Smart welding cells in Industry 4.0: optimization of manufacturing processes using collaborative robots and artificial intelligence

Abstract

In the modern industry, welding processes represent a critical stage of production that directly affects the quality, safety, and reliability of final products. The development of the Industry 4.0 paradigm has enabled the integration of advanced technologies, such as collaborative robots and artificial intelligence, with the aim of enhancing the flexibility, productivity, and adaptability of manufacturing systems. This paper investigates the application of smart welding cells based on human–robot collaboration, supported by AI algorithms for process optimization. The proposed system integrates a collaborative robot, sensor systems, and machine learning models for real-time monitoring and adaptive control of welding parameters. Emphasis is placed on weld defect detection using visual and process data, as well as on the prediction of weld quality. This analyse includes a comparison between a traditional welding approach and an automated system incorporating an AI-based model. The research results indicate significant improvements in weld quality, a reduction in defect rates, and optimization of cycle time. Additionally, a decrease in unplanned downtime and an increase in overall system efficiency were observed. The integration of collaborative robots enables safe and efficient interaction with human operators, while AI supports fast and reliable decision-making in real time.