The combination of metrology hardware, adaptive CAM software and connectivity to plant-wide systems is making additive hybrid machine tool applications ever more practical on the shop floor.
Artificial intelligence will go long way to imbue data management with trust.
The U.S. needs to build a national infrastructure in engineering and manufacturing R&D that parallels its scientific infrastructure. While it makes all the sense in the world, it is not happening.
Various industries are still struggling with automation despite long-standing efforts, consulting McKinsey & Co. said in a report.
I just returned from IMTS in Chicago and my first thought was, “where will I be able to rack up all those bonus steps I got last week?” On the easiest day, I walked 7.9 miles, and I topped 10 miles on two other days. It’s easy to understand why.
Being a competitive player in the aerospace and defense industry is no small feat. In an industry in which you need to be accountable for every piece of an assembly, meeting customer expectations and requirements can be daunting tasks.
Some things are a given today. One is computing is cheap and powerful, and it is getting cheaper and more powerful. Another is the dropping price of industrial sensors. Combine this with easier ways of moving around data from those sensors and you get lots of data: Terabytes of data.
A decade removed from the Great Recession, the U.S. job market is thriving. Because employers are struggling to fill empty positions, they must explore other ways to increase production needs.
Smart sensors, already an integral feature of many manufacturing plants that are integrating IT and OT, are now making their way into the supply chain where they monitor reliability and shipping conditions, improve predictive maintenance and make just-in-time delivery (the innovation from the 1980s) easier.
Several years ago, a global commercial vehicle maker asked my firm to develop a remote fleet management, health and performance portal that would open a new revenue stream.