Prediction of cutting forces during micro end milling considering chip thickness accumulation

By Szymon Wojciechowski, M. Matuszak, B. Powałka, M. Madajewski, R. Maruda, G. Królczyk. 2019

195 citations recorded by the source corpus.

Abstract This study focuses on the prediction of cutting forces during micro end milling using a novel approach that takes into account the chip thickness accumulation phenomenon. The proposed original force model considers the micro end milling kinematics, geometric errors of the machine tool–toolholder–mill system, elastic and plastic deformations of workpiece correlated with the minimum uncut chip thickness, and flexibility of the slender micro end mill. It also includes a novel analytical approach for the instantaneous area of cut. The chip thickness accumulation phenomenon can be manifested as chip thickness variations in the current tool rotation, resulting from material burnishing and elastic recovery in all previous tool rotations. The predicted forces consider the minimum uncut chip thickness value, which has been estimated directly from the micromilling process of AISI 1045 steel based on an original analytic–experimental approach that applies the identification of a stagnant point in the milling process. The results obtained show that the instantaneous and average micromilling forces determined using the proposed model have considerably better conformity with the experimental forces than those predicted using the commonly used rigid micro end milling model. Moreover, the non-linearity of the cutting forces as a function of feed per tooth is strongly affected by multiple cutting mechanism transitions observed during micromilling with uncut chip thicknesses close to the minimum uncut chip thickness value.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/4a45bf58e90f23672205182f262251af1acb81e0

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In Biomedical Engineering

  1. Rachid M'Saoubi
  2. Dragos Axinte
  3. Z. Liao

In Electrical and Electronic Engineering

  1. Rachid M'Saoubi
  2. Dragos Axinte
  3. Z. Liao

In Mechanical Engineering

  1. Rachid M'Saoubi
  2. Dragos Axinte
  3. A. Clare
  4. Z. Liao
  5. I. S. Jawahir

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