Secure and Sustainable Mechatronic Systems

Includes a review of AI and machine learning for topology optimisation and generative design in additive manufacturing. A mechatronic system must be dependable in two distinct senses. It must resist attack through the interfaces by which it is operated, and it must be built and maintained in ways that do not exhaust the resources it depends on. This book treats those two requirements together, on the view that both are properties of how a system is designed rather than features added to it afterwards. Two chapters address security where it meets operational technology. Engineering workstations used for machine programming and controller configuration are routinely exposed to removable media, and the first chapter develops a forensic intelligence framework for reconstructing what was connected and what was transferred. The second turns to phishing, a common initial access vector in attacks on manufacturing and utilities, and grounds a language model’s judgement in retrieved evidence rather than generation alone, reporting the false-positive behaviour that determines whether such a system is deployable. The remaining chapters address sustainability and biomedical systems modelling. A review examines how artificial intelligence has accelerated topology optimisation and generative design in additive manufacturing to the point where lightweight, load-path-optimised components are produced routinely, treating data scarcity, interpretability and certification as the real barriers. The closing chapter develops a compartmental model of tick-borne disease transmission and its stability behaviour, framed so that the derived thresholds could trigger a sensor-driven surveillance system