The recovery of the manufacturing sector and the emergence of the Internet of Things (IoT) and machine to machine (M2M) markets are set to collide over the new few years, bringing huge gains for the maintenance analytics field, according to a recent study.
The cost savings associated with the ability to predict equipment breakdowns before they actually happen is the driving factor. Predictive maintenance incorporates M2M data from equipment meters and sensors to determine when corrective maintenance tasks need to be performed—hopefully, ahead of a failure so equipment can be repaired before a major disruption.
As manufacturers fight to remain competitive, these cost savings are becoming increasingly important to the bottom line. ABI Research’s (News - Alert) “Predictive Maintenance Solutions and Strategies” study predicts revenue from maintenance analytics will likely reach $9.1 billion in 2014. Even more intriguing, with a 22-percent compound annual growth rate (CAGR), the market is expected to reach $24.7 billion in 2019.
“Today, predictive maintenance is one of the commercially readiest forms of M2M and IoT analytics, possibly second only to usage-based insurance,” said Aapo Markkanen, ABI Research senior analyst, in a statement. “It helps asset-intensive organizations transform their maintenance operations and eliminate waste, reducing costly downtime. Infrastructure, vehicles and industrial equipment can all benefit from it.”
The combination of efficiency and cost savings for manufacturers translates into significant market growth for the analytics market. Predictive and prescriptive maintenance account for 23 percent of this year’s IoT analytics market, but by 2019, they are estimated to represent 60 percent of revenue, according to ABI Research.
“Analytics is where much of the money in IoT will be ultimately made,” said Dan Shey, ABI Research practice director. “This means that application platforms like Axeda (News - Alert), ILS Technology, ThingWorx and Xively need to facilitate big data if they want to gain a competitive edge. Mnubo and MachineShop, two recent designed-for-analytics start-ups, will make an interesting comparison on that front. Besides the platforms, some of the IoT-savvier telcos—AT&T (News - Alert) and Telefonica, for example—could possibly leverage analytics to move up the stack.”
Edited by Rachel Ramsey