Minimizing Risks in Close Proximity ARC Welding with Autonomous AI-Powered Welding System: Risk Assessment and Hazard Prevention

Arc welding is a critical process in many industries that involves the use of high heat and intense light to join metal components. However, the process also poses significant risks to welders and co-workers, such as exposure to UV/IR radiation, high temperatures, electrical hazards, toxic fumes, and noise. To minimize these risks, this research proposes the use of an autonomous AI-powered welding system that integrates various sensors and actuators to monitor and control the welding process. The system includes UV/IR radiation sensors, temperature sensors, electrical sensors, gas sensors, noise sensors, and motion sensors that collect data on the welding environment and conditions. The data is then transmitted to a microcontroller and subsequently to a computer, which uses artificial intelligence algorithms to analyze the data and make necessary adjustments to the welding process. These adjustments may include controlling the welding power source, the shielding gas flow, the noise levels, and the workstation position and orientation. The objective of this research is to assess the risks associated with close proximity arc welding and develop a sensor-based system that can effectively minimize these risks while maintaining the quality of the welding process. The study will include a risk assessment of the various hazards and their effects on welders and co-workers, as well as a detailed analysis of the performance of the AI-powered welding system. The results of this study have the potential to make a significant impact on the welding industry by reducing the risks associated with close proximity arc welding and improving the overall safety and health of welders and co-workers. The proposed system can also improve the efficiency and effectiveness of the welding process, making it more cost-effective and sustainable for industries in the long-term.