Marshall Aerospace and Defence Group is now using 3D printing from Stratasys to manufacture flight-ready parts for several of its military, civil and business aircraft—while producing specific ground-running equipment at a lower cost than aluminum alternatives.
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.
As additive manufacturing (AM) moves from prototypes to mass production, manufacturers are setting their sights on the holy grails—the products and processes that will be game-changers. Many game-changers are already in play.
As with any digital transformation process, the devil is in the details, and there are many potential pitfalls that can derail projects.
Aerospace machining encompasses machines small and large. These range from the Tornos SwissNano to the Makino MAG3, as Rich Sullivan put it. He is the OEM manager for Iscar Metals Inc., Arlington, Texas.
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.
The U.S. Department of Defense (DoD) is set to award $10 million in funding this year to the Digital Manufacturing and Design Innovation Institute (DMDII) here, UI Labs CEO Caralynn Nowinski Collens, said this morning. UI Labs is DMDII’s parent organization.
Swiss-style machine tools can be a good choice for making complex parts. On the downside, however, Swiss machining itself has a reputation of being complex—and, therefore, more difficult to master than standard machining.
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.
Marposs said its new Mida Hyper Probing software can achieve an 80% reduction in cycle time, ensuring fast and precise probing.