Infrared Thermography (IRT) has emerged as a powerful non-contact technique for real-time process monitoring, defect detection, and quality assurance in advanced manufacturing. Its rapid, full-field imaging capability makes it particularly suitable for dynamic thermal processes such as welding and metal additive manufacturing (AM). Over the past two decades, IRT has progressed from a primarily qualitative inspection method to a quantitative diagnostic and control tool, supported by advances in detector technology, calibration methodologies, data analytics, and artificial intelligence. This paper presents a structured review of IRT applications in welding and additive manufacturing, addressing radiative heat transfer considerations, emissivity-related measurement uncertainty, defect-induced thermal signatures, and integration with process modelling and machine learning frameworks. A comparative evaluation of thermographic implementation in welding and AM is provided, highlighting process-specific challenges and limitations. The review also identifies key constraints related to emissivity variation, defect detectability limits, and measurement uncertainty, while outlining future research directions toward digital twin integration and intelligent manufacturing systems.
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Sudhir Y. Kumar (2026) studied this question.
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