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Understanding the journey to IoT and Big Data in operations

During a session at the Siemens Automation Summit, a panel of experts discuss what’s holding back deployments and how to start the project that will make a difference.

From left to right: David Greenfield, Biplab Pal, Andrew Crowley, Jagannath Rao.
From left to right: David Greenfield, Biplab Pal, Andrew Crowley, Jagannath Rao.

When it comes to the Industrial Internet of Things and Big Data, there are currently two camps out there: The people who are 100 percent committed to adopting the technology and the people who have not bought into the idea—at all. These are two opposite ends of the spectrum, but there is room in the middle of these extremes for those manufacturers that want to dabble in the data without taking a big business risk.

That was the message from three experts on the subject who sat on a panel moderated by Automation World’s Editor-in-Chief David Greenfield at the Siemens Automation Summit this week.

The panel started by addressing the misconceptions that surround the topic, which range from data quality over quantity to overall expectations.

“There’s a big misconception that [manufacturers] will see results tomorrow,” said Jagannath Rao, senior vice president of IoT strategy for Siemens PLM Software, explaining that companies often enter into an IoT and Big Data project assuming their business will change immediately.

Overnight success drives much of the “hype” around the topic, and that is especially true when it comes to predictive maintenance, which is often considered the low-hanging fruit for IoT initiatives. To cut through the hype, Biplab Pal, co-founder and CTO at MachineSense, a supplier of predictive maintenance and analytics technology for industrial machines, said manufacturers need to rethink how they interact with the machines over the entire lifecycle.
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