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How do we turn all the data collected at each step of the manufacturing process into something usable?

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.

The National Institute for Metalworking Skills (NIMS) and the Oregon Manufacturing Innovation Center – Research & Development (OMIC R&D) have united to define a set of Metrology standards and to develop a Metrology certification process.

CNC Software Inc., Tolland, Conn., the developers of Mastercam, has announced the winners of the 2018-2019 Wildest Parts Competition. The Wildest Parts Competition is held each year to encourage student interest and participation in manufacturing.

Much has changed in the world of automotive accessory designing, engineering, and manufacturing in the past few years. Sales and after sales of automotive parts have witnessed a surge in data-usage across the horizontal and vertical value chains between suppliers, business partners, internal departments, and the end-customers.

High QA, Inc., the developer of Inspection Manager Quality Management Software, has established a headquarters operation in Sevenum, Netherlands, to directly serve its customers on the European continent.

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.

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.

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.

Amid vigorous growth in their industry, product lifecycle management (PLM) software developers are exploiting the cloud and machine learning to manage data and enhance the users’ experience.