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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.

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.

Amada America Inc., Buena Park, C.A., a supplier of precision sheet metal production equipment and related systems, has expanded its customer coverage in the Southeast with the opening of a 190,000 ft2 (17,652 m²) manufacturing facility near High Point, N.C.

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

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.

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

Engineering information is both pervasive and essential within manufacturing plants. And, it changes constantly as a result of maintenance-related adjustments, alterations in plant processes, or the swap-out of components.

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.