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.

Organizations are increasingly adopting Software as a Service (SaaS) for quality management, moving away from traditional on-premises systems due to its scalability and cost-effectiveness. By 2025, SaaS is projected to power 85% of all business applications, up from 70% in 2023.

These advancements made our factories smarter by enabling systems to communicate with each other, share live data, and make decisions without human intervention. 

Ametek, Inc. announced the acquisition of Virtek Vision International, a leading provider of advanced laser-based projection and inspection systems.

INFORM has hired two senior managers to help the company with their goals.

As businesses increasingly rely on machine vision to enhance quality, improve productivity, and increase the bottom line, technology providers are relying more on industrial computing solutions that enable faster processing speeds and higher efficiency, or that support new tasks altogether. 

As consumers demand higher-quality goods at steadily increasing volumes, the chief benefits of industrial automation — speed, accuracy, and consistency—become more important to businesses worldwide with each passing day. 

In March 2023, after a GPT model passed a biology exam, Bill Gates noted on his blog that AI could save lives and address climate change. If AI can tackle such significant challenges, it can also help with issues faced by manufacturers, metrologists, and quality control professionals. This article will examine the challenges metrologists encounter and highlight potential AI-driven solutions in the metrology value chain.

Initially seen as science fiction, machine vision in manufacturing faced hesitance due to high costs and lack of awareness. However, interest has surged, shifting the focus from "Can it be done?" to "How will we do it?" This reflects significant transformative changes in the industry.