When did shopping online become more like driving a 200-mile-per-hour racecar? Quite recently, thanks to something called “digital twin” technology. Now it’s going to change railroads, airlines, factories and the rest of the business world.

Winning a Formula 1 race is no longer just about building the fastest car, hiring the bravest driver and praying for luck. These days, when a McLaren team races in Monaco or Singapore, it beams data from hundreds of sensors wired in the car to Woking, England. There, analysts study that data and use complex computer models to relay optimal race strategies back to the driver.

Meanwhile, the most advanced retailers don’t just advertise based on broad demographic information such as age and income anymore. They develop psychographic models of customers. Do you read Michael Lewis books and enjoy independent films? Do you prefer cycling to golf, celebrate your wedding anniversary in May and live two hours from your parents? Sophisticated retailers pour such data into models that predict your tastes. When you shop online, they’ll carefully select ads you’ll find more seductive.

What’s the connection between racers and online shoppers? To GE Vice President of Software Research Colin Parris, it is clear. The McLaren race crew and the online retailers both harness data and use algorithms to make reasonable projections about the future, Parris explains. The concept is called digital twin. “The opportunities of the digital twin are huge,” he says.

The idea, which involves building a digital model, or twin, of every GE machine, from a jet engine to a locomotive, will grow and create new business and service models through the Industrial Internet. Parris lays out how these digital twins can then be analyzed: A jet engine that would normally be overhauled every 24 to 36 months, for example, may not require such a service until after 38 months based on data from its digital twin. It’s an approach also being embraced by the U.S. Air Force.

Parris admits he is fascinated by Google, Apple and Amazon. The three companies relentlessly gather psychographic data and use analytics to predict what customers want. Their efforts helped them generate $338 billion in combined revenues in 2014, up 10 percent from 2013. (The average annual revenue growth for S&P 500 companies is less than 3 percent.) Parris is convinced that their ability to predicting their customers’ behavior has helped this growth. He says the Industrial Internet is now at a tipping point, promising a similar opportunity for companies such as GE.

“We are doing the same thing with digital twin. We are getting all the data we can possibly get about our engines — data for every flight, of the physics of the engine blades and how the engine is operating, data about ambient temperature and dust levels — and then I can predict exactly when to bring the aircraft in for inspection,” Parris says.

Parris, who joined from IBM a year ago, has been spreading the work of the digital twin throughout GE, from health care to aerospace. In doing so, he’s demonstrating the advantage of the GE Store— the sharing of ideas and expertise between GE’s various businesses. GE is already using digital twins that can optimize and help design wind farms and power plant-scale circuit breakers. He will discuss his vision at GE’s fourth annual Minds + Machines conference about the potential of the Industrial Internet, to be held Sept. 29-Oct. 1 in San Francisco.

For Parris, the digital twin opportunities for GE start with its big machines — aircraft engines, locomotives and gas turbines. Using the digital twin approach, a GE service team will know not only when to bring an aircraft in for inspection but what parts to have on hand and how long the jet will be out of service.

Previously, maintenance was done based on averages derived from field experience. Using this new approach, a locomotive train might not undergo a replacement of its bearings if they still looked good upon inspection and the locomotive’s digital twin signaled they didn’t need replacement. Conversely, the twin might tell inspectors that the bearings in another locomotive car that endured heavier use or harsher temperatures should be replaced early to avoid failure.

It’s a win-win for GE and its customers. For customers it means less downtime for everything from ships to power plants, where the technology can optimize fuel economy and reduce unplanned downtime. For GE, says Parris, it will boost service-contract profit margins.

“The twin is a collection of algorithms and models that give us continuous insight,” Parris says. “We have the inspection data to understand damage to a machine, we have the digital and physical models that can predict the damage and we have analytics that actually work for industrial problems.”

GE’s chief executive, Jeff Immelt, has brought these capabilities together into a new unit called GE Digital, combining the firm’s IT capabilities, including software and analytics. The unit is expected to generate $6 billion in revenues this year and is forecast to become a top 10 software company by 2020, up from 15th currently.

Parris says the digital twin approach will also help GE develop new areas of business, perhaps developing software to schedule the use of hospital beds and imaging equipment such as MRIs.

GE, he says, could expand into new areas and build new revenue streams from such things as customizing optimizers and dynamic controls. For example, Parris says, GE could sell algorithms and services to other firms that need to gather and analyze large amounts of data. “Once we have built this,” Parris says, “we can take these capabilities to other industries.”

“We will be able to influence a lot more companies,” he explains, “because we will manage the system of systems.”

The industrial app economy will spur innovation by enabling a more seamless environment for people and machines to work smarter and more efficiently together.

We live in a world of apps. They have become so pervasive in our daily experience that we don’t even think about it anymore: an app wakes us in the morning, and another app reports the quality of our sleep; we use apps to move around town, book restaurants and movies, track our weight and physical activity, meet friends, stream music and keep up with the news. Life is an app.

Now machines are joining the game. The industrial world is getting online fast —and Big Data is getting really big. Machine data is growing twice as fast as other data. Jet engines generate 1 terabyte of data per flight. Gas turbines, wind turbines, railway tracks and medical devices are beginning to produce gigantic quantities of data. By 2020, there will be an estimated 50 billion “things” connected to the Internet, and an increasing share of these interconnected devices will be industrial assets.

As they get interconnected, industrial machines will do exactly as we do — they will rely on apps to do just about anything: improve their health, feed themselves better, socialize with each other. Seriously! We already have apps that allow wind turbines to talk to each other and coordinate the way they change the pitch of their blades as the wind changes to maximize the power output of the whole wind farm. Teamwork — enabled by an industrial app. We have apps that tell jet engines how to reduce their fuel consumption. Apps that constantly check the health of gas turbines and predict when a fault is likely to happen — so we can intervene with preventive maintenance. Apps that allow doctors and nurses to schedule medical procedures more efficiently and collaborate in real time on patients’ diagnoses, curing people better and faster.

This is only the beginning. The Industrial Internet now has an operating system, Predix, and a cloud infrastructure, Predix Cloud. This provides a common platform on which developers can experiment with new ways to improve the efficiency and reliability of all sorts of machines. The platform is essential to leverage the power of the “Global Brain” — the distributed and connected intelligence of millions of people around the globe. There are already close to two and a half million developers globally. That is a lot of brains at work, and that is why in the consumer world we already have apps for almost anything.

The world of consumer apps has not only transformed our lives; it has generated substantial economic value. The global app economy grew at a 27 percent rate last year and is projected to reach $143 billion by next year.

These are impressive numbers. But they will be dwarfed by the industrial app economy that is now emerging. Industrial apps will leverage a massive installed base of physical assets across sectors that act as the engines of global economic growth: energy, healthcare, transportation. Industry today accounts for about one-third of global economic output — and investment infrastructure is expected to exceed $60 trillion over the next 15 years.

