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June 24th, 2016

How Manufacturing Giants Are Building The Massive Industrial Internet Of Things

The biggest investment in sensors, data platforms and connected machines is coming to the industrial sector.

Selling the Internet of Things to the general public has been tough to date. Not everybody wants their appliances to talk to each other or exchange information.

On the plus side, the industrial sector is practically drooling at the possibilities that a world of connected assets and machines will open.

Over the next 10 years, investment in the Industrial Internet of Things is predicted to be hundreds of billions of dollars. Companies such as General Electric and Hitachi have already started pouring significant amounts of money into dedicated research and software platforms to make the most of the opportunities available.

And while consumers may be loath to divulge information through connected devices, the collection, analysis and understanding of machine-generated data is the key to success for the Industrial Internet of Things.

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“If we look at the next 10-15 years we anticipate an investment in harnessing all this data around the end-to-end value chain of industrial companies … across many industries,” said Hitachi Insight Group’s vice president Greg Kinsey, in a recent interview with ARC. “For example, if you look at aerospace and automotive manufacture, there is still massive potential in digitizing and integrating their end-to-end processes, from design to production to operation.”

Society Is Smarter With An Industrial Internet Of Things

According to Kinsey, the Industrial Internet of Things presents a huge opportunity to make manufacturing and distribution companies more efficient and more flexible.

The Japanese are big believers in the concept of social innovation—in other words using technology to improve society in all aspects of life. And manufacturing is a perfect place to start.

Kinsey said that Hitachi had identified three areas where the Industrial Internet of Things can help provide this social innovation within the manufacturing sector—dynamic scheduling, improving production quality and predictive asset maintenance.

“Dynamic scheduling is about reducing or eliminating the bottlenecks that occur in every manufacturing operation,” Kinsey said.

Poor scheduling flexibility can create bottlenecks which prevent a manufacturer from hitting daily, weekly or monthly targets. At the same time, poorly maintained machinery can slow production or—worst case scenario—be offline altogether, which basically means that a company either has to fix an asset or replace it.


“An industrial company is in business to make money,” Kinsey said. “If digitization can improve their customer serve levels, reduce operating costs, convert capital equipment costs into operating costs and improve the quality of their manufacturing … then that hits their bottom line directly.”

Kinsey cited an example of a factory with machines that were installed in the 1930s sitting next to machines that were only several months old. A common data lake can create a digital representation of both machines, and how they interrelate. Manufacturers  can leverage data from their existing IT systems to dovetail with a platform that have been designed specifically to connect with other data sources and real-time machine data. This aggregation of data improves transparency and enables advanced analytics and cognitive functionality.

“Any industrial company has a heterogeneous environment of devices—computers, app software, whatever,” Kinsey said. “That is the reality, which has created islands of automation over the years.”

Investing In The Assets Is A First Step

Industrial assets are General Electric’s bread and butter.

One of the pillars of GE’s reputation over the last 150 years is that the assets or machinery take priority. The company works on the basis that the asset lifecycle—from the moment you buy an asset to when you retire it—can be optimized from the start.

“There are three big things in play,” said GE Digital’s head of engineering for industrial IOT application Vish Soaji, in an interview with ARC. “Machine learning … sensors collecting data, then you combine that data with other types of data to make changes. Second is big data and third is analytics.”

As befits a company that coined phrase “industrial Internet” way back in 2012, GE has stated on numerous occasions that the industrial world is primed for digitization. As a leading manufacturer of industrial assets, there is a need to make the most of what Soaji considers as an intelligent (and available) environment.

“How do I improve the performance of my asset and how do I get more juice out of it by spending less?” Soaji said.

One way that an asset can be improved is by investing in the tools that will make it more efficient or productive. For example, GE Digital sees its Predix cloud-based platform-as-a-service as being in alignment with everything that its parent company currently does. The Wall Street Journal reported that GE will invest $1.4 billion into its software business this year, which is a significant demonstration of faith in a fledgling market.

“The most difficult part of the Internet of Things is that nobody wants to share data,” said Soaji. “GE doesn’t have to worry about that part.”


General Electric’s chief digital officer Bill Ruh told investors at an event held at GE’s San Ramon campus that the industrial Internet could be a $225 billion market within the next four years, $125 billion of which will be software applications, Investors Business Daily reported.

See also: The Industrial Internet Of Things Is About To Become A Multi-Trillion Dollar Market

GE Digital has said that by 2030 total investment in the Industrial Internet of Things will reach $60 trillion, which is not an unreasonable prediction when you consider the number of sectors that rely on big machinery to generate revenue.

“How can we take advantage of this infrastructure that we already have? Can we turn this infrastructure into some sort of mechanism for data collection and analytics?” said Soaji.

The answer to the latter question is a definitive yes.

Think about a power plant. A huge asset like a turbine in a power plant needs to run efficiently all the time, which means that the data it generates on a daily basis is extremely valuable in understanding when a problem might occur. If that asset breaks down, it creates a butterfly effect that could have been avoided if real-time analysis through connected devices was available to the asset owner.

“The center of the Industrial Internet of Things is assets – plane engines, locomotive engines, oil refineries etc.,” said Soaji. “Around these assets there are so many things that we can do to maximize the life of assets, to do predictive analytics so we can catch failure before it happens. We can literally predict when the maintenance of an airplane engine is needed – whether it is a month or a week from now – and if you don’t do it what will happen.”

Planning For Potential Failure Can Increase Productivity

Hitachi’s Kinsey also agrees that the Industrial Internet of Things will reduce the potential for asset failure. And if you can predict when an asset is going to fail, then the cost of potential downtime is reduced or eliminated, he said.

“Maintenance is much more about insuring uptime, but we believe that you can predict and plan your maintenance better,” said Kinsey. “You eliminate downtime but more importantly you can reduce the cost of maintaining your equipment and reduce your spare parts inventory.”

Hitachi is investing $2.8 billion over the next three years to implement predictive solutions for their industrial customers, with Kinsey citing a 10% productivity improvement in factories that use big data and advanced analytics as part of daily operations. A 10% productivity improvement may not seem much in the grand scheme of things, but it translates into multi-million dollar savings for a mid-sized manufacturer while providing benefits that trickle down to the end user—the consumer.

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“If we look at the food industry, we have value in farm-to-fork—that entire value chain from the planting of the seed to the meal on the table,” Kinsey said. “There is a massive opportunity to make that more efficient, to improve the quality, to improve the safety and eliminate waste.”

Consumers may still not see the value in the Internet of Things, but the potential for the industrial world is huge. GE Digital and the Hitachi Insight Group are not the only players in the game, but they have set their sights on making the Industrial Internet of Things the centerpiece of the intelligent environment that people will inevitably be a part of.

“I think the timing is right,” said GE Digital’s Soaji. “Ten years from now you won’t see on- premises applications. I guarantee that. Everything will be cloud, everything will be software … that is going to happen, no matter what.”

Image: “Turbines,” by Flickr user richardghawley, Creative Commons.

*This article is amended from the original version to include additional information from Hitachi Insight Group.

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  • Krishna Adurthy

    A very nice article giving a clear idea of a Major Visualization explained in simple terms and also giving the views of Giants like GE and Hitachi makes it more Interesting how closely the Mfg Giants are in Pace with Digitization and the key benefits they are looking with this revolution.. also small correction “GE Digital’s head of engineering for industrial IOT application is Vish Saoji, it is written as Soaji..”.. Krishna Adurthy…SCM Architect @ .Heart…