IOT (Internet of Things) is not only a home fridge capable of emailing a shopping list to our smart phone or directly to a local supermarket.
Our home furnace and heating system is typically serviced once a year, or every other year, right before winter. This makes it a classic example of a time-based preventative maintenance model. A common example of usage-based preventative maintenance, on the other hand, would be getting your car serviced every 10,000 miles.
In both cases, the preventative maintenance is set to a fixed schedule, regardless of the asset’s current condition or state. The value of such scheduled maintenance is probably already abundantly clear to all of you. By preempting equipment failure, scheduled maintenance protects against service downtime and reduces costs associated with breakage.
But while its value is undeniable, scheduled maintenance doesn’t come without costs. By failing to take into account a piece of equipment’s current condition, scheduled maintenance runs the risk of being either unnecessary or insufficient. Your car could be in perfect working order after its first 10,000 miles, or it might be falling apart after just 5,000. While maintenance schedules are usually carefully tuned to an asset’s life cycle, they’re far from perfect. As a result, equipment can often be subjected to too much maintenance or not enough.
A simple IoT device can now monitor essential performance metrics in real-time and send alerts the moment something starts to go wrong.
IOT in the Plant
The cost of equipment failure tends to cascade. The failure of a single piece of machinery can bring an entire assembly line to a grinding halt. And for every hour that production has stopped, hundreds of thousands of dollars might be slipping out the door. That hiccup in production can also result in unfulfilled contracts, angry customers, and upheaval in your supply chain.
Traditionally, those types of failures were prevented by routine scheduled maintenance by specialized technicians. But as discussed earlier, scheduled maintenance is imperfect. Fear of equipment failure often drives businesses to set aggressive preventative maintenance schedules, which of course raises costs.
In fact, according to a recent paper from IBM, up to 70% of a company’s investment in preventative maintenance does not affect uptime metrics. This is due largely to the fact that only 11% of machine failures follow an age-degradation pattern. A whopping 89% occur at random.
If there’s any one statistic that best highlights the inefficiency of scheduled maintenance, that’s it. Real-time condition monitoring, provided by IoT devices, will allow businesses to be much more agile in their maintenance patterns and limit inefficiencies.
“IOT TECHNOLOGY CAN IMPROVE SERVICES AND DEMAND PLANNING BY COLLECTING DATA ON WHEN MACHINES BEGIN TO BREAK.”
It’s also important to note that new IoT technologies have the added benefit of easy implementation. Legacy equipment can be easily retrofitted with connected devices, without the need to purchase or develop new machinery.