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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.

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.

Assisting Small and Medium-Sized Manufacturers with Industry 4.0/Smart Manufacturing Technology Adoption

Siemens acquisition of TimeSeries to expand Xcelerator portfolio through development of industry-specific apps built on Mendix platform, help customers speed digital transformation through increased adoption of low-code

Mark 2020 as the year the U.S. government chose to stand up a Manufacturing Innovation Institute focused solely on cybersecurity.

In today’s ultra-connected and camera-covered smart factories, the amount of visual data generated and transferred taxes even the most powerful computer and network systems.

AI’s learning ability is moving to the compute edge. And manufacturers will be a major beneficiary. I realized the usefulness of being able to run AI on small computer processing power while working with NASA in 2010.

Profound changes in the manufacturing landscape are now being driven by current health concerns and their influence on how plant and factory workers do their jobs.

AI already helps individual factories improve production, safety, efficiency and other metrics while lowering costs. Marrying AI and cloud technology can supercharge those benefits.

Designing new aerospace engines is challenging, but Rolls-Royce Germany turned to data analytics and AI to meet these challenges. The results? Reduced costs and shortened lead times.