In a new era of industrial revolution, intelligence is key. Knowing how product design can affect manufacturability or how production processes can affect finished quality helps manufacturers make ...

In this contributed article, Gregory Miller, a writer with DO Supply, explores the ways in which machine learning is being applied in the modern industrial world, focusing on manufacturing. To date, ...

The development of next-generation metallic materials is entering a transformative era driven by data-driven methodologies. Traditional trial-and-error ...

Machine learning (ML) and computer vision (CV) technologies are vital branches of artificial intelligence (AI) that help automate tasks and increase efficiency across industries. Experts predict that ...

Researchers at Korea University have developed a machine learning model for predicting sheet resistance in phosphorus oxychloride (POCl3) doping processes in solar cell manufacturing. “Our study aims ...

Learn how APT has evolved over seven decades to now a fully-automated AI-assisted manufacturing process, without learning coding.

Since 2000, semiconductor manufacturing has increasingly depended on advanced computational techniques, notably first principles calculations and machine learning, with quantum computing anticipated ...

A case study in aerospace manufacturing provides an overview of how physics-informed digital twin systems transform robotics processes—from adaptive process planning and real-time process monitoring ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Efficiency is the key to staying competitive in our fast-paced manufacturing landscape. One of the most significant obstacles standing in the way of said efficiency is repetitive tasks. In several ...