Articles Tagged with ''Artificial Intelligence (AI)''

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.

The 7th China International Import Expo (CIIE) in Shanghai featured 3,500 global exhibitors and the International Quality Innovation Forum, where I delivered a keynote on "AI Transformation in Quality and Metrology."

The manufacturing sector is poised for transformation by 2025 through automation and AI to tackle labor shortages. There is also a crucial emphasis on cybersecurity and analytics to future-proof supply chains against ongoing challenges.

This article explores the evolution of manufacturing data, the limitations of DMAIC in the Fourth Industrial Revolution, and introduces Binary Classification of Quality (BCoQ) and Learning Quality Control (LQC) systems as part of Quality 4.0.

A recent Idera report reveals that many industries view artificial intelligence positively. Judy Bossi, Vice President of Product Management at Idera, discusses AI's potential in quality assurance (QA), the challenges to adoption, and steps to effectively implement the technology.

Robotics is rapidly advancing from science fiction to practical uses across industries like manufacturing, logistics, and healthcare. Key trends include autonomous systems operating independently, robots collaborating with humans for improved productivity and safety, and AI integration that allows robots to learn and adapt. This technology enables both large enterprises and SMEs to optimize processes and meet growing demands.

Generative AI Searches are transforming how professionals access technical data in fields like inspection and gages. While these tools deliver quick results, reliance on their outputs can lead to inaccuracies, as shown by discrepancies in thread specifications. Understanding the strengths and limitations of Generative AI is essential for ensuring the accuracy and relevance of information used in gage calibration and metrology.

The manufacturing sector struggles with declining workforce experience as seasoned veterans retire and new operators lack the necessary skills. To address this, integrating predictive quality technologies and AI-driven recommendations can empower less experienced workers to achieve the quality and performance levels needed.