Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—Manufacturing factories, having continuous pursuit of productivity and quality, often meet challenges in coping with high production complexities and uncertainties. These are the areas in which traditional manufacturing paradigms underperform due to the limitation of human operators’ ability to cope with these complexities, uncertainties, understanding/memorizing big data, and also their inability to make time demanding decisions. Intelligent manufacturing systems, on the other hand, can yield superior results compared to traditional manufacturing systems as they are capable of analyzing, self-learning, apprehending complexities and are also able to store and analyze large amounts of data to obtain increased quality of the product and lower production cost while shortening the time-to-market. The aim of this paper is to outline the recent accomplishments and developments in intelligent scheduling, process optimization, control, and maintenance. For each aspect, concepts, requirements, application implemented, and methodologies deployed are also presented.
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