Quality spoke with David Dechow of Machine Vision Source following his recent presentation at The Quality Show South about vision solutions for quality applications and integration that drives application success with current and emerging technologies.
The engineering work landscape is rapidly evolving with technologies like artificial intelligence, robotics, and additive manufacturing. Many engineers lack practical skills, and the industry faces a significant skills gap. Read how addressing this gap is crucial for engineering learning and development.
AI, despite its hype, often causes delays in manufacturers' automation strategies due to confusion and fear. Fundamentally, AI complements machine vision, which uses handcrafted algorithms needing new formulas and trial-and-error development for each product type or feature.
Quality managing editor Michelle Bangert talked with Justin Newell, CEO of Inform North America, who recently wrote an article for Quality on trustworthy AI.
New calibration software trends simplify processes, enhance traceability, ensure compliance, and drive data-driven accuracy in response to increasing demands for precision.
Manufacturers are integrating metrology, using data analytics, automating maintenance, and embedding measurement processes in production for greater efficiency and predictability.
AI is revolutionizing quality control in manufacturing, driving us into Industry 4.0 and beyond. Manufacturers can streamline processes, boost efficiency, and deliver top-notch products globally. Embracing AI isn't just advantageous; it's essential for thriving in today's economy. Businesses must invest in AI to empower their workforce and stay ahead in the rapidly evolving manufacturing landscape.
Discovering, evolving, and sometimes unsettling, artificial intelligence mirrors our human learning. Yet, as it integrates further, questions arise: Can it handle quality assurance? What's in the future? And crucially, how much control are we comfortable relinquishing to it?