The industry’s fastest growing firms are leveraging new artificial intelligence (AI), blockchain and Internet of Things (IoT) solutions to transform supply chains, transport and logistics. Reliance on paper forms and clashing systems are giving way to improved transparency across the value chain.
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Because its president saw opportunities to improve efficiency and an immediate need to make up for capacity lost due to impending worker retirements, Daiwa Steel Tube is set to save more than $1 million a year.
Are you ready for metamorphic manufacturing, what some call the third wave of the industry’s digitization? If not, take in Contributing Editor Karen Haywood Queen’s expertly reported story.
At a Tier 1 automotive manufacturer in Mexico, it quickly became clear that AI in the factory was a fantastic solution to help human workers achieve greater levels of success; a human plus machine scenario where AI enhances the capabilities of, rather than replaces, human workers.
This is the first in a series of articles that will cover the accelerating improvement in manufacturing technology.
In a high-mix/low-volume environment, it’s not good enough to simply be part of the pack. Today you need to be out front and pulling away, powered by the best smart tech available.
The increased use of CT scanning for metal powder bed fusion parts is usually associated with high-value parts and elevated quality requirements. There are increased requests for CT scanning on parts made of engineering-grade polymers like PEEK, PEKK or ULTEM and for fiber-reinforced composites like Nylon 12 CF.
When fully integrated with 5G and MEC, manufacturers should be able to accurately track costs using computer vision and launch immersive collaboration and training with the help of augmented reality.
It’s time to redefine AM and DfAM by what is possible from advanced LPBF systems—and to look ahead with the same determination the semiconductor industry used to better our lives.
An engine manufacturer discovers there is a way to reduce 50 billion data points to 2 billion—a reasonable number from which the foundation for machine learning can be built.