Tool Wear Estimation Under Different Feed Conditions via Cutting Force Coefficients Derived from Cutting Power Consumption

Abstract

This study proposes a compact cutting power-based framework for estimating flank wear width (VB) in full-slot end-milling of Ti-6Al-4V under varying feed conditions without additional force sensing systems. Relationships between cutting force coefficients and VB were directly incorporated into an analytical cutting-power model, and the model parameters were identified using ordinary least squares. This formulation yields a closed-form estimator for VB using measured cutting power and process parameters. Milling experiments were conducted at spindle speeds of 800 rpm, 1025 rpm, and 1250 rpm and feed per tooth values of 0.03 mm/tooth, 0.035 mm/tooth, and 0.04 mm/tooth. For each spindle speed, the model was calibrated using the two boundary feed conditions and evaluated at the intermediate condition of 0.035 mm/tooth. The estimated VB generally tracked the measured wear progression, with root mean square error values of 2.88 μm, 14.95 μm, and 14.72 μm at 800 rpm, 1025 rpm, and 1250 rpm, respectively. The proposed approach demonstrates that tool wear can be estimated from cutting power with a limited calibration dataset and provides a simple basis for practical tool condition monitoring within the calibrated feed range.