Turning Foresight Into Savings

Turning Foresight Into Savings

Tesla cars are now intelligent enough to diagnose themselves, schedule maintenance, and order new parts all on their own. Drivers no longer have to worry about unexpected breakdowns on the side of the road. Their car will diagnose issues, like powertrain malfunctions, before any serious damage occurs. This is the concept of predictive maintenance. 

Tesla vehicles are constantly creating and analyzing data, enabling them to predict when performance issues will occur. This prevents unexpected setbacks and streamlines the servicing of the vehicle. Tesla is the only car that deploys this feature to benefit its customers, but many car manufacturers use predictive maintenance in the production of their vehicles. 


Audi uses predictive maintenance to reduce downtime and improve maintenance efficiency. The company has evolved past the method of scheduling routine maintenance on its manufacturing machines. The process consisted of maintenance crews walking through the factory to inspect and make adjustments on machines, without knowing which machines even needed repairs. With Audi’s new system, equipment like it’s riveting machine, automatically generates data on its usage and performance. An artificial intelligence model then predicts when the machine will require maintenance. The engineering team then gets a quick snapshot of what needs to be done and by when. They can use that information to schedule the optimal time to perform maintenance without disrupting production. 


Nissan uses predictive maintenance to automatically monitor over 9,000 assets. The assets include conveyors, pumps, motors, and robots across its manufacturing operations. Nissan was faced with an abundance of data but a very manual intensive method to analyze it. The company deployed an artificial intelligence based system to take over the manual processes. Now each asset is constantly monitored and analyzed. The ability to predict when maintenance will be needed has directly resulted in millions of dollars saved on unplanned downtime. 


Toyota uses predictive maintenance to maximize its uptime. Its past maintenance efforts consisted of the manual process of reacting to machines as they fail. Many of the machines in its manufacturing line were already collecting data. The data just wasn’t being put to use. Toyota’s predictive maintenance system now takes the data and uses artificial intelligence to predict when a machine will fail beforehand. The system has cut downtime due to maintenance issues in half since being deployed. Inspection of the machines is now automated and teams can efficiently adjust maintenance schedules to optimize uptime.

Predictive maintenance is an incredibly powerful tool for minimizing disruptions due to maintenance and automating the inspection processes. Going forward, it will be an essential way for manufacturers to cut back on their operating expenses.