Image Processing for Quantification of Machining Induced Changes in Subsurface Microstructure

Abstract

Subsurface microstructure and subsurface microhardness are two important aspects of surface integrity in machining operations to assess the quality of a product. Traditionally, subsurface microstructure is examined using visual metallographic techniques. However, in some cases, visual inspections fail to provide an explanation for changes in the material properties. This paper presents research with three samples of Ti-6Al-4V titanium alloy machined using dry, wet and cryogenic cooling environments. The subsurface microhardness of the samples is then measured and Scanning Electron Microscope (SEM) micrographs of the subsurface microstructure are produced. A new method is proposed to quantify the SEM micrographs. The proposed method is based on image processing techniques and aims to provide a measurable parameter for the concentration of various phases of material at each given distance below the machined surface. Visual comparison of the results from the proposed method with the subsurface microhardness of the material indicates that it has the potential to provide a more robust understanding of the machining induced changes in the subsurface microstructure of workpiece material