Abstract
In this work, a geometric model for surface generation of finish machining was developed in MATLAB, and subsequently verified by experimental surface roughness data gathered from turning tests in Ti-6Al4V. The present model predicts the behavior of surface roughness at multiple length scales, depending on feed, nose radius, tool edge radius, machine tool error, and material-dependent parameters—in particular, the minimum effective rake angle. Experimental tests were conducted on a commercial lathe with slightly modified conventional tooling to provide relevant results. Additionally, the model-predicted roughness was compared against pedigreed surface roughness data from previous efforts that included materials 51CrV4 and AL 1075. Previously obscure machine tool error effects have been identified and can be modeled within the proposed framework. Preliminary findings of the model’s relevance to subsurface properties have also been presented. The proposed model has been shown to accurately predict roughness values for both long and short surface roughness evaluation lengths, which implies its utility not only as a surface roughness prediction tool, but as a basis for understanding three-dimensional surface generation in ductile-machining materials, and the properties derived therefrom.
Highlights
The roles of minimum uncut chip thickness and side flow on increasing surface roughness in finish turning have been acknowledged for some time
The hmin effect is widely recognized as resulting from the finite sharpness of the cutting edge, and Albrecht [3] was among the first to demonstrate the relevance of the cutting edge radius to process forces, as well as surface generation
This article outlines an iterative geometric model which is based on novel assumptions, intended to more accurately capture surface generation in finish machining
Summary
The roles of minimum uncut chip thickness and side flow on increasing surface roughness in finish turning have been acknowledged for some time. Zhao [31] established a roughness prediction model that demonstrated an increase in roughness due to side flow He et al [32] has developed a model for diamond turning that incorporates plastic side flow based on a minimum chip thickness value. This article outlines an iterative geometric model which is based on novel assumptions, intended to more accurately capture surface generation in finish machining (using finish turning as a representative process to demonstrate the methodology) This effort will be concentrated on examining the surface roughness prediction capabilities of a new iterative modeling approach, which is an indication of valid surface generation assumptions. While such surface integrity characteristics are outside the scope of the current manuscript, subsequent work will illustrate the intimate connection between the present (geometric) work, and surface integrity (thermomechanical material property) evolution
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