Non-destructive detection of machining-induced white layers through grain size and crystallographic texture-sensitive methods. (15th February 2021) - Brown, M.; Pieris, D.; Wright, D.; Crawforth, P.; M'Saoubi, R.; McGourlay, J.; Mantle, A.; Patel, R.; Smith, R.J.; Ghadbeigi, H.
Abstract: Detection of machining-induced white layers is currently a destructive inspection process with a form of cross-sectional microscopy required. This paper, therefore, reports on the development of a novel non-destructive inspection method for detecting white layers using grain size-sensitive and crystallographic texture-sensitive techniques. It is shown that x-ray diffraction can be used to detect white layers as thin as 5 μm in Ti-6Al-4 V through measurement of diffraction peak breadths and diffraction peak intensities, due to the influence of the sub 100 nm grain size and high lattice strain in the white layer, as well as the strong crystallographic texture in this titanium alloy. Compared to the existing optical microscopy inspection method, which can take days due to the number of steps involved, the x-ray diffraction peak breadth method offers non-destructive white layer detection in a matter of minutes at a resolution of 5 μm or less that competes directly with the optical method. Spatially resolved acoustic spectroscopy, a laser-generated ultrasonic surface acoustic wave detection method, can also be used to identify anomalous surfaces, containing a white layer or swept grain material, due to its sensitivity to the crystallographic texture changes that arise in severely plastically deformed Ti-6Al-4V as in Titanium with 6 % Aluminium and 4% Vanadium. Graphical abstract: Unlabelled Image Highlights: A novel x-ray diffraction method can be used to non-destructively detect machining-induced white layers. The technique measures peak broadening caused by the high strain and ultrafine grains which are intrinsic to white layers. White layers as small as 5 µm can be detected rapidly, compared to the time-consuming microscopy process commonly used. Anomalous surfaces can also be detected using laser ultrasonics, which are sensitive to crystallographic texture.