Bill Holmes, facilities manager at the Corona, Calif., plant that produces the iconic Fender Stratocaster and Telecaster guitars, remembers all too well walking the factory floor with a crude handheld vibration analyzer and then plugging the device into a computer to get readings on the condition of his equipment.
While all of the woodworking was done by hand when Leo Fender founded Fender Musical Instruments Corp. 75 years ago, today the guitar necks and bodies are produced with computer-controller woodworking routers, then handed off to the craftsmen who build the final product. Holmes says he is always looking for the latest technological advances to solve problems (he uses robotics to help paint the guitars), and there’s no problem more vexing than equipment breakdowns.
Preventive maintenance, where machines get attention on a predetermined schedule, is insufficient, he says. “Ninety percent of breakdowns are instant failures that shut down processes. That’s hard on business. If you can spot a failure before it happens, you’re not shutting down production and the maintenance team isn’t running around putting out fires.”
With 1,500 pieces of equipment at the 177,000-square-foot facility, Fender is a classic candidate for putting sensors on the machinery and using AI analytics to anticipate failures. That’s exactly what Fender is doing, but with a twist – the company is using Amazon’s cloud-based Monitron service, so all of the data processing take places in Amazon’s cloud.
For smaller companies like Fender, Amazon’s fully managed service is attractive because Amazon provides the wireless sensors, which connect to Amazon’s Wi-Fi gateway over near-field communications (NFC). Amazon’s gateways are preconfigured to send relevant data to the Amazon cloud for analysis. Amazon develops the machine-learning algorithms, processes the data, and sends alerts directly to Holmes.