Something similar is now happening in the world of industrial machines.
Take the example of a large manufacturer of mining equipment for oil fields. There was a time when their million dollar pumps and assorted equipment were sold as dumb machines. Not any more. Now, they come with sensors hooked onto the internet for real time monitoring of their health.
Think of it as a Fitbit for machines. A pressure anomaly or a strange vibration, for example, would signal a servicing or replacement of parts. Breakdowns can thus be prevented or at least fixed at lightning speed. This means huge savings, because a day’s downtime for oil mining equipment is a million dollars lost.
“Instead of reacting to failure, you orchestrate the entire response before failure.”
And for the original equipment manufacturers (OEMs), it opens up a new line of business. They can remain connected over the internet with all the machines they sell, monitor their performance in real time, and take remedial action in advance to cut shutdown time. With proactive services like these, they boost their LTV (lifetime value) from customers, who get continuous monitoring of their machines instead of periodic inspections.
To do this, however, the OEMs need to be able to collate the multitude of signals from their machines, analyze them, and predict problems. Here’s where an Indian IoT and M2M (machine-to-machine) data analytics startup comes in to provide the missing piece in the puzzle.
“The OEMs know the physics and heuristics of their machines, but they’re novices when it comes to data,” says Krishnan Raman, CEO and co-founder of Flutura. “So we partner with them to build data-driven models that can look at machine status, diagnose problems, and predict failures… Instead of reacting to failure, you orchestrate the entire response before failure.”
Flutura has a brainy product called Cerebra which can do this and it’s flexible enough to be adapted to a wide range of heavy industries. But it has a formidable rival.