Towards the Development of Operational Digital Twins for Autonomous Manufacturing
In recent years advances in computing power along with the widespread availability of data has led process industries to consider a new paradigm for automated and more efficient operations. This trend is commonly referred to as “Industry 4.0” and many reports indicate that it can result in cost reductions of up to 20% while improving asset utilisation by 30 to 40%. Despite the research effort dedicated on techniques for the interpretation and efficient employment of big-data within the industry, the development of mathematical modelling and optimisation techniques that serve the requirements for seamless communication among the different levels of decision making has received considerably less attention. Contemporary process industries are part of a progressively complex global market network and the need to account for efficient and integrated solutions becomes increasingly mandatory. Nonetheless, as industries are moving towards more digitalised and continuous paradigms to need for designing computationally efficient frameworks for real-time decision making is becoming urgent. Integrating control with operations has gained considerable amount of research interest (Charitopoulos et al., 2018; Zhuge and Ierapetritou, 2012) due to the benefits of exploiting their underlying interdependence and optimising process operations. So far, most of the research works have dealt with integrating cyclic scheduling and control with little work done on the integration of planning, scheduling and control (iPSC). While considering process planning together with scheduling and control poses an additional degree of complication by exacerbating the multi-scale nature of the problem, their rigorous integration can result in enhanced and more resilient process operations in the face of uncertainty. In this talk, the development of a systematic model-based framework for the efficient online closed-loop implementation of the iPSC of continuous manufacturing processes will be presented. Results from case studies highlight the importance of integrated optimisation so as to increase flexibility and resilience in the face of uncertainty.
Dr. Vassilis Charitopoulos is a Lecturer (2019-) in the Department of Chemical Engineering, CPSE at UCL and an Associate Researcher at the Energy Policy Research Group at Cambridge Judge Business School. He specialises in developing mathematical programming models and solutions techniques for incorporating uncertainty considerations for process and energy systems engineering problems. Dr. Charitopoulos has received global recognition for his excellent research activity including: UCL Rooke Prize (2016), IChemE Best Young Researcher finalist (2018; 2019; 2020), Springer Thesis Award (2019), UCL David Newton Prize (2019). He was the recipient of an Early Career Fellowship (2019) from the Isaac Newton Trust, University of Cambridge for a project related to the stochastic optimisation of heat decarbonisation pathways in the UK. His current research focuses on the development of novel techniques for model-based and data-driven optimisation frameworks for digital process manufacturing and industrial heat decarbonisation with demand side response considerations.
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When: Sep 30, 2020 13:00 PM London
Topic: CPSE Summer Webinar Series: Dr Vasileios Charitopoulos (CPSE, University College London)
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The Centre for Process Systems Engineering (CPSE) is a multi- institutional research centre. It was inaugurated in August 1989 by Professor Roger W.H. Sargent and involves Imperial College London and University College London. Innovative and dynamic in its approach to research and development, CPSE’s accomplishments include the Queens Prize for Higher Education, presented in 2003 for research excellence and technology transfer. Three spin-out companies have been established. One of these, Process Systems Enterprise Limited (PSE), received the Royal Academy of Engineering’s MacRobert Award in 2007; this is the UK’s highest award for innovation in engineering. The Centre continues to broaden the scope of its activities over all size scales enabling all areas of process systems to be addressed. This enables CPSE to be responsive to the evolving needs of industry and society.