Industrial apps will bring greater efficiency throughout the economy. They will allow us to produce more energy from renewable sources and use it more efficiently — spurring major changes in the energy industry. They will make healthcare better and more affordable. They will reduce delays in hospitals and airports. Combined with new production techniques, they will help develop manufacturing activities in new places, creating jobs and accelerating growth in emerging economies. Their impact on our lives will be stronger than that of consumer apps — even if it might not be as evident.

Key to the growth of the industrial app economy will be the interoperability and compatibility of apps, so that they can be adapted and “ported” across different industrial sectors. Apps that help optimize the management of a fleet of aircraft, for example, should be easily adapted to managing fleets of ships or locomotives. This will trigger a cross-fertilization of ideas and solutions that will accelerate the growth of the industrial Internet and multiply its efficiency gains.

The industrial app economy will not only have a much more powerful economic impact than the consumer app economy, it will also be different in some important respects. The scope for very simple apps will be a lot more limited in the industrial sector: apps for industrial machines will have to be robust and secure. They will be aimed at monitoring and controlling the operation of complex industrial machinery, they will need to be able to handle industrial-level quantities of data, and they will have to satisfy the highest cybersecurity standards — both to protect the data and to avoid interference with industrial plants and infrastructure.

Economic progress has always been powered by people and by machines. Now innovation is accelerating, and it is making both machines and people smarter, more efficient and more complementary than ever. Economic progress will increasingly be driven by people and machines working in symbiosis. Industrial apps will provide the interface, the common language that allows them to work together — creating more high-quality jobs and better living standards.

This piece was based on a paper, The Moment for Industry.

Marco Annunziata is the Chief Economist and Executive Director of Global Market Insight at GE.

Like an industrial cathedral, a power plant can be a placed filled with a special kind of serenity. Walk into the pump room that feeds high-pressure steam into turbines that make electricity and you can see sun dancing on aluminum ducts while the pumps hum to the tune of 800 horsepower.

But on this day, all is not as it seems. Sure, technicians move around purposefully, performing their normal tasks. Valves open in the right sequence like pipes on an organ. Even trained eyes can’t see anything amiss. But back in the control room, a warning box pops up on the plant operator’s screen.

It’s the data talking. The plant’s engineers recently installed new vibration sensors on the pumps and they just detected a slight movement that wasn’t there yesterday or the week before. The sensors streamed the data to the control room’s computer, which analyzed it and flagged an anomaly for review. Next, the software automatically took another look at data coming from a temperature sensor, confirmed the finding and reported that things had not yet gone too far out of whack for major damage to have occurred.

And just like that, unlike in the plot of a Hollywood thriller, everything got quietly resolved. The system prompted the operator to record the anomaly for the maintenance crew, who inspected the pump and saw that anchoring screws had come loose. A few turns of the wrench avoided a situation.

For now, this scenario is still largely hypothetical. But things are changing quickly. On Tuesday at its Minds + Machines conference in San Francisco, GE unveiled the first “digital power plant” – a new design that can seamlessly integrate data from assets inside the power station and make it run more efficiently.

The Digital Power Plant isn’t limited to new plants. Applications can be installed on existing units as well, bringing the power of data to power generation machines of all types.

The digital power plant will make such installations smart by connecting them to the Industrial Internet and outfitting them with sensors that can measure pressure, temperature, vibration, environmental variables and many other conditions. The system, which is built on Predix, GE’s industrial software platform, can analyze the data to optimize the plants and spot problems before they get out of hand.

Predix will also allow utilities to write their own apps to monitor and control their plants even from a smartphone.

But the Industrial Internet isn’t the only technology behind the digital power plant. The supply of electricity to homes and businesses is shifting from the old model of a single, distant plant making and transmitting power one way to consumers to a more flexible, two-way system, where roof-mounted solar panels, wind farms and batteries bring renewable but still unpredictable power to the grid.

The industry needs tools to manage this shift and data and software might just do the trick. It can tell the best time to reduce the output of a gas-fired power plant and replace it with power made by wind, which just started blowing, or the sun, which just came out.

Ganesh Bell, chief digital officer at GE Power & Water – the first digital officer in GE’s 130-year history – says that the world will need find a way to generate 50 percent more electricity in the next two decades. “This is a huge challenge and nobody no matter how large can succeed in doing it alone,” he says. “That’s why we invite customers, partners, startups and others to join us and innovate on our Predix software platform and solve it together.”

Exelon and PSEG are among the first utilities to digitize their power plants to deploy apps and to improve assets and operations.

Mike Kurzeja, senior manager for emerging technologies at Exelon, one of the largest American energy generation and distribution companies, says that in order maintain Exelon’s place in the industry and also to thrive, “we have to look to innovation for opportunities in efficiency and growth.”

“All of our decisions are based on data,” Kurzeja says. “The more data we have, the better we can predict performance, the better we can optimize our assets.”

Consumers think nothing of tapping the screen of their smartphone to instantly stream “Can’t Feel My Face” by The Weeknd, track an exercise and diet regimen, or download Candy Crush. But there’s no app store for software needed for power plants, automobile factories or other industrial environments.

For years, consumers have enjoyed a glut of cloud-hosted apps, but software for heavy industry has lagged behind other sectors in following suit. That has limited not only those who need industrial software apps, the users, but also those who write them, the engineers.

GE is now changing that landscape, says Harel Kodesh, vice president of Predix and chief technology officer of GE Digital, by opening its Industrial Internet cloud platform, Predix, to outside developers.

In recent months more than 2,000 GE software engineers have built apps on the platform, ironing out kinks in the system. GE now expects to double that number by the end of the year before opening the platform to all developers in 2016.

GE will open the world’s first industrial app store built around it’s Predix software platform. The apps will control and monitor everything from wind turbines and locomotives to agriculture.

By then, Predix is set to become the world’s first and largest marketplace for industrial applications. “This is a major shift in the industry,” Kodesh says. “This is a market that by and large has not been exposed to the same processes you have in the consumer world.”

As the number of connected machines grows, so will the torrent of data they produce. That’s a problem that Google, Apple, Facebook and other consumer companies have been trying to solve, and GE has been taking notes. “Real-time analysis of streaming data that works for social networks and media providers can work for [large machinery] sensors,” Kodesh says.

Similar to software developers competing against each other to create the best products in the consumer space, such as exercise apps and games, developers on the Predix cloud will build applications for a large range of industries such as aviation, agriculture, health care, manufacturing and transportation. They will be able to work together and compete using secure technology. Just as Apple, with its tight vetting process, has created a sort of gated community for its app developers, GE plans to do the same for the industrial software crowd.

The Predix marketplace will also give industrial developers an environment where they can reach customers more easily and seek out partnerships. “Independent software vendors can apply their technology or even compete with our GE services,” says Lothar Schubert, leader of developer relations at GE Digital. “We encourage an open market.”

Delivering apps in the Predix cloud has benefits beyond reaching more customers more easily. App developers can receive instant feedback on their products — sharply cutting the time it normally takes to develop a prototype. By being able to immediately show customers an emerging product, Predix developers already have proven to be able to deliver their first prototype in a matter of weeks or even just a few days, rather than the usual months.

