Automation

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AI is revolutionizing quality control in electronics manufacturing by enhancing inspection processes and reducing costs. Anna-Katrina Shedletsky emphasized the power of machine learning and deep learning to automate tasks, improve product quality, and deliver significant ROI, making quality control the perfect starting point for AI implementation.

The combination of closed loop quality systems and AI-driven machine vision is transforming manufacturing by enabling real-time adjustments and proactive problem-solving.

The manufacturing industry is evolving due to Artificial Intelligence (AI) and robotics, significantly impacting job outlooks, as highlighted by the U.S. Bureau of Labor Statistics. This article will explore quality trends and provide guidance for future changes.

Event-based vision technology addresses challenges in industrial machine vision, such as data overload and the need for real-time processing, by efficiently capturing changes in a scene with high speed and low power consumption.

Discover how advancements in AI and automation are transforming universal testing machines, offering enhanced accuracy and safety while posing new challenges in workforce training and user experience.

Medical device companies are adopting APIs to enhance operational efficiency and speed up product development while meeting regulatory requirements. APIs enable seamless data exchange between software systems, streamlining processes like clinical trial data collection and quality management.

A3 President Jeff Burnstein shares insights on the growing automation trend, highlighting advancements in humanoid robots and autonomous mobile technologies aimed at enhancing productivity and safety across industries.

Discover how AI-powered machine vision is revolutionizing manufacturing by streamlining defect detection and enhancing vision-guided robotics, driving efficiency and quality to new heights!

Despite advancements in intelligent automation, human oversight remains crucial in navigating complex warehouse environments. This article highlights the enduring role of humans in the future of robotics, emphasizing a human-centered approach to automation.

Nicholas Blake of Advex AI explains how synthetic examples can be used to help improve training models, what machine vision offers, and how AI inspection can cut training time down from years to hours.