Smart manufacturing not just for the big players anymore July 26, 2021 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.
Much more than sheet metal February 2, 2022 TRUMPF North America is embracing 3D printing, smart manufacturing and a vibrant workforce.
Forget Your Troubles, Come on Get Happy February 20, 2018 Companies like ABB, Balluff and Sick would be within their rights to film a commercial with exuberant sensor product managers breaking out in a song of cheer.
Power of AM to approach zero inventory is growing October 17, 2017 What is good about inventory? Being able to find a part when you need it. What’s not so good about inventory? Where to even start…
Going Big on 3D Fiber Laser: A Perfect Fit for Heavy-Gauge Metal Spinner August 9, 2023 Going Big on 3D Fiber Laser: Glenn Metalcraft Boosts Efficiency and Capacity with Prima Power's Laser Next 2141
Next-Gen Continuous Fiber Tech October 2, 2023 Northrop Grumman's SCRAM system revolutionizes additive manufacturing with integrated continuous carbon fiber for aerospace and defense. It offers cost-effective build-on-demand capabilities, streamlines certification processes, and enhances agility in responding to evolving customer needs.
How Machine Learning Aids Material Selection April 8, 2024 When it comes to materials, artificial intelligence can automate the screening process, simulate the performance of different materials and identify the best option.
New Sheetmetal Software Can Improve Quoting Accuracy January 6, 2023 Some comprehensive software platforms now offer a quoting module that can help with this daunting task.
A case of the littlest bird singing the prettiest song July 14, 2020 Imagine hearing the news that manufacturers are producing a proven and safe vaccine for COVID-19 and shipping it your way. It will be music to the world’s ears.
At Forecast 3D, digital savvy brings supply chain resiliency July 29, 2021 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.
