiency or enhances an industrial process. The completed course project is to be electronically transmitted to the course instructor within 2 weeks of the last lecture in Module II.
Course notes and supplemental reading material are provided to complement the lectures in Module 1 and Module 2.
George Knopf is a Professor in the Department of Mechanical and Materials Engineering at Western University. His research interests include bioelectronics, biosensors, laser material processing, and micro-optical transducers. Dr. Knopf’s current work involves the development of conductive graphene-based inks and novel fabrication processes for printing electronic circuitry on a variety of mechanically flexible substrates (polymers, paper, silk). He has acted as a technical reviewer for numerous academic journals, conferences, and granting agencies and has co-chaired several international conferences. In recent years, he has also co-edited two books entitled “Smart Biosensor Technology” and “Optical Nano and Micro Actuator Technology”.