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Glass fiber reinforced plastic (GFRP) composites, initially developed for home insulation, are now essential in aerospace, automotive, marine, and construction industries due to their lightweight, corrosion resistance , and high mechanical strength . However, their anisotropic and heterogeneous nature, coupled with the abrasive behavior of glass fibers, poses significant machining challenges, including rapid tool wear , surface defects , delamination , and subsurface damage. This review systematically examines recent advancements and strategies to address these challenges across machining methods such as turning, milling, drilling, grinding , and tapping . It highlights the influence of cutting regimes, tool geometries, and advanced coatings on machinability and surface integrity. The review also evaluates the impact of cutting environments, including cryogenic cooling , minimum quantity lubrication , and hybrid machining, on cutting forces, tool wear, chip morphology, and surface quality. A key contribution is the exploration of emerging techniques like vibration-assisted and thermally-assisted machining, alongside computational tools such as finite element modeling , artificial intelligence, and artificial neural networks . These tools optimize machining conditions, predict outcomes, and reduce experimental costs. Promising strategies, including advanced coatings (e.g., PCD , TiN, CBN) and simulation-driven approaches, are identified to enhance machinability. By addressing the complex interplay between machining parameters, material properties, and surface quality, this article offers a concise framework for improving the precision, efficiency, and cost-effectiveness of machining GFRPs , paving the way for optimized processes in next-generation composite materials.
Pereira et al. (Wed,) studied this question.