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Engineering and Technology OPEN ACCESS

Modeling Interfacial Temperature Distribution to Enhance Machining Condition Optimization

Chinedu Okafor
Department of Engineering and Technology, Lagos, Nigeria
tajet 2026
VOL. 8 / NO. 10 OCTOBER
FULL TEXT PP. 110-119
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VOLUME 8
ISSUE 10
YEAR 2026
PAGES 110-119
RESEARCH OVERVIEW

Abstract

Temperature distribution at the tool–workpiece interface is a critical factor governing machining performance, tool wear, surface integrity, and process stability. During metal cutting, plastic deformation, friction, and heat transfer generate complex thermal fields that vary with cutting speed, feed rate, depth of cut, tool geometry, and lubrication conditions. Accurate estimation of these fields is challenging because the cutting interface is difficult to access directly, while individual measurement techniques provide incomplete or spatially limited information. This paper develops a theoretical and computational framework for modeling interfacial temperature distribution and integrating thermal predictions into machining-condition optimization. The proposed approach combines transient heat-transfer equations, a moving heat-source representation, tool–workpiece thermal interaction, numerical simulation, and experimental validation through infrared thermography and tool–workpiece thermocouple measurements. Inverse heat-transfer analysis is considered for estimating inaccessible interface temperatures from measurable thermal responses. The framework also incorporates machining performance indicators, including surface roughness, residual stress, and thermal loading, to support multi-objective parameter selection. The synthesis of the provided literature identifies the importance of measurement validation, thermal boundary-condition definition, and coupling between temperature prediction and machining quality. In particular, established work on in-situ machining-temperature measurement provides a methodological foundation for assessing the reliability of thermal observations (Kara Ali et al., 2019). The resulting framework offers a structured basis for improving thermal prediction and selecting machining conditions, although its numerical performance must be established through material-specific experiments rather than assumed without validation.

RESEARCH TOPICS

Keywords

Interfacial temperature metal cutting machining optimization

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