Temperature field in modulation-assisted machining

Abstract Modulation-Assisted Machining (MAM) is a novel machining process where a controlled low-frequency oscillation is superimposed on the tool feed during cutting so as to allow intermittent disengagement of the tool from the workpiece, resulting in discrete chip formation. While MAM has been shown to significantly reduce tool wear when compared to conventional machining, fundamental mechanisms responsible for the reduced tool wear remain unclear. This study explores the role of temperature through in-situ measurement of the cutting tool temperature during MAM. The tool temperature distribution is captured using a medium-wavelength high-speed infrared imaging system. This in-situ data is used to analyze spatiotemporal variations in temperature distribution along the tool rake face during MAM. The results show that the average tool-chip contact temperature in MAM is lower than that in conventional machining under the same material removal rate. An analytical model is presented to capture the periodic heating and cooling cycles in MAM and identify the fundamental factors contributing to tool temperature reduction in the presence of feed modulation. The combined experimental and modeling framework presented in the study serves as a valuable tool for investigating the effect of various modulation parameters on tool temperature distribution and identifying optimal MAM conditions to improve tool performance.

Authors

Institutions

Publication Details

Journal
Journal of Manufacturing Science and Engineering
Published
2026-06-24
DOI
https://doi.org/10.1115/1.4072229
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Temperature field in modulation-assisted machining

Dinakar Sagapuram, R. Narasimhan, Yang Guo, Jobin T. Mathews
Journal of Manufacturing Science and Engineering
Advanced machining processes and optimization
article

Temperature field in modulation-assisted machining

Dinakar Sagapuram, R. Narasimhan, Yang Guo, Jobin T. Mathews
article en

Abstract

Abstract Modulation-Assisted Machining (MAM) is a novel machining process where a controlled low-frequency oscillation is superimposed on the tool feed during cutting so as to allow intermittent disengagement of the tool from the workpiece, resulting in discrete chip formation. While MAM has been shown to significantly reduce tool wear when compared to conventional machining, fundamental mechanisms responsible for the reduced tool wear remain unclear. This study explores the role of temperature through in-situ measurement of the cutting tool temperature during MAM. The tool temperature distribution is captured using a medium-wavelength high-speed infrared imaging system. This in-situ data is used to analyze spatiotemporal variations in temperature distribution along the tool rake face during MAM. The results show that the average tool-chip contact temperature in MAM is lower than that in conventional machining under the same material removal rate. An analytical model is presented to capture the periodic heating and cooling cycles in MAM and identify the fundamental factors contributing to tool temperature reduction in the presence of feed modulation. The combined experimental and modeling framework presented in the study serves as a valuable tool for investigating the effect of various modulation parameters on tool temperature distribution and identifying optimal MAM conditions to improve tool performance.

Journal of Manufacturing Science and Engineering
Wellborn Road Veterinary Medical Center (US), Michigan State University (US)
Affordable and clean energy
Openalex Percentile: Top 13%
Advanced machining processes and optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.