Mathematical Model Development for AI Gesture Classification in Industrial Motion and Time Study

This study presents the development of an artificial intelligence (AI) algorithm designed to classify work motions in a production process, utilizing Python and OpenCV. The proposed AI algorithm comprises three key components: motion detection, motion classification, and work cycle separation. To validate its accuracy, the algorithm was evaluated in a controlled experiment, comparing AI-based motion assessments with those conducted by human appraisers. Statistical analysis of the results demonstrated a high level of agreement between the AI system, established standards, and human assessments. Motion and time studies are essential for waste elimination in process improvement initiatives. Advancing automated methods for conducting these studies significantly reduces the resources traditionally required when performed manually. Furthermore, this technology offers small and medium-sized enterprises (SMEs) a cost-and time-effective solution for achieving process improvement goals.