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The bane of modern engineering is complexity. One promise of artificial intelligence and machine learning is helping engineers to use complex tools and harness vast data sets effectively.

The Measuring Division of Kaman Precision Products, Inc. announces the availability of its line of Extreme Environment high-precision displacement sensors and systems.

Simcenter Testlab enables better usage of test-based data, from design and simulation to validation and certification.

Marposs said its new Mida Hyper Probing software can achieve an 80% reduction in cycle time, ensuring fast and precise probing.

Metrology-grade laser scanners are expanding their range of applications. New users are finding the main attractions of laser scanners—speed and ease of use. What prevented more widespread use in the past were laser scanners’ perceived tradeoffs. Using one usually meant sacrificing accuracy or working with noisy data.

In 2018, CNC Software Inc., Tolland, Conn., reached several milestones: its 35th anniversary as a company, 250,000th installation, a new user website and the introduction of Mastercam 2019.

It’s a sad fact of practically all metal removal operations that, no matter how sharp the tool or free-machining the material, there are going to be burrs, hanging chads, ragged corners, and other edge quality issues that must be dealt with before calling the workpiece complete.

We all know the buzzwords circulating around digital data and the factory. You have heard them—Industry 4.0, smart factories, data analytics, and artificial intelligence (AI). The question we all have is how will this impact workers in the long term? What do these terms really mean? Nevertheless, both traditional software suppliers and makers of advanced manufacturing equipment are offering digital solutions.

Mahr Inc., a global manufacturer of precision measurement equipment, will host a grand opening of its new Midwest Regional Customer Center July 25-26.

Software AG (Frankfurt, MDAX: SOW) announced an original survey of over 125 North American manufacturers in the heavy industry and automotive sectors that revealed they are unable to scale their Industrial Internet of Things (IIoT) investments across their enterprises, and therefore are losing millions of dollars in potential profits while falling behind competitors that have invested in enabling technologies that support IIoT across the enterprise.