Point-by-point prediction of cutting force in 3-axis CNC milling machines through voxel framework in digital manufacturing

Omid Yousefian (), Andrey Balabokhin and Joshua Tarbutton
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Omid Yousefian: North Carolina State University
Andrey Balabokhin: University of South Carolina
Joshua Tarbutton: UNC Charlotte

Journal of Intelligent Manufacturing, 2020, vol. 31, issue 1, No 12, 215-226

Abstract: Abstract A new digital-based model is presented for the prediction of cutting forces in 3-axis CNC milling of surfaces. The model uses an algorithm to detect the work-piece/cutter intersection domain automatically for given cutter location, cutter and work-piece geometries. The algorithm uses a voxel-based representation for the workpiece and rasterized tool slice to detect the tool engagement. Furthermore, an analytical approach is used to calculate the cutting forces based on the discretized model. The results of model validation experiments on machining PMMA, Aluminum 6061 and 304 Stainless Steel are presented. Comparisons of the predicted and measured forces show that this digital approach can be used to accurately predict forces during machining.

Keywords: Cutting force prediction; Digital manufacturing; Voxel-based framework (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10845-018-1442-7

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