The US Department of Defense (DoD) is keen on exploring the implementation of additive equipment in the battlefield and shipboard for quick-turn part fabrication.
In today’s booming software landscape, you see highly dynamic teams quickly iterating to develop and improve their products. Yet while the world’s software creators have learned to “move fast and break things,” hardware developers are still (slowly) moving to adopt a more agile product development methodology.
Industry 4.0 is inevitable, and everyone is looking to find a way forward. But manufacturing leaders who focus only on the technology involved will be frustrated—because the new industrial revolution is just as much a culture and people thing as it is a technology thing.
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.
Most manufacturers have relied on third-party vendors to make parts that are then incorporated into the final product. From automakers sourcing stereos and aircraft makers contracting for jet engines to a small bakery ordering plastic bags or a woodshop buying nails, producers of all types have supplemented their internal capabilities through a painstakingly developed supply chain of external vendors.
Just getting familiar with the digital thread? You’ve come to the right place to learn what it is and why you need it for your products.
There have been many process improvement trends in manufacturing over the decades, and none have had more significant ROI than machine monitoring. The increase in machine monitoring is owed in large part to the rise in popularity of the open and royalty-free interconnectivity standard MTConnect.
Additive will provide a simpler, more responsive supply chain for high-value parts, according to Velo3D CEO Benny Buller.
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.
Artificial intelligence will go long way to imbue data management with trust.