The Centre for Intelligent Autonomous Manufacturing Systems (i-AMS) in the Faculty of Engineering and Physical Sciences at Queen’s is an interdisciplinary team of researchers spanning the disciplines of Engineering, Computer Science, Applied Mathematics and Psychology working together to develop innovative technologies and solutions to address the challenges of Industry 4.0.

With the rapid developments in the Internet of Things (IoT) and its convergence with manufacturing Cyber Physical Systems (CPS), there is an increasing awareness of the major potential for impact of embedding this technology in factories of the future – in terms of improving the productivity, flexibility, resilience, responsiveness and energy efficiency of manufacturing systems and associated supply chains, and ultimately driving down costs, improving product quality and minimising waste (materials and energy).

Cooperative multi-robot and autonomous systems will also play a central role in delivering the underpinning flexible manufacturing systems. Here the vision is of robots as co-workers, with robots and humans working cooperatively and interactively to achieve common tasks, and of autonomous systems that are resilient and can adapt seamlessly as tasks and operating conditions change.

Many are describing the approaching era as the 4th industrial revolution. The German Government[1] have coined the phrase Industry 4.0, while in the UK and elsewhere it is referred to as The Industrial Internet[2]. As Industry 4.0 becomes a reality it will deliver comprehensive real-time monitoring and data collection across the whole manufacturing ecosystem from end to end.  The major challenge going forward is how to exploit the envisaged Industry 4.0 infrastructure and associated heterogonous real-time data streams and historical data repositories to deliver intelligent autonomous manufacturing systems that are ultimately self-optimising in terms of manufacturing competiveness and environmental sustainability.  

In i-AMS we recognise that tackling this challenge requires and interdisciplinary approach involving the integration of advanced data analytics, machine learning, intelligent system and autonomous robotics concepts with new design, digital manufacturing, human-robot interaction, and control paradigms. A multi-level manufacturing CPS architecture is envisaged where intelligence and autonomy are embedded at all levels - from individual sensors and machines (providing condition monitoring and prognostics functionality), to fleet level information sharing and coordination (enabling process improvement and enhanced predictive analytics) to system level supervisory control, decision making and scheduling (supporting virtual factory model development and synchronisation, and factory level optimisation of operating efficiency, production costs, carbon footprint etc.).


 Our research programme is centred around three themes:

(1) Virtual sensing, prognostics & Virtual Factory Simulations

(2) Flexible automation and cobotics

(3) Autonomous and Intelligent Decision making 

We are interested in developing new partnerships with industrial organisations so that research is focused on the most relevant and challenging industrial problems. Partnerships are sought from all sizes of organisations engaged in manufacturing with a full range of partnership platforms and leveraging opportunities available. We hope to develop and demonstrate research solutions and we are able to work across the full TRL spectrum. Academic partners are also sought to broaden and complement our internal themes of research strength.



[1] German Ministry of Education and Research, Project of the Future: Industry 4.0, http://www.bmbf.de/en/19955.php

[2] The Industrial Internet Consortium, http://www.iiconsortium.org/about-us.htm