For Dale Mickelson, Yasda product manager at Methods Machine Tools Inc. (Sudbury, MA) and author of several books on hard milling, tackling heat-resistant superalloys (HRSAs) requires the perfect combination of machine, workholding, tooling, tool paths and coolant.
Constant refinement of medical machining from tooling design to finished product requires not only the ability to handle a broad range of plastic and metal materials but also to achieve predictable results—particularly in the face of strict regulations.
Smart factory systems benefit from improved technologies, as well as proven applications.
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.
FANUC has made real one of the promises of Industry 4.0, that of predictive maintenance for factory equipment, with its Zero Down Time IoT solution. ZDT can be applied to any of FANUC’s robotic arms and their peripherals.
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.
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.
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.
As with any digital transformation process, the devil is in the details, and there are many potential pitfalls that can derail projects.
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.