“Now developers who had been trained to develop for the enterprise or consumer space … can for the first time apply those skills readily to the industrial world,” says Schubert. “Instead of working to improve the click rate for a banner ad by 1 percent, they can work to improve the energy efficiency of a gas turbine by 1 percent, driving outcomes on industrial scale, all while helping to make the world a better place to live.”

Not only will big industry be able to connect their own machines to the technology for prompt analytic results, but industrial companies will also be able to rapidly communicate with others in their community.

For example, if wind farms get connected to Predix and start making decisions based on how to best adjust their turbine blade pitches based on the weather intelligence they receive, other connected turbines can communicate in almost real-time and make changes accordingly. If all the wind farms in a region “talk” in this fashion, the end result could be higher capacity and productivity all around.

To date, developers who have worked with Predix report seeing greater reliability, lower operational costs, risk mitigation and profitable growth. The data management company Pitney Bowes, for example, says it has been rewarded for migrating to the platform early. Says Grant Miller, Pitney Bowes vice president: “GE’s core technology, coupled with our ability to collect data and drive efficiencies on the platform, will allow our clients to drive their machines faster, better, bigger and stronger.”

Instead of trying to guess the risk of cyber attacks, companies should view their industrial assets like an unlocked car — and simply focus on stopping attacks from occurring in the first place.

Part of my job is to evangelize the need for cyber security solutions to protect industrial control systems (ICS). In many instances, when I meet with executives from companies who own or operate industrial technology, they are already aware that their control systems are at risk from cyber attacks.

As it turns out, the challenge for most executives is not lack of industrial control systems cyber risk awareness, but rather how to quantify cyber risk in a way that enables investment in effective mitigation.

A recurring theme I often hear is that the challenge for operational technology (OT) security in quantifying risk, is in estimating the probability of an attack. After all, common risk assessment methodologies such as measuring an annual loss expectancy (ALE), requires us to first determine a rate of occurrence, i.e. a probability. But in many cases we are trying to measure uncertainty of unknown events. This leads me to the following questions: How can threat events be modeled in this manner when many catastrophic scenarios assume outlier occurrences? Can we even be sure that our probability assessments are correct within several orders of magnitude? For example, is it a one-in-million or one-in-a-billion chance that your industrial assets may be victims of the next targeted attack, insider threat, or accidental cyber event?

What if instead of taking a threat-centric approach to assessing risk, we instead view cyber risk from a vulnerability-centric lens? To draw an analogy, let’s take the risk of your car being burglarized while parked. A vulnerability-centric approach says to lock the doors to prevent an intrusion, and to turn on the alarm system to deter a potential break-in. The “vulnerability” itself is the unlocked door. A threat-centric view looks at the probability of theft in the local area. If one lived in a high crime area, locking the doors would be standard practice. If one lived in Mayberry with a near-zero crime rate, one might feel confident than an unlocked car would not be at risk of a burglary.

However, even in Mayberry, there may be unknown future events that are unpredictable, such as the town hosting a sporting event, carnival or festival that invites strangers to the area; or perhaps a group of tourists passing through town who may be less trustworthy than the local resident. When we drive our cars on vacation, we don’t perform a risk assessment of each new area in order to make a decision on whether to lock our doors or not. Instead, we ensure that we protect against obvious vulnerabilities, regardless of the actual risk, by simply locking the doors and turning on the alarm.

In many ways, OT environments vulnerable to cyber attacks are like unlocked cars residing in Mayberry. The assumption is that being air-gapped means the OT assets reside in a safe local area (e.g. “we are air-gapped, therefore, we have minimal risk”). But the convergence of IT into OT environments, and the prevalence of laptops and mobile devices entering the OT network (perhaps unintentionally) introduce unknown, but non-zero cyber risk. Trying to measure this unknown risk from a threat-centric perspective is very difficult. Instead, what if we simply looked at how to protect industrial assets against known vulnerabilities, regardless of the actual risk, like the unlocked car?

If we could simply block attempted attacks from occurring in the first place, we can have assurance that a cyber event in the OT environment would not disrupt our cyber-physical systems. As long as executives recognize that their industrial cyber risk is greater than zero, taking a vulnerability-centric approach to risk analysis can simplify the decision on when and how to protect industrial assets.

(Top image: Courtesy of Thinkstock)

Paul Rogers is President & CEO of Wurldtech and General Manager of GE Industrial Cyber Security.

From fathoms, sails and knots, our modern maritime language still bears the fingerprints of past ages when sea captains relied on “dipseys” to measure off the depth of water in six-foot units called fathoms, wind to move and “log lines” with knots tied at specific intervals to determine speed.

Things changed dramatically with the advent of electronic chart displays, satellite navigation, sonar and other technology, but ships can still run into waves, foul weather and congested ports that cause delays and cost money. “We’ve traveled far beyond the compass, but there’s so much father we can do,” says Andy McKeran, digital marine leader at GE Marine, the company’s maritime technology unit. “Today, we can use data to optimize the ship’s design, maintenance, journey and availability. We already do it with planes and locomotive. There’s no reason to stop at the shore.”

McKeran is talking about SeaStream Insight. GE originally developed the marine analytics system to monitor and control deep-sea energy assets like drill ships, risers and blowout preventers, where outages can add up to $700,000 per day. “What we needed was a ‘God’s view” of the entire system,” he says. “With SeaStream Insight, we can put sensors on the machines, analyze the data they produce, send the results to experts remotely and start picking off problems before they strike.”

“We were looking at what our colleagues at GE Transportation and GE Aviation were doing to make trains and planes run more efficiently and saw a lot of similarities,” says GE Marine’s Andy McKeran Image credit: Becky Remmel/Snap-Shoppe

But McKeran, who is in San Francisco this week at GE’s Minds + Machines conference, and the team didn’t stop there. “We were looking at what our colleagues at GE Transportation and GE Aviation were doing to make trains and planes run more efficiently and saw a lot of similarities.”

The systems all run on the same Predix software platform are “equipment-agnostic” – meaning that they could run on machines of different makes. The team thought that GE Marine could use the same algorithms that track rail conditions, for example, to analyze weather, waves and tides and help the captain chart the best course. “This is the benefit of the GE Store,” McKeran says. “Everything comes back to the common nucleus. We can move quickly by borrowing from each other and save time by not reinventing the wheel. Predix allows us to analyze an amount of data that is virtually limitless.”

By optimizing navigation, for example, SeaStream Insight can help shippers reduce some of their biggest costs like fuel, which can amount to 40 percent of operational expenses.

The expanded SeaStream Insight can now help navies as well as passenger and freight shipping lines, and LNG Carriers with everything from ship design to predictive maintenance and finding optimal performance. “The system can model behavior based on user and system requirements to build out the digital blueprint of the entire vessel and then predict its operational performance,” McKeran says. “We can predict a how a battleship design will behave before it hits the water. That’s something unseen in the industry.”

