Predictive maintenance is a key industrial ‘internet of things’ use case, according to analyst
As the industrial internet of things brings automation to an array of verticals, the as-a-service model is evolving to fill an emerging market for the hardware – sensors and other devices – that make up the so-called “things” in the industrial internet of things.
This growing market is referred to by Lux Research analyst Isaac Brown, in a new report titled “Predictive Maintenance: The Art of Uptime,” as equipment-as-a-service. The paper focuses on the predictive maintenance use case, which would enable industrial equipment owners to essentially fix problems before they happen, effectively increasing uptime and decreasing operational costs.
“To fully benefit from the new technology, industrial organizations need to rapidly move away from the current practice of fixing equipment only after failure, or at pre-determined intervals,” Brown wrote. “Remote diagnostics and maintenance solutions are a key factor in enabling [original equipment manufacturers] to offer equipment-as-a-service models.”
Brown also makes the point that while implementing predictive maintenance requires significant upfront capital outlay, it does drive cost savings at scale; he gives the example of Monsanto, which he said saved $1 million by using wireless gateways and failure ratings to some 14,000 pieces of equipment.
The equipment-as-a-service model would help avoid high capital expenditures and enable industrial players to jump straight to the cost savings promised by predictive maintenance. He reports that Caterpillar, ThysenKrupp and Tennant are “experimenting with new business models that could eliminate capex.”
Brown also notes that the size of the industrial company as well as its regional location “play important roles in the adoption of predictive maintenance and connected solutions. Among industries, energy and heavy industries are much further along than others.”
