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Visitors to the Valley of the Sun were recently treated to a dizzying display of software technology at Arizona’s Phoenix Convention Center. From June 4-7, the Siemens PLM Connection—Americas 2018 user conference hosted thousands of visitors from hundreds of manufacturing companies.

It’s the machine tool acronym you never bother to put into words: CNC. And much of the time it’s probably OK to view your “computer numerical control” as a black box doing magic. But if you’re struggling with high-speed machining, need better surface finishes or higher accuracy, have training and retention problems, or want a better handle on your production efficiency, the answer just might be the latest iterations of those three little letters.

There are plenty of manufacturing catchphrases: the Industrial Internet of Things (IIoT), Industry 4.0 and the Digital Factory. “Sometimes it’s a lot of buzzwords. Sometimes there’s a lot of reality behind it,” said Roger Hart, research and development manager of Siemens (Berlin and Munich, Germany).

Successful manufacturing companies and distributors know the importance of a good ERP system. Without it, shipments suffer and profits fall. Part of keeping the ERP wheels greased, however, is staying current on software technology, as well as networking with industry peers.

While 3D scanning has already been adopted by many automotive part manufacturers, the use cases in Quality Control (QC) have been limited.

Like most auto manufacturers, NASCAR race teams are motivated to make vehicle parts better, cheaper and faster. Hundreds of the leading Fortune 500 brands are highly visible on the evocative vehicle paint schemes, pointing to continued healthy investment in the sport.

PowerMill 2019 provides a dedicated suite of tools to program high-rate additive processes—commonly known as directed energy deposition [DED]. The DED process utilizes a CNC machine tool or industrial robot that can focus a power source—typically laser, arc or electron-beam—at a point in space.

My instincts tell me we need a sense of urgency around the use of artificial intelligence (AI) in manufacturing. The urgency is driven by how quickly technology can move today, and how an unexpected breakthrough can quickly dominate.

When wrestling with vexing issues such as product complexity, lightweighting, advanced materials and new manufacturing methods, today’s manufacturing engineers increasingly use high-fidelity simulations to visualize solutions to these challenges.

Intelligent factories have existed since manufacturing’s historical inception, but intelligence—defined as the acquisition and application of manufacturing knowledge—resided only with the factory’s staff.