JOURNAL ARTICLE

Tool wear rate prediction in ultrasonic vibration-assisted milling

Abstract

In the current study, a predictive model on tool flank wear rate during ultrasonic vibration-assisted milling is proposed. One benefit of ultrasonic vibration is the frequent separation between tool and workpiece as the cutting time is reduced. In order to account for this effect, three types of tool–workpiece separation criteria are checked based on the tool center instantaneous position and velocity. Type I criterion examines the instantaneous velocity of tool center under feed movement and vibration. If the tool is moving away from workpiece, there is no contact. Type II criterion examines the position of tool center. If the tool center is far from the uncut workpiece surface, there is no contact even though the tool is getting closer. Type III criterion describes the smaller chip size due to the overlaps between current and previous tool paths as a result of vibration. If any criterion is satisfied, the tool flank wear rate is zero. Otherwise, the flank wear rate is predicted considering abrasion, adhesion and diffusion. The proposed predictive tool flank wear rate model is validated through comparison to experimental measurements on SKD 61 steel with uncoated carbide tool. The proposed predictive model is able to match the measured tool flank wear rate with high accuracy of 10.9% average percentage error. In addition, based on the sensitivity analysis, smaller axial depth of milling, larger feed per tooth or higher cutting speed will result in higher flank wear rate. And the effect of vibration parameters is less significant.

Keywords:
Flank Machining Tool wear Vibration Abrasion (mechanical) Grinding Ultrasonic sensor Position (finance) Materials science Machine tool Mechanical engineering Acoustics Engineering

Metrics

50
Cited By
3.06
FWCI (Field Weighted Citation Impact)
32
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced machining processes and optimization
Physical Sciences →  Engineering →  Mechanical Engineering
Advanced Machining and Optimization Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Surface Polishing Techniques
Physical Sciences →  Engineering →  Biomedical Engineering

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