Most customers will be probably interested more quotidian applications, however. By optimizing navigation, for example, SeaStream Insight can help shippers reduce some of their biggest costs like fuel, which can amount to 40 percent of operational expenses. GE says that being able to remotely spot anomalies and diagnose problems, SeaStream Insight can also cut costs associated with third-party repairs by up to a quarter, or as much as $200,000 per day, by sending field-engineers where they need to be in case something breaks down.

When Christine Furstoss joined GE 26 years ago, she was a hands-on materials scientist who made new turbine parts. She remembers it as a painstaking, arduous and often frustrating process.

“Two decades ago, if I had to change a material in a power generation turbine, it could take years,” she says from GE Global Research (GRC) in Niskayuna, NY, where serves as global technology director responsible for developing a new manufacturing concept GE calls the Brilliant Factory. “We would sit down and start by looking at paper drawings, ask questions, pull out our handbook of materials and figure out what was best after lots of discussions.” (You can read a Q&A with Furstoss about the Brilliant Factory here.)

But the handbooks and drawings of old have now given way to a vision of the future in the Brilliant Factory Lab at the GRC. In a darkened room, engineers can gather to look through 3D glasses to gauge how close a digitally rendered production of a design is to its original specifications. Nearby a robot inspects an aircraft blade for any imperfections with great precision.

The lab is a prototype of the new $73-million Brilliant Factory that is coming to life in Greenville, S.C., where GE makes huge gas turbines for power plants. That facility will use new production processes like additive manufacturing and advanced materials like Ceramic Matrix Composites (CMCs).

The Greenville factory, which is set to open in November, could save $100 million over three years, compared with traditional facilities, by decreasing design expenses and savings on sourcing and manufacturing. “The speed of change that I see, to me, defines this as a revolution — it is not just one change but a culture change,” Furstoss says.

It’s not only GE who will benefit from the idea. The company announced this week at the Minds+Machines conference that it would give customers access to its Brilliant Factory software to build their own version of the Brilliant Factory. Built around Predix, GE’s digital platform for the Industrial Internet, the software will allow customers like Procter & Gamble to make things more efficiently, from design and production to service in a closed loop. It could also help them to reduce unplanned downtime by as much as 20 percent.

GE is developing the Brilliant Factory inside a dedicated lab at GE Global Research. The results have already found applications inside dozens of GE plants.

Elements if the concept already at work in Pune, India, where GE opened its first “flexible” multi-modal plant last year. Workers at the plant, which covers an area equivalent of 38 football fields, will make parts for jet engines, locomotives, wind turbines, water treatment units and also the oil and gas and agriculture industries all under one roof. “The plant will allow us to quickly adjust production as demand comes in, using the same people and space,” said  Banmali Agrawala, president of CEO of GE South Asia.

today announced the next version of its Brilliant Manufacturing Suite at its fourth annual Minds + Machines conference. Field-tested and optimized within GE’s own factories, the suite maximizes manufacturing production performance through advanced real-time analytics to enable all manufacturers to realize GE’s Brilliant Factory vision.

The shift to the Brilliant Factory is being driven by advances on three key fronts — data, connectivity and materials. Engineers and designers can use sensors to harvest huge amounts of data on factory floors, securely pool it in the cloud and analyze it by powerful software. New materials and rapid prototyping tools like 3D printing have also shortened the time needed to build prototypes of new parts and machines. “We can get parts through factories faster with higher confidence because we are always learning and these improvements lead to us being more cost effective, which boosts the bottom line,” Furstoss says.

At Minds+Machines this week, GE opened the Brilliant Factory to other companies, including Procter & Gamble.

For example, using 3D printing, tool production that once took six months now takes three weeks, and “agile,” computer-guided welding can increase productivity four fold. Globally, every single percentage point increase in factory productivity could save GE an estimated $500 million per year.

Furstoss says the Brilliant Factory is also possible because of the GE Store– the sharing of ideas and expertise between GE’s various businesses. For example,  ultrasound technology from GE Healthcare is now used in factories to inspect blades for wind turbines. “We can inspect parts as they are being made, using the same ultrasound technology we use in our medical machines,” she says.

“The speed of change that I see, to me, defines this as a revolution,” says GE’s Christine Furstoss.

The Brilliant Factory also allows teams to work better together. For example, now that parts are designed digitally, designers can share their ideas earlier with manufacturers, get feedback, and 3D print new prototypes sooner.

Furstoss says the biggest challenge her team is facing involves developing common tools — software and IT infrastructure — so designers, manufacturers and field engineers can collaborate in immersive environments over cloud-based computer platforms. She is working with other companies to develop common standards backed by the federally funded Digital Manufacturing and Design Innovation Institute.

Says Furstoss: “We want to move quickly to build something scalable.”

You may remember four-star General Keith Alexander as the first head of the United States Cyber Command. Now, in the private sector, he’s helping industrial companies protect themselves against hackers. He says that as the number of connected machines and devices grows, so will the potential lines of attack. He sees the vulnerabilities not so much on the enterprise side, but in connected industrial operations – one of fastest growing segments of the Industrial Internet. “There is no cyber legislation that allows industry and government to work together seamlessly to prevent cyber exploits and attacks,” he says. “I doesn’t exist, it needs to exist.”

This week, GE Reports caught up with him at the Minds + Machines conference in San Francisco, where some 1,300 visitors were talking about the present and the future of connected machines and the Industrial Internet. Take a look.

New machines may not have souls, but they do have lives. Tracking them is the idea behind the Industrial Digital Thread Testbed. This mouthful of a name hides a clear goal: give each machine and even individual parts a digital “birth certificate,” track them through their lifetime, and make sure that the information is properly recorded. “It will give us the digital story of a part’s life from birth to death,” says Dave Bartlett, chief technology officer of GE Aviation. “This has never existed before at this level. Previously, records were disjointed and … very hard to pull together.”

The testbed is a partnership between GE and Infosys. They’ve built it under the auspices of the Industrial Internet Consortium, a group of some 200 companies working to realize the $15 trillion promise of the Industrial Internet.

For years, the way most machines and their parts were tracked was pretty basic, even in industries as advanced as aerospace: Their surfaces were stamped with identifying information that engineers could later look up in a database. Information was often incomplete, hard to retrieve and rarely amenable to software analysis.

Just like humans, jet engines, other machines and their parts will soon have digital birth certificates.

The digital birth certificates will allow manufacturers and customers to accumulate details about the life of a machine in a database which Bartlett and his colleagues have dubbed a “digital thread.” This computer scrapbook would accumulate details about the machine’s design, supply chain, manufacturing, service and even operating conditions it endured.

The implications are huge. Bartlett says the digital thread could help engineers trace problems to their root cause when they pop up. It could lead to a particular supplier or reveal that it was made using a specific material manufactured under slightly different conditions than normal.

In the beginning, the testbed will track parts made by GE Aviation in Terre Haute, Indiana. It will also include parts repaired at the Aviation Component Service Center in Cincinnati, Ohio. The project will test how the industrial ecosystem functions, look for problem areas and suggest solutions. “We can show how we can work across the bigger ecosystem and how we can drive innovation and value together,” Bartlett says. “These testbeds facilitate that.”

