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Machine-to-Machine Communication: A Step on the Road to IIoT

Feb. 25, 2015

Which is more efficient, a human writing down his or her productivity for the day or a machine recording that same output? Which brings your company closer to the Industrial Internet?

Imagine a human writing down or entering his productivity for a day and then imagine a machine simply recording his or her output, then communicating that to another machine? Which seems more efficient and more accurate?

Many industries today are still relying on users to enter or even write down their machine output for a day. Bill Bither, who is CEO and co-founder of an early-stage startup called MachineMetrics has been looking at a way to automate the machine shop workflow by taking humans out of the equation and using the power of the cloud to deliver key production metrics in real time.

As with many old-guard industries, the machine shop industry is one that has failed to take advantage of computers beyond standard kinds of enterprise software like ERP. They certainly haven't taken advantage of the kinds of advantages cloud and mobile can bring, and they are slow to adopt new technologies.

Bither's company recognized a need when they saw, in some instances, machine operators manually tallying their output for the day on a whiteboard. A secretary would then copy that information to a spreadsheet in the morning, providing two opportunities for human error.

Even companies that allowed direct entry into a PC, leaving it to operators left the possibility of error or deception (trying to make it look like they had more output than they really did).

Bither's company connects to the company's machines and the data is saved to the cloud where companies can see worker productivity in a dashboard in real time.  They can dig into the data and see exactly what's happening, when the machine was down, when the worker stepped away, what their peak work periods were and so forth.

It takes them from a situation of basically operating in the dark or looking backward to giving them valuable information to rate their worker's output (and how it compares to industry averages) and to better understand what types of worker behavior increases or decreases output -- all valuable information.

Machine to machine (M2M) communication greatly increases efficiency and when you combine it with modern technologies, you can begin to see real bottom line results.  It may not take advantage of the entire range of efficiencies that you can gain from the Industrial Internet of Things, but it's surely a step on the way to doing it

All of these methods take advantage of data to build a better understanding of your business, and give management better insight for more sound decision making. As you begin to bring the combination of Big Data, analytics and sensors into the business, you can begin to remove some of the human element in places where machines can make better and faster decisions, such as how to tune the machine to get the most out of it based on production requirements versus squeezing the maximum life out of it. 

Many companies are going to join the revolution in different ways, but if you understand that the IIoT and its cousins can make your companies run faster, smarter and better, you can begin to layer on these technologies over time.

But understand there is disruption happening in every industry, even the most antiquated industrial shop, and if you wait too long, your more forward-thinking competitors could leave you in the dust.

Ron Miller is a freelance technology journalist, blogger, enterprise reporter at TechCrunch and Contributing Editor at EContent Magazine. He has been writing about technology since 1988 when he began working as a technical writer. Past gigs include FierceContentManagement, CITEworld, Computerworld, TechTarget and many others. He co-founded socmedianews.com (originally socmedia101.com) in 2009 and contributes regularly to its content. You can learn more by visiting his blog, by Ron Miller at http://byronmiller.typepad.com.

Photo Credit: Official U.S. Navy Page on Flickr. Used under CC by 2.0 license.