Moldmakers are under constant pressure to speed up the moldmaking process, improving their processes and product quality while boosting productivity.
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Q&A with Ben Mund, Senior Market Analyst, CNC Software Inc.
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It’s the machine tool acronym you never bother to put into words: CNC. And much of the time it’s probably OK to view your “computer numerical control” as a black box doing magic. But if you’re struggling with high-speed machining, need better surface finishes or higher accuracy, have training and retention problems, or want a better handle on your production efficiency, the answer just might be the latest iterations of those three little letters.
In the early days at CNC Software, we saw that our Mastercam CAD/CAM system was only part of a larger manufacturing solution and that an open architecture foundation could allow seamless data communication with complementary devices and systems across the shop floor.
For decades, plant personnel have performed insulation resistance tests with handheld megohmmeters to prevent motor failures that lead to costly unplanned shutdowns, failure-to-produce penalties and rewinding repairs. However, these tests only provide a “snapshot” of motor health. In a matter of days, motor windings and cables exposed to moisture, chemicals, contaminants or vibration can be compromised and fail at startup.
Some of the key trends in manufacturing are brought about by convergence of the design and manufacturing industries. With manufacturers under more pressure than ever to deliver better products faster and at lower cost, the need to connect and automate design and manufacturing processes to reduce iterations, errors, and delivery times is becoming critical.
Reducing the risk of automotive defects is one of the most critical issues facing manufacturers today – to protect the well-being of consumers, as well as their own reputations and financial health.
The IUPUI Mechanical Engineering Technology program concentrated on Mastercam and the online benefits of Mastercam University for its students. This approach paid big dividends on a unique Indy Car project for the Indianapolis Motor Speedway.
How do we turn all the data collected at each step of the manufacturing process into something usable?