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Measurable Trends

A look at what is going on in measuring tech for powertrain and body applications.
#quality #Nissan


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With companies including Brown & Sharpe, Cognitens, DEA, Leica Geosystems (metrology products), Leica, Leitz, m&h Inprocess, Optiv, PC-DMIS, QUINDOS, ROMER, Sheffield, Technodigit, and TESA, Hexagon Metrology, Inc. (hexagonmetrology.com) has more than a handle on all things related to the science and art of measurement. And Lester Glover, vp of Account Business Development for Hexagon Metrology, who numbers auto among the industries that he is responsible for (he’s based in Nashville; he traveled there originally in the early ‘80s to get business with Nissan, which was setting up the Smyrna Assembly Plant, which went into production in June, 1983), has a solid grasp on what’s going on as regards both the array of technologies that the various Hexagon companies have on offer and what is happening within car and supplier plants as related to that tech.

Glover says that in a macro sense, when you look at auto and metrology, there are two categories: Powertrain and Body-in-White.
Powertrain is currently the domain, he says, of the traditional bridge-type coor-dinate measuring machine (CMM). Like the Brown & Shape Global Advantage or the PRISMO from Carl Zeiss Industrial Metrology, LLC (zeiss.com/imt). Machines that are generally in climatized enclosures and equipped with parts-loading systems. While there have been improvements in software, scanning speed and performance, Glover says that by and large, what has been the case continues to be the case in this space.
Looking forward, he posits that the future for powertrain measurement will be noncontact sensors . . . but sensors that will provide not only the accuracy required by powertrain manufacturing, but also increases in speed. “I’m talking about white-light, single-point, submicron accuracy,” he says, adding, “Two to three times faster than now and giving up no accuracy.”
He suggests that when this is developed it will be a “game-changer.” And while providing no details, says that they are working on this technology.
If it is the bridge for powertrain, then it is the classic horizontal-arm CMM for the body-in-white. But a key difference is that there is a highly viable option for measuring the frames, quarter panels, hoods, decklids and the like: laser-based systems. He cites the Leica Geosystems laser tracker and T-Probe device, a wireless and arm-less unit that allows a user to walk around with it and to make accurate measurements even of hard-to-reach locations. Another technology that is finding increased application is photogrammetry, which allows the creation of a full 3D map of a part or an assembly: “You can mate components before they get to a car and see any interference problems,” Glover says.
While noncontact, light-based systems have increasingly become the norm in assembly plants, Glover says that a difference that he sees transpiring is one where it goes from being process control, which is the case now, to quality assurance, too. “Today’s inline systems do a very adequate job of detecting changes to the process,” he says, “but they’re not capable of giving an absolute answer that the specification or dimension of a component is to print. So that’s what we’re focusing on for the future: the ability to provide very, very fast systems that gives you both process control and quality assurance.”
While he thinks that the configuration of the initial noncontact system for powertrain measurement is likely to be similar to that of a traditional CMM (he points out that the CMM structure has been optimized over the years, so it would be useful: “If you design a submicron sensor and carry it around on a sloppy structure, you’ve defeated the whole purpose.”), he suggests that the in-line body-in-white systems will probably utilize robots.
Once, and it wasn’t all that long ago, it seemed as if a goal in quality assurance departments was generating reams and reams (or in current parlance, “gigabytes”) of data. But Glover says that while data is still vital, the type of data that’s necessary isn’t necessarily that which comes in bulk quantities: “It’s not about cranking out a lot of data, but data that is actionable, that we can immediately take action with to improve the process.”
And improved processes result in better cars and trucks, which is the goal at the end of the line.


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