The digital birth certificates will allow manufacturers and customers to accumulate details about the life of a machine and even individual parts, says GE’s Dave Bartlet.

The digital thread also ties nicely to another GE effort called the Brilliant Factory— manufacturing facilities of the very near future using data analysis, connectivity and materials to optimize everything from design to supply chain and product control.

“This opens up our Brilliant Factories for other companies to innovate with us to help us develop that concept for GE and then for the wider world,” Bartlett says. “To really pull this off, we need to accommodate a wide ecosystem … that includes all of the companies working on things related to this idea.”

The beating heart of the testbed is a piece of technology called Platform Tier. It includes GE’s cloud-based Predix industrial software platform and Infosys’s analytic engine called Infosys Information Platform (IIP). Jayraj Nair, head of the Internet of Things practice at Infosys, says the testbed will integrate and test the compatibility of Predix system with the analytic insights provided by IIP. It will also survey the capabilities of equipment and software from other firms on what is called the Edge Tier and see how they work as part of a single ecosystem.

This is important since following the digital thread is not always easy. Imagine that a sensor on a jet engine identifies premature wear on a blade. To add that information to its digital thread, it must send that data through secure protocols through a secure industrial firewall. In order to leverage such capabilities from other companies, they will have to be tested to ensure they properly integrate with Predix and IIP.

Similarly, the testbed’s Enterprise Tier will check how the system operates in coordination with computer-aided design and other commercial software. “We have to get multitudes of partners to work with us,” Nair says. “That is why we are doing this together through the IIC.”

Bartlett and Nair say that testbeds will be critical to expanding the Industrial Internet – a digital network of machines, software and cloud analytics. A recent survey of more than 400 industrial manufacturers worldwide by Infosys revealed that, while 85 percent industrial companies saw its potential, only 15 percent have implemented dedicated strategies to analyze machine data.

GE and Infosys know a thing or two about how to get going.

Scientists at GE Global Research are developing a new manufacturing idea called the Brilliant Factory. It will allow engineers and designers to optimize production by using sensors to harvest huge amounts of data on factory floors, securely pool it in the cloud and analyze it by powerful software.

New materials and rapid prototyping tools like 3D printing have also shortened the time needed to build new parts and machines. “We can get parts through factories faster with higher confidence because we are always learning and these improvements lead to us being more cost effective, which boosts the bottom line,” Christine Furstoss, GE’s global technology director responsible for developing the new manufacturing concept.

But it’s not only GE who will benefit from the idea. Last week, at the Minds + Machines conference in San Francisco, GE announced that it would give customers access to Predix, the operating system powering the company’s Brilliant Factory software. At Minds + Machines GE Reports caught up with customers familiar with it. Listen to what they have to say.

By Zack Lord

Scientists at GE Global Research spent the last four years building a more efficient wind turbine. The result rises 450-feet above the Mojave desert in California – almost half the height of the Eiffel Tower — and looks like it has a silver UFO stuck to its face. It may appear strange, but you are looking at the future of wind power. The team explains how it came about.

In 2011, Mark Little, GE’s chief technology officer and the head of the GRC, challenged principal engineer Seyed Saddoughi and his team to build a rotor that could harvest more wind. Michael Idelchik, who runs advanced technology programs at the GRC, gave them another clue: “Since we know that the inner parts of wind turbines don’t do much for energy capture, why don’t we change the design?”

The team came up with the idea of putting a hemisphere on the center part of the wind turbine to redirect the incoming wind towards the outer parts of the blades. “The biggest unknown for us was what size the dome should be,” Saddoughi says. The group decided to do some experiments. They bought on the Internet a 10-inch wind turbine and a bunch of Styrofoam balls of different sizes, then took the lot to a wind tunnel at GE’s aerodynamic lab (see above). “By cutting the Styrofoam balls in half, we created our domes of different sizes and then stuck these domes on the center of the small wind turbine and ran our experiments at different tunnel air speeds,” Saddoughi says.

The team hooked up the turbine to their instruments and measured the amount of voltage it produced. “Invariably we got a jump in voltage output with the dome placed at the center of the wind turbine; albeit the increases differed for different size domes,” Saddoughi says. The scientists reached out to a colleague who did simple computer simulations for them and confirmed that even a full-size turbine was more efficient with a nose upfront. “Of course overjoyed by the very limited experimental and computational results, we wanted to come up with a name for this design, such that it really represented the idea – and was also something that everybody would remember easily,” Saddoughi says. “The team gathered in my office again, and after an hour of playing with words the name Energy Capture Optimization by Revolutionary Onboard Turbine Reshape (ecoROTR) was created.”

Above: Saddoughi is attaching differently shaped noses and turbine blades in Stuttgart. All image credits: GE Global Research and Chris New (ecoROTR)

The team then built a 2-meter rotor model of the turbine and took it for testing to a large wind tunnel in Stuttgart, Germany. The tunnel was 6.3 meters in diameters and it allowed them to dramatically reduce the wall effects on the performance. The researchers spent couple of months working in Stuttgart. “We conducted a significant number of experiments at the Gust wind tunnel for different tunnel air velocities and wind turbine tip-speed ratios with several variations of domes,” Saddoughi says. “The wind tunnel was also operated at its maximum speed for the blades in feathered configurations at several yaw angles of the turbine to simulate gust conditions.” They ran the turbine as fast as 1,000 rpm and carried out surface dye flow visualization experiments (see below).

Above: When dye hits the fan. Saddoughi after the dye flow visualization. When they came back in the second half on 2012, they started designing the actual prototype of the dome that was 20 meters in diameter and weighed 20 tons. The size presented a new batch of challenges. “Unlike gas or steam turbines that are designed to operate under a relatively limited number of set conditions, wind turbines must operate reliably and safely under literally hundreds of conditions, many of them highly transient,” says Norman Turnquist, senior principal engineer for aero thermal and mechanical systems.

They ran more calculations to make sure that GE’s 1.7-megawatt test turbine in Tehachapi, Calif., would be able to support the dome. They looked at performance during different wind speed and directions, storms and gusts. They also designed special mounting adapters and brackets to attach the dome. “The design looked really strange, but it made a lot of sense,” says Mike Bowman, the leader of sustainable energy projects at GE Global Research. The team then assembled the dome on site. “Early on, it was decided that the prototype dome would be a geodesic construction,” Turnquist says. “The reason is simply that it was the construction method that required the least amount of unknown risk.”

For safety reasons, the workers assembled the dome about 300m from the turbine and used a giant crane to move it to the turbine base for installation. But there was a hitch. “After the adapters were mounted to the hub it was discovered that bolt circle diameter was approximately 8mm too small to fit the dome,” Turnquist says. The team had to make custom shims to make it work.

