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GE creates partnership to build industrial internet

Cliff Saran

GE has built an industrial internet platform using Amazon Web Services (AWS) to process real-time data from machines.

Jeff Immelt, chairman and CEO of GE, said: "Productivity drives economic growth. The rate of innovation in Europe and the US has declined. We believe companies like GE can run faster and leaner with IT. Small changes drive big outcomes."

During an event at Battersea Power Station, he said a combination of material science and analytics can improve productivity

GE has 9,000 software engineers working on smart machines and analytics, but Immelt has no plans to develop a software business. 

"I don't see GE becoming a software company, but software is part of our service business. Our goal is to drive more technology, using partners through an extended enterprise approach. Every industrial company will creep into analytics, because that will be the only way to be successful," he said.

Big things expected of big data

Bill Ruh, vice-president of GE's global software centre (pictured), said: "The ability to quickly analyse, understand and put machine-based data to work in real time points us to a society that benefits from the promise of big data."

The company has developed a system and a service using Hadoop-based software for high-volume machine data management.

The platform will be used for predictive maintenance on jet engines and healthcare systems. 

The industrial internet is being used in jet engines, where GE can predict wear and tear on a jet engine turbine blade depending on what flight routes it is used on. In the UK, a GE CT analytics service called DoseWatch is being used by the NHS.

Commenting on the industrial internet, Phil Jones, CEO Northern PowerGrid, which runs one of the largest smart grid projects in the UK, said: "Nobody really knows when electricity is used in a house. We could develop a genome-like [electricity] demand profile for every house. Users could be active in helping to reduce [electricity] network capacity."

Companies like GE can run faster and leaner with IT. Small changes drive big outcomes

Jeff Immelt, GE

Strategic partnerships to build business intelligence

Built in partnership with Accenture and Pivotal, GE claimed the system is the first big data and analytics platform robust enough to manage the data produced by large-scale, industrial machines in the cloud. 

The analytics will be available to GE's customers through a new service, GE Predictivity, to enable airlines, railway operators, hospitals and utilities to manage GE-based machines.

The relationship with Accenture extends GE's existing Taleris partnership, which provides airlines and cargo carriers with business intelligence for operations.

Accenture will now work with GE on developing and marketing new technology services and applications for monitoring the performance of machines.

Marty Cole, group chief executive of technology at Accenture, said: "Our expanded alliance with GE means we can bring big data and analytics capabilities to improve the business operations of a wide range of companies and industries."

Amazon Web Services has also signed a strategic partnership with GE. AWS will be the first cloud provider on which GE will deploy its industrial internet platform. GE will leverage AWS's powerful, scalable, low-cost platform to offer GE’s customers cloud solutions for industrial applications and infrastructure.

"GE's domain knowledge and R&D capabilities, combined with the strength of AWS's global infrastructure, breadth of services and big data expertise, will help enable customers to solve problems in ways we haven't even imagined yet," said Werner Vogels, Amazon.com's chief technology officer.

The system uses a common architecture, combining intelligent machines, sensors and analytics to feed data into Proficy Historian HD, a Hadoop-based historian data management product. 

Historian delivers real-time data management, analytics and machine-to-operations connectivity in a secure, closed-loop architecture so critical global industries can move from a reactive to a predictive industrial operating model.


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