Big Data and the industrial internet

Bernard Marr,
Founder & CEO, Bernard Marr & Co

GE, the company that brought electric lighting and machinery into homes and businesses, has been at the forefront of innovation for over a century, and their machinery is used in the generation of a quarter of the world’s electricity supply. In this era of Big Data, GE has embarked on an ambitious plan to create what they call the “Industrial Internet”.

How GE uses Big Data in practice

Downtime of essential machinery can directly lead to loss of revenue, especially for a giant like GE. To help reduce downtime and losses, GE has installed sensors in machinery across every sector in which it operates. The data generated is analysed to provide information on how the machinery is operating and to monitor the effect of minor changes –like operating temperatures or fuel levels – on performance.

GE’s power turbines, aircraft engines and hospital scanners are allconstantly monitoring the conditions in which they operate. Each of the company’s 22,000 wind turbines is continually streaming operational data to the cloud, where GE analysts can tweak the direction and pitch of the blades to ensure as much energy is being captured as possible. Intelligent learning algorithms allow each individual turbine to adapt its behaviour to mimic other nearby turbines that are operating more efficiently.

These “Industrial Internet” capabilities have also been made available to customers who operate GE’s equipment and systems – power companies, airlines and so on – leading to potentially huge savings for those businesses. GE have indicated that their industrial customers can expect to save an average of $8 million per year from the reduction in machine downtime alone.

These “Industrial Internet” capabilities have also been made available to customers who operate GE’s equipment and systems – power companies, airlines and so on – leading to potentially huge savings for those businesses. GE have indicated that their industrial customers can expect to save an average of $8 million per year from the reduction in machine downtime alone.

The technical details

Although GE does work with external data (like meteorological, geopolitical and demographic data), they have invested heavily in the large-scale capture and analysis of internal data from their own machinery. Just one of their gas power station turbines generates around 500 gigabytes of data a day.

This data is fed into GE’s Hadoop-based Industrial Data Lake service, which GE customers can access. The service provides a range of tools to help customers interpret the data, including GE’s own Predictivity and Predix services, as well as tools developed with partners such as Pivotal and Accenture.

Ideas and insights you can steal

Interconnected technology can help drive efficiencies across all sectors and any size business. Why wait for your equipment to go wrong when that failure can be predicted and downtime kept to a minimum? Machines are capable of making such predictions far more reliably than people and at a reduced cost, so it makes perfect sense to invest in such innovation – just as GE have done.