Monitoring and Predicting the Surface Generation and Surface Roughness in Ultraprecision Machining: A Critical Review

The aim of manufacturing can be described as achieving the predefined high quality product in a short delivery time and at competitive cost. However, it is unfortunately quite challenging often difficult to ensure that certain characteristics products are met following contemporary paradigm, such surface roughness, texture, topographical requirements. Ultraprecision machining (UPM) requirements common essential for components with optical finishing, including larger highly accurate mirrors, infrared optics, laser devices, varifocal lenses, other freeform optics satisfy technical specifications precision devices without further post-polishing. provide precision, complex nanometric level finishing. Nevertheless, process requires an in-depth comprehensive understanding system, diamond turning various input parameters, tool features able alter efficiency, machine working environment conditions, even workpiece tooling materials. non-linear nature UPM poses major challenge prediction generation Recent advances Industry 4.0 learning providing effective means optimization particularly through in-process monitoring while avoiding conventional trial-and-error approach. This paper attempts critical review on state-of-the-art in-surfaces processes, well discussion exploration future research field Artificial Intelligence (AI) digital solutions harnessing practical issues process, real-time. In paper, implementation application perspectives also presented, focusing industrial-scale applications aid advanced models, algorithms, digital-enabling technologies.