Professor Roy Kalawksy, Imperial College London

Professor Kalawsky’s research focusses on delivering novel innovations for aerospace digital transformation by developing new digital engineering/manufacturing techniques and improved information systems, allowing engineers to process and access intrinsically linked critical data and information across a product’s lifecycle and its wider aerospace enterprise.

Aerospace products are inherently complex, having an information life-cycle spanning several decades, spanning product design, manufacture, in-service operation and retirement. However, optimising the design of an aircraft across such a long-time frame requires design and technical trade-off decisions to be taken between different disciplines and stakeholders over the product’s life-cycle. Consequently, development of aircraft to meet future needs, against increasing regulatory demands (such as NetZero) are leading to ever more complicated integration of aircraft and its systems, and with the increasingly complex air transport system of systems. Crucially, coupling this with the need for faster/leaner production rates, requires a radically different departure from traditional aircraft manufacturing processes.

An important element of Kalawsky’s research is the underpinning science and engineering to establish new methodologies to create digitally defined products and their associated complex engineering information systems. At the heart of this is the need for a seamless digital thread, including the acquisition, processing and representation of data from experts (tacit knowledge), design systems, factory inspection systems through to availability of in-service live product performance data. The goal is to facilitate human interaction with decision making systems by development of next generation information architectures through novel digital access technologies. The information architecture in this case is being realised with new model-based systems engineering (MBSE) paradigms; systems of systems engineering, system integration, executable surrogate models with co-simulation to create next generation digital-twins employing interactive optimisation methodologies employing AI/machine learning, visual analytics and immersive technologies (including augmented/virtual reality).