The dome went up in May on Memorial Day and the turbine is currently powering through four months of testing. “This is the pinnacle of wind power,” says Mike Bowman. “As far as I know, there’s nothing like this in the world. This could be a game changer.“

GE didn’t invent the jet engine, but it built the first one in America during World War II. It was no accident. The company had been making turbines for power plants and superchargers for propeller planes for decades. Without all that knowledge, the jet age would’ve taken longer to lift off.

The Museum of Innovation and Science in Schenectady, N.Y., not far from GE’s current global research headquarters, holds a treasure trove of GE history. Chris Hunter, the museum’s vice president for collections and exhibitions, found a comic book from 1958 that tells the whole story of how GE turbine engineers turned Sir Frank Whittle’s jet engine design into a working machine that in 1942 powered America’s first jet plane.

(The reason why GE published comics is a whole different tale. It used what was then perhaps the most viral medium to explain and demystify science, just like it uses Snapchat or Instagram today. You can read that story here.)

Jet engines today look very different from Sir Frank’s machine, but the jet engine history – shaped by both men and women– illustrates one important point:  that the synergies that exist inside the company make the whole more valuable than the sum of its parts. GE executives call this concept the GE store. Just as turbine know-how allowed the company to build the jet engine, later jet engine research funneled knowledge back to other units and led to more efficient power plants, locomotives and ships. Take a look.

All images courtesy of the Museum of Innovation and Science in Schenectady

From Thomas Edison to former President Ronald Reagan and novelist Kurt Vonnegut, GE has employed a number of luminaries over the course of its 123-year history. One famous last name that’s been missing from this list is Spielberg.

In the late 1950s, Arnold Spielberg, the father of Hollywood director Steven Spielberg, helped revolutionize computing when he designed the GE-225 mainframe computer. The machine allowed a team of Dartmouth University students and researchers to develop the BASIC programing language, an easy-to-use coding tool that quickly spread and ushered in the era of personal computers. (Young Bill Gates, Paul Allen, Steve Wozniak and Steve Jobs all used the language when they started building their digital empires.)

“I remember visiting the plant when dad was working on the GE-225,” Steven Spielberg told GE Reports. “I walked through rooms that were so bright, I recall it hurting my eyes. Dad explained how his computer was expected to perform, but the language of computer science in those days was like Greek to me. It all seemed
very exciting, but it was very much out of my reach, until the 1980s, when I realized what pioneers like my dad had created were now the things I could not live without.”

The GE-225 at a GE factory in Schenectady, N.Y.

The Dartmouth team ran BASIC, or Beginner’s All-Purpose Symbolic Instruction Code, on the GE-225 for the first time a half-century ago, on May 1, 1964.

Arnold Spielberg, who is now 98, has been fascinated with electronics from an early age. “[It] was sort of a way of life for me, because I started playing around with radios when I was about eight or nine years old,” he told Anne Frantilla, a historian from the Charles Babbage Institute at the University of Minnesota.

During World War II, he served as the communications chief of a U.S. bomb squadron in India and later started making early vacuum tube computers at RCA Corp. GE engineer Homer R. “Barney” Oldfield hired Spielberg to set up GE’s Industrial Computer Department in Phoenix, Ariz., in 1957.

The department’s name, however, was a ruse. Unlike Oldfield, Ralph Cordiner, then GE chairman and CEO, didn’t want to make business computers. “Every time a plan was sent to him that mentioned going into business computers, he would write ‘No’ across it and send it back,” Arnold Spielberg told Frantilla. Cordiner apparently believed that an industrial company should make products for industry.

Still, Oldfield forged ahead without Cordiner’s blessing. Spielberg and his colleague Charles Propster, whom he brought from RCA, designed the GE-225 in 1959. It was a 20-bit computer that filled an entire room and contained 1,000 circuit boards, 10,000 transistors and 20,000 diodes. It stored data on disks, magnetic tapes, punch cards and paper tapes. It also allowed operators sitting at up to 11 external terminals to access the memory independently. The possibility of this embryonic form of personal computing led the Dartmouth team to develop BASIC.

When Cordiner found out what the team was doing, it was too late. They already had Bank of America as a customer. “[He] came out to attend the dedication ceremonies and promptly fired Barney Oldfield right after the ceremony for violating his rules,” Arnold Spielberg told Frantilla. “He gave the company 18 months to get out of the business.”

It took longer than that. The GE-225, which cost $250,000, was a hit and the marketing team described early orders as a “landslide.” The business sold dozens of them to customers and also to other GE units “The GE-225 can add 30,000 six-digit numbers in one second and can calculate the ages of every man, woman and child in Schenectady in 5 seconds,” wrote the Schenectady Works News, a GE newspaper. One machine working at the First Union National Bank in North Carolina predicted the results of the 1964 Johnson-Goldwater presidential race within 5 percentage points, reported the GE Monogram magazine. The Cleveland Browns football team used a GE-225 to manage season ticket sales. “Who knows,” quipped the Browns’ president Art Modell in 1966, “there might come a time when computers will help call the next play.”

Arnold Spielberg left GE in 1963, the same year Dartmouth’s “BASIC team” traveled to Arizona to learn how to program the equipment. GE sold the computer division to Honeywell in 1970. The IEEE Computer Society recognized Spielberg as a computer pioneer in 2006 for “contribution to real-time data acquisition and recording that significantly contributed to the definition of modern feedback and control processes.”

GE’s current Chairman and CEO – and Dartmouth graduate – Jeff Immelt has, in a sense, finally carried out Cordiner’s vision of industrial computing. The company is now developing software and cloud analytics for the Industrial Internet, monitoring and making more efficient everything from oil rigs to power plants and jet engines.

Let’s pass legislation to modernize the U.S. aviation system by doing what our competitors have already done — separate air traffic control operations from the safety regulator.

The United States is the birthplace of modern aviation. Beginning with the early experimentation of the Wright Brothers, and followed by numerous technological advancements, we now have the busiest aviation system in the world and an industry that is vital to our economy. Aviation is responsible for 5 percent of our gross national product. Fifty million flights and 800 million passengers crisscross our nation annually, according to the Federal Aviation Administration, with the number of air travelers projected to top 1 billion in a little over a decade.

Our industry and our air traffic control (ATC) system must be prepared and enabled to handle this growth. Unfortunately, that is not the case today. The U.S. House Transportation and Infrastructure Committee, which I chair, is preparing to address this problem with legislation that will help modernize the ATC system, encourage innovation, benefit consumers and ensure our aviation system is ready for the future.

Our aviation system is safe, and that’s a testament to the hard work of many people: air traffic controllers, safety inspectors, technicians and other FAA employees, and aviation stakeholders — including our pilots and flight crews. But it is not an efficient system. It’s not even close.

Delays already cost passengers $17 billion each year, according to the FAA. Over the last 10 years, ATC delays have gotten longer at 13 of our 20 largest airports. And these delays can have a dramatic ripple effect throughout the rest of the aviation system. When LaGuardia, O’Hare or LAX has a problem, it’s not just a New York, Chicago or Los Angeles problem — it can cause delays nationwide, and even cause the whole system to grind to a halt.

