For machine shops in a competitive global marketplace, keeping spindles running and making product is the only way to stay in business. Still, adding a new piece of equipment, even with the promise of improving the efficiency of your existing ones, may be a difficult sell to management.
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.
Power management company Eaton announced a $4.9 million award from the U.S. Department of Energy (DOE) to reduce the cost and complexity of deploying direct-current (DC) fast electric vehicle charging infrastructure (EVCI).
Bosch said it is moving forward with volume production of silicon carbide chips.
Key steps are virtual twins and real relationships.
Sandvik Coromant’s Package Selector Application analyzes a 3D CAD model of a product and recommends the smallest packaging possible using an AI algorithm that calculates the product’s rotation.
