Dr Giovanna Martínez-Arellano (University of Nottingham): Abstract
The Industry 4.0 initiative promises to deliver highly automated, resilient, and flexible manufacturing systems that can react to current market and environmental challenges through the integration of digital technologies. From smart sensors and robotics, to artificial intelligence and data analytics, these Industrial Digital Technologies (IDTs) form the building blocks of future intelligent manufacturing systems. Applications of these are already seen across multiple areas of manufacturing systems such as process and condition monitoring, automated process control at the resource and system level and production line re-configuration to name a few. Intelligent Manufacturing is a multifaceted problem encompassing various levels of intelligence, from smart connection of sensors to cognitive, self-configuration, self-optimisation capabilities. Data Mining has become the recurring element that underpins each and every intelligence level, but despite current advancements, there is still a need for further development before IDTs become realistic to use at an industrial scale. This is particularly true for Small and Medium Enterprises.
This talk presents the current advancements on the application of data mining in the development of intelligent manufacturing systems and the challenges that are still faced for their wide integration in industry.