Our current ATC system is woefully outdated, still primarily based on old radar technology that’s been around since the World War II era. Other modern ATC systems around the world rely on more accurate, efficient GPS technology. Cars, smartphones and other devices also use this technology — it’s time for our aviation system to catch up. If it doesn’t, we can expect growth in delays, inefficiency and their associated costs as passenger levels increase.

The Federal Aviation Administration (FAA) has been trying to modernize the ATC system for over 30 years, but without success. These efforts, which have consumed billions of taxpayer dollars and have met with repeated setbacks and cost increases, have yet to produce significant benefits for passengers and the users of the aviation system. And there’s no end in sight.

Congress has repeatedly tried to reform the FAA’s management of the modernization process, but the time for tinkering around the edges is over.

Through the legislation we are developing, we will finally do what 50 other modern nations have already successfully done over the last 20 years: separate air traffic control operations from the safety regulator. Where this has been done, safety levels have been maintained or improved. That is a critical point — splitting ATC operations from the regulatory function has not negatively impacted the safety of air travel. But there are other significant benefits to this approach as well: ATC systems have been modernized, service has been improved and costs have been generally reduced. Presidents Bush and Clinton also supported this model of air traffic control.

By establishing an independent, not-for-profit corporation to operate and modernize our ATC services — with a stable, self-sustaining, fair user fee funding structure — we can ensure modernization is no longer subject to political whims, federal bureaucracy and budget battles. Taxpayers will benefit from significantly more efficient operations in the aviation system, saving potentially billions of dollars. And we will stop throwing away billions more on delayed and failed modernization efforts.

Under this structure, successful around the world, the FAA will continue to be responsible for safety regulation, and able to focus more exclusively on this mission. After all, safety is the agency’s specialty — it’s not a technology company or set up to be an innovator.

Innovation is the domain of the private sector, and government regulations must stop unnecessarily hindering the development of technology, the competitiveness of U.S. companies and job creation.

Another important component of the legislation my committee is developing will provide reforms to the FAA’s slow, bureaucratic process for certifying new aviation technologies. This will allow manufacturers here to test products and get them to market in a more reasonable time, and foster an environment that doesn’t drive innovation to countries that impose fewer regulatory hurdles.

Through aviation legislation that includes these and other transformative reforms, we can protect the legacy of the Wright Brothers and this vital American-born industry. We can ensure that our system becomes more modern, efficient, and reliable, that passengers benefit from fewer delays and cancellations, and that the United States remains the world leader in aviation.

Rep. Bill Shuster (R-PA) is Chairman of the U.S. House Committee on Transportation and Infrastructure.

GE Capital has signed nearly $95 billion in deals to reduce its size as of the end of the third quarter, the company reported on Wednesday. The news comes less than six months after Jeff Immelt told investors that GE would become a more focused digital industrial company and sell most of its banking operations.

Immelt said in April that GE would shed $200 billion of GE Capital’s assets, but keep the financing units directly related to GE’s industrial core, including financing for healthcare, aviation and energy. Since then, GE Capital assets have attracted interest Blackstone Group, Wells Fargo, BMO, BNP/Arval and other top financial institutions.

Illustration photos: GE Capital has sold units that provided financing to the trucking, transportation and rail industries.

The $95 billion figure includes the April sale of GE Capital’s Real Estate business, the largest real estate deal since the financial crisis. Together, the transactions set a new record for M&A volume in GE history.

The company said it was on track to reach agreements to sell between $120-150 billion in assets this year and expects to “substantially complete” the exit process by the end of 2016.

GE Capital announced deals valued at more than $26 billion in ending net investment (ENI) in the third quarter, which concluded on Sept. 30. The two largest deals accounted for more that $17 billion of the total. They included Capital One’s purchase of the Healthcare Financial Services business, which is a leading provider of capital to U.S. healthcare companies, sponsors, developers and investors. In September, the Canada-based Bank of Montreal agreed to buy GE Capital Transportation Finance, which provides wholesale and commercial end-user financing to original equipment manufacturers, dealers and end users for heavy and medium-duty commercial trucks and trailers.

The third quarter total also included $6 billion in agreements to sell its Rail Services business and a joint-venture stake between Mubadala and GE Capital. The buyers for its rail business, which leases a broad range of railcars as well as locomotives to shippers and railroads across North America, were Marmon Holdings, Inc., a Berkshire Hathaway company, and First Union Rail, a Wells Fargo company. .

According to Keith Sherin, GE Capital’s chairman and CEO, “these transactions are another example of the value generated by GE Capital’s strong businesses and exceptional teams as we continue to demonstrate speed and execute on our strategy to sell most of the assets of GE Capital.”

Today, Trian Partners announced a $2.5 billion investment in GE. Read Jeff Immelt’s statement on the investment.

The investment underscores GE’s focus on improving margins and returns, reducing costs and the size of corporate, returning capital to shareholders and realigning its portfolio.

Here’s a snapshot of GE’s strategy, portfolio actions, and how the company is performing.

 Strategy – The GE Store

In reflecting on the scale and diversity of GE, Jeff Immelt wrote in his latest letter to shareowners: “We drive enterprise advantages that benefit the entire company, through what we call the ‘GE Store.’ It means that every business in GE can share and access the same technology, markets, structure and intellect. The value of the GE Store is captured by faster growth at higher margins; it makes the totality of GE more competitive than the parts. No other company has the ability to transfer intellect and technology as GE can through the Store.”

The GE Store is a key competitive advantage for GE. The company invests to build common capabilities in technology and services, to leverage its scale across businesses and regions, and to share intellect and culture.

 Portfolio actions creating a more valuable industrial company

On April 10 of this year, GE reaffirmed its focus on its industrial businesses, announcing a plan to sell off most of its GE Capital assets to achieve 90 percent of its earnings from high-return, industrial businesses technology by 2018. The move marked the continuation of GE’s strategy to transform its portfolio and return to its industrial roots. The company also announced a revised capital allocation strategy – one that will return more than $90 billion to investors by the end on 2018.

The plan is being executed quickly, with approximately $95 billion in deals announced since April 10, nearly halfway to the asset sale goal less than six months after announcing the plan.

GE also expects to complete the split-off of Synchrony Financial this year, a share exchange valued at approximately $20 billion. The move will help reduce GE’s share count and is a large part of GE’s exit from financial services.

In addition to the GE Capital exit plan and Synchrony split, GE has received regulatory approval for its largest-ever industrial acquisition, of Alstom’s power and grid businesses. Alstom will increase GE’s installed base of turbines by 50 percent, adds complementary technologies, and significantly grows GE’s global footprint.

GE also expects to close on the sale of its Appliances business, for $3.3 billion, by the end of the year. Here’s a list of other transactions’ GE has made as part of its portfolio transformation.

Performance – First Half of 2015

In July, GE reported strong second quarter earnings, increasing margins 100 bps, driving organic revenue growth of 5 percent and raised its guidance for 2015 industrial operating earnings per share. The results keep GE on track towards its investor goals.

