November 13, 2025
Time: 11:00 AM ET | 10:00 AM CT | 8:00 AM PT
Duration: 60 Minutes
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Summary
Remote laser welding has become a key technology in modern manufacturing thanks to its speed, flexibility, and scalability. However, the process also brings challenges such as high scrap rates, quality assurance issues, and the growing demand for volume production. To address these problems, advanced sensor technologies have been developed, ranging from pyrometry and diode-based sensors to vision systems, light-section sensors, and OCT-based solutions. Each of these approaches offers advantages, but also comes with limitations. Traditional alternatives like destructive testing are costly and inefficient, underlining the need for smarter, real-time solutions.
Artificial intelligence plays a crucial role in unlocking the full potential of these sensors. By processing large amounts of data and enabling sensor fusion, AI allows manufacturers to combine the strengths of different technologies, improving defect detection, process stability, and overall efficiency. OCT data evaluation, for instance, benefits greatly from AI-driven analysis, enabling deeper insight into weld quality. Looking ahead, the integration of AI-powered sensor fusion will not only overcome compatibility hurdles but also deliver measurable benefits to customers -- ensuring higher quality, reduced costs, and greater confidence in remote laser welding applications.