Running a car company is about a lot more than just pushing cars out the door. Incredible amounts of time and effort go into things that are completely overlooked by the average enthusiast. For instance, assembly line efficiency can either make or break a car company’s profits for the year. In this case, Audi is using what it calls “predictive maintenance” to fix problems before they happen at its Neckarsulm plant.
Audi has been collecting one millions pieces of data on its machinery and equipment at the Neckarsulm plant, to analyze the need for maintenance. The idea is to identify when a certain piece of equipment will need fixing and make that fix exactly at the right time.
Take the punch rivet machine, which joins countless Audi body parts together every day. Audi is using this predictive maintenance to identify when it will need servicing and then service it before it breaks.
“The punch riveting systems drive between 600,000 and 1.2 million rivets through a plastic tube using compressed air. This technology propels the punch rivet through the tube at up to 20 meters per second. This results in traces of wear inside the tube,” said Andreas Rieker, maintenance planner at the Audi Neckarsulm site.
If you service a machine too early, you might be wasting money on the parts and labor, as you’ll be doing it too often. If you wait until a machine breaks, then that part of the assembly line has to be shut down until it’s fixed, thus causing back ups and delays in production, which costs money. So being able to identify the exact right time a machine is going to need replacing can not only save the initial money on the machine but also save invaluable time and production.
There’s also an iMaintenance app that Audi workers use at the Neckarsulm plant. So if a machine breaks and throws a code, that code is then sent to the app and the worker can identify the problem quickly and have it fixed. Much like in a car, with check-engine codes.
What’s interesting is that this same technology could be designed and used for automotive maintenance. Data could warn customers and owners of specific issues before they arise, telling them when said issues need to be addressed by. Of course, that would never happen because how would dealerships make money on repairs?
[Source: Automotive World]
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