The power of predictive
IoT sensors on your asset produce data about factors such as pressure, vibration or viscosity. Artificial intelligence (AI) and machine learning monitor the data and trigger warnings when human intervention may be required. Using certain thresholds that you define, you can give yourself a cushion on maintenance depending on the risk level of failure and what the impact of that failure would be — whether it’s unplanned downtime at the more minor end of the spectrum or catastrophic damage on the other. The setup creates an automated way to schedule inspections and replacements, reducing or preventing asset failure while boosting equipment uptime.
IDC Manufacturing research shows that predictive maintenance plans can cut expenses up to 20% while boosting asset availability by 20%. Within the oil and gas industry, which is heavily reliant on expensive assets, IoT-enabled maintenance cut costs by 30% and equipment downtime by 45% and helped raise production output by 25%, the U.S. Department of Energy says.
“Predictive maintenance offers a 21st-century solution to a timeless concern among executives: how to get more from assets by reducing downtime and extending life cycles,” says Jim Perrine, Principal, Americas Enterprise Asset Management Leader, Ernst & Young LLP.
Aside from costing money and causing downtime, unneeded maintenance can backfire and deliver the opposite of what’s intended, reducing the life of your asset. Maintenance technicians cannot take apart an asset and put it back together as well as it was originally manufactured: every time they do so, a new failure point is potentially introduced.
Consider your home’s heating, ventilation and air conditioning system. Perhaps you pay a technician to clean and inspect your compressors every year. Every time you do a pressure test, you lose refrigerant, and, over time, you’ll eventually lose enough that you’ll then have to pay for more. But, with IoT-enabled sensors, such maintenance won’t need to occur until you’re notified that the refrigerant pressure is becoming too low.
There’s also an impact on safety, since some maintenance is potentially harmful to your workforce. In the manufacturing industry, 25% to 30% of workplace deaths are related to maintenance — due to shocks, burns and injuries from moving parts, for example — according to a report from BLR. Minimizing maintenance also means you’re not exposing your workers to unneeded risk.
And when you have the data, you’re set up for even more proactive possibilities. For instance, when you develop confidence in your AI capabilities, the technology can automatically start looking for replacement parts when needed and determine the availability from vendors if you don’t have them in stock.