Dublin, Oct. 02, 2025 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Manufacturing Market by Processor (MPUS, GPUs, FPGA, ASICs), Software (On-premises, Cloud), Technology (Machine Learning, NLP, ...

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

As enterprises increasingly adopt autonomous systems and smart automation technologies, robotics is moving beyond traditional manufacturing to power logistics, healthcare, smart cities and advanced ...

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...

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 ...

Manufacturing’s future is inextricably linked with robotic advancement. Organizations embracing these transformative ...

Predicting exactly how and when a process tool is going to fail is a complex task, but it’s getting a tad easier with the rollout of smart sensors, standard interfaces, and advanced data analytics.

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 ...

Smart manufacturing integrates real-time data, connected machinery, intelligent decision-support systems, and cyber-secure networks to enable predictive maintenance, automated quality control, ...