Review of Image Processing Methods for Surface and Tool Condition Assessments in Machining
Ali Erçetin, Oğuzhan Der, Fatih Akkoyun, Manjunath Patel Gowdru Chandrashekarappa, Ramazan Şener, Mücahit Çalışan, Nevzat Olgun, Ganesh R. Chate, K. N. Bharath
Abstract
This paper systematically explores the applications of image processing techniques in machined surface analysis, a critical area in industries like manufacturing, aerospace, automotive, and healthcare. It examines the integration of image processing in traditional Computer Numerical Control (CNC) machining and micromachining, focusing on its role in tool wear analysis, workpiece detection, automatic CNC programming, and defect inspection. With AI and machine learning advancements, these technologies enhance defect detection, surface texture analysis, predictive maintenance, and quality optimization. The paper also discusses future advancements in high resolutions, 3D imaging, augmented reality, and Industry 4.0, highlighting their impact on productivity, precision, and challenges such as data privacy. In conclusion, image processing remains vital to improving manufacturing efficiency and quality control.