This article reviews the existing work in selfhealing and self-repairing technologies, including work in software engineering, materials, mechanics, electronics, MEMS, self-reconfigurable robotics, and others. It suggests a terminology and taxonomy for self-healing and selfrepair, and discusses the various related types of other self-* properties. The mechanisms and methods leading to selfhealing are reviewed, and common elements across disciplines are identified.
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We describe the novel fabrication of a 3D electrical small antenna and its subsequent characterization. The patterning of meander lines conformed onto a hemispherical substrate is achieved by 3D holographic photolithography, which uses time-division multiplexing of a series of iteratively optimized computer-generated holograms. The meander lines have a line width of 100 μm and line separation of 400 μm, with a line pitch of 500 μm and a total meander length of 145 mm. The working frequency is found to be 2.06 GHz, with an efficiency of 46%. This work demonstrates a new method for the fabrication of 3D conformal antennas.
Autonomy has become a focal point for research and development in many industries. Whilst this was traditionally achieved by modelling self-engineering behaviours at the component-level, efforts are now being focused on the sub-system and system-level through advancements in artificial intelligence.Exploiting its benefits requires some innovative thinking to integrate overarching concepts from big data analysis, digitisation, sensing, optimisation, information technology, and systems engineering.With recent developments in Industry 4.0, machine learning and digital twin , there has been a growing interest in adapting these concepts to achieve autonomous maintenance; the automation of predictive maintenance scheduling directly from operational data and for in-built repair at the systems-level.However, there is still ambiguity whether state-of-the-art developments are truly autonomous or they simply automate a process.In light of this, it is important to present the current perspectives about where the technology stands today and indicate possible routes for the future. As a result, this effort focuses on recent trends in autonomous maintenance before moving on to discuss digital twin as a vehicle for decision making from the viewpoint of requirements, whilst the role of AI in assisting with this process is also explored.A suggested framework for integrating digital twin strategies within maintenance models is also discussed. Finally, the article looks towards future directions on the likely evolution and implications for its development as a sustainable technology.Click here to view linked References
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