Predict breakdown and dangerous operating conditions
One of the greatest benefits of the IIoT is how it can dramatically improve operating efficiencies. If a machine goes down, for example, connected sensors can automatically pinpoint where the issue is occurring and trigger a service request. Perhaps more importantly, IIoT can also help a manufacturer predict when a machine will likely breakdown or enter a dangerous operating condition before it ever happens.
“Predictive maintenance is a big thing,” says Schmid. “This lets us limit equipment downtime and improve safety by being proactive about a fix.”
The sensors work by analyzing the sound frequencies, vibrations, and temperature of a given machine to tell if it’s working within its normal condition. This process—known as condition monitoring—is time intensive when humans do it manually. By using sensors to collect and quickly analyze data points in the cloud, prediction becomes easier.
Schmid cites a client that makes packaging materials as a great use case for the prediction capability of connected sensors. When the company outfitted its production equipment with IIoT sensors, overall equipment effectiveness (OEE) improved by 9%. The heightened OEE decreased waste for the company by predicting when machines would need to be maintained before they failed and had to be taken out of service. By decreasing machine downtime, Schmid says the company was able to take better advantage of the factory’s capacity.
“Thanks to the predictive nature of the sensors, the company avoided building another production line, which helped them save $25 million in added capital expenditures,” he says.