Abstract
Using state-of-the-art in-situ characterization via high-speed optical microscopy and full-field digital image correlation analysis with nanometer resolution, Particle Image Velocimetry (PIV) as well as high bandwidth time-correlated process force analysis, this paper provides new quantitative insights into the complex dynamic variability present in the machining of Ti-6Al4V alloy, particularly at low uncut chip thicknesses where microstructural effects are most influential. Dynamically varying loads were analyzed across a wide range of uncut chip thicknesses (from 6 µm to 150 µm) and typical industrial cutting speeds for Ti-6Al4V alloy (30–120 m/min). The results reveal three distinct regimes of uncut chip thickness: from microstructural size effects at low thicknesses to quasi-steady state chip formation at intermediate uncut chip thickness to continuum-scale adiabatic shear banding at higher uncut chip thicknesses. Each regime is characterized by significantly different dominant mechanisms of chip formation, leading to variable sub-surface elastic and plastic loading with varying frequency/time and characteristic length scales. To minimize variability in thermomechanical loading and improve surface integrity in the cutting of Ti-6Al4V alloy at speeds between 30 and 120 m/min, our findings indicate an optimal uncut chip thickness range of 20–60 µm. These findings advance machining practices for Ti-6Al4V alloy, contributing to a new process optimization paradigm based on minimizing process and material-specific load variability to maximize as-machined component quality across multiple length scales.
| Original language | English |
|---|---|
| Article number | 118869 |
| Journal | Journal of Materials Processing Technology |
| Volume | 340 |
| DOIs | |
| State | Published - Jun 2025 |
Bibliographical note
Publisher Copyright:© 2025 Elsevier B.V.
Funding
This work was supported by the U.S. National Science Foundation , grant number 2143806 , project title “CAREER: Thermomechanical Response and Fatigue Performance of Surface Layers Engineered by Finish Machining: In-situ Characterization and Digital Process Twin”.
| Funders | Funder number |
|---|---|
| National Science Foundation Arctic Social Science Program | 2143806 |
Keywords
- In-situ characterization
- Predictive modeling
- Process signatures
- Surface integrity
ASJC Scopus subject areas
- Ceramics and Composites
- Computer Science Applications
- Industrial and Manufacturing Engineering
- Metals and Alloys