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The Copper Development Association (CDA) is eager to help shops discover and tap into the high-speed machining advantages of brass. The substantial benefits of doing so have an increasing number of shops rethinking their part materials and, when possible, converting those parts to brass.

A Michigan company that displays instructions for manual manufacturing processes on work stations via augmented reality (AR) is adding wearables to provide similar guidance.

Structured light systems measure surfaces by projecting a pattern of fringes, then using cameras and sophisticated software to convert them into point clouds of metrology data. Accuracy can reach the single-digit microns over millions of points.

With the number of offline and in-process toolsetting options on the rise, developing a way to efficiently utilize this technology can be confusing. Which presetter should we buy? What about the software that’s so often part of these systems—do we really need it?

When I graduated with an engineering degree some decades ago, I learned that the organizations I was going to work for had internal communication problems. This was especially true for those that designed and manufactured complex machinery such as engines, aircraft, or automobiles.

For CMMs, the good times continue to roll. “One of the surprising things that has happened in just the last three to four years is the sheer volume of CMMs that we are shipping,” said Angus Taylor, president of Hexagon Manufacturing Intelligence, North America (North Kingstown, RI). “The market seems to be really exploding.”

US machine shops are potentially underutilizing the machinability of brass by as much as 85 percent in their part processing operations, reports a recent study from the Copper Development Association Inc. (McLean, VA).

In the near absence of academic programs to teach undergraduate engineering students additive manufacturing, a California-based startup has stepped in to help fill the void through internships.

Beware predictions of the demise of any technology. If the early 1920s saw the dawn of the optical comparator, there has been much speculation about its sunset. That was especially true when vision systems started hitting their stride a few years ago. Many could see optical comparators were superfluous with the use of vision systems. Many thought the sunset of optical comparators was imminent. Many were wrong. Why?

Data mining and Big Data are hot topics. Your company develops process mining software; how does it differ from data mining?