The Future of GE – The World’s Digital Industrial Company

This week at GE’s annual Minds + Machines event, Jeff Immelt projected that revenue from GE’s software services would nearly triple, to $15 billion, by 2020. As software continues to ‘eat the world’ GE is positioned at the nexus of the industrial domain expertise and industrial software capability. This unique position will provide exceptional outcomes for the next generation of customers.

Here’s a link to Jeff’s keynote at Minds + Machines 2015.

If a good picture is worth a thousand words, then these images are visual equivalent of War and Peace. GE imaging technology – from MRI machines to high-resolution microscopes – offers incredibly detailed snapshots of the body all the way down to the cellular level.

It doesn’t benefit just patients, but also gives us a clearer picture of the past and future. With a CT scan, for example, you can discover what a 3,000-year-old mummy ate based on its bone density. Using a super resolution microscope, you can watch the HIV virus jump from cell to cell. An ultrasound machine can allow you to watch your child’s facial expressions before it’s even born. Take a look.

Top and above: These images of the skull and the vessels and arteries that supply the brain with blood were taken by the superfast Revolution CT machine. Image credit: GE Healthcare

Doctors use ultrasound technology to study organs and functions of the fetus like the structure of the brain and the working of the heart. GIF credit: GE Healthcare

Doctors call the super-resolution DeltaVision OMX microscope “OMG” because the images it can take. Above an image of a dividing cell. Image credit: Jane Stout, Indiana University

A new software for ultrasound scanning called cSound allows doctors to observe the heart in 3D. “It’s like opening the chest and seeing the heart beating,” says cardiologist Bijoy Khandheria.

GE has been making X-ray tubes for more than a century. Scientists used them to study mummies at the 1939 World’s Fair in New York. Image credit: New York Public Library

Cytell is an intuitive and relatively inexpensive imaging system that fits on a lab bench and allows researchers to quickly analyze and visualize routine samples, from insect limbs down to cells. Above is an image of lingual papillae, the hair-like structures located on the top of the tongue. Image credit: Gary Sarkis, GE Healthcare Life Sciences

Last year, GE Healthcare celebrated the International Day of Radiology by scanning 100 everyday objects. Here’s an MRI image of cauliflower. Image credit: GE Healthcare

Map out one million flight plans each year for Southwest Airlines. Everything from planeloads of chilly Chicagoans heading for vacations in Cancun to budget-minded businesspeople dashing from Los Angeles to New York. It’s difficult. Now try toting up the countless variables on each one of those flights, such as the air’s humidity and the fuel load on each leg, in hopes of accurately calculating their impact on the bottom line.

It’s a task that was once impossible. But now, thanks to the Industrial Internet – a digital network that connects machines like jet engines to software and the data cloud – and a slew of new GE technologies, that’s changing.

Seeking new insight into what’s happening during every flight, Southwest just became the first U.S. domestics airline to use a big data system developed by GE’s Flight Efficiency Services (FES) unit. The system runs on the secure Industrial Internet, using cloud computing and cutting-edge software and analytics. Southwest, which manages a fleet of nearly 700 Boeing 737s, can use its flight analytics to drill down to each individual plane and flight to discover how decisions on each flight may have altered its profitability. Australia’s Qantas also just announced it would start using the system and join existing international customers EVA Air, AirAsia, Swiss International Airlines, Zhejiang Loong Air and SpiceJet. 

“For the first time ever, the airline can look at what they planned to do and what actually happened,” says John Gough, executive engagement leader at GE Aviation Digital Solutions. “This is something that airlines have historically not been able to do because of the vast amount of data involved.” GE’s technology will gather all the data generated by Southwest’s flights, Gough says, and combine it with the airline’s operational and planning data, including details about fuel, passenger and cargo loads, information about the weather and navigational data.

In the U.S. Southwest has pursued this concept for years. GE Aviation’s Digital Solutions business already provides the company with Flight Operational Quality Assurance analytics, a system that captures and analyzes the data generated by an aircraft while it flies from one point to another.

The new technology reaches much further. The tool, which is powered by Predix, GE’s cloud-based industrial software platform, starts with collecting data generated by each Southwest aircraft: wind speeds, ambient temperatures, weight of the plane, maximum thrust and so on. GE applies proprietary techniques and historic intelligence to analyze the data. The Southwest team can then pore over the resulting aircraft performance analytics to find patterns that previously might have been hard to detect. The ultimate goal: transform a torrent of raw data about individual flights into actionable insights that optimize airline operations.

Flight analytics could help Southwest decide whether it should add or subtract flights to some of its routes. But it also aims to identify smaller, subtler improvements. If data shows that planes on a particular route consistently carry too much fuel, reducing fuel loads will not only cut costs, it could allow Southwest to consider selling additional tickets to passengers or taking on more cargo. Reduced costs and increased revenue — those are the lifeblood of any airline.

“This is not just about saving costs but also potentially growing revenues,” Gough says. “Now an airline can understand the cost drivers on each phase of a flight — taxi, takeoff, climb, cruise, descent, approach, landing and taxi back to the gate. Previously they did not have insight into all that.”

For years, Gough says, airline planning was an inexact science because there were too many variables, from the altitude actually flown because of unexpected wind conditions to outside air pressure, speed and weather. Even the weight of otherwise identical aircraft can vary by as much as 2,000 pounds because of each plane’s maintenance history, Gough says. Now real-time data from hundreds of aircraft, coupled with data on everything from weather to navigation, allows airlines to plan more precisely. Gough likened it to medical imaging advances.

“Now airlines can be very surgical in nature,” Gough says. “It’s like the difference between an X-ray and an MRI. We are providing an MRI to an airline’s operations, whereas before they at best had an X-ray.”

The system will also help Southwest identify ways to save fuel. In 2014 airlines wasted $4.3 billion of fuel while planes idled on the tarmac. GE estimates that a 1 percent reduction in jet fuel use could save the global commercial aviation industry $30 billion over 15 years.

For example, an Austin-to-New York flight might plan to cruise at 33,000 feet. But because of turbulence, pilots might decide to move down to 29,000 feet. Now the system will specify how much extra fuel will be burned and what that will cost, giving the pilots more information to make a tactical decision.

With airline profit margins often at just 2 percent of operating expenses, being fuel-efficient is critical. Unlike cars, ships and other, less lofty means of transportation, planes can’t tap alternative energy sources like natural gas and electricity. Fuel amounts to more than 20 percent of the average airline’s operating expenses and is the fastest-rising cost facing airlines, up an incredible 130 percent over the past 15 years. Using GE’s FES, a pilot can make optimized decisions about flight plans and fuel load. The system can also help fine-tune internal policies, such as measuring whether pilots are following instructions to reduce gas-guzzling takeoff thrust at 1,500 feet.

Gough says using FES to manage fuel can reduce annual fuel costs by as much as 2 percent. For example, in 2014, Southwest spent $5.27 billion to buy fuel, meaning the FES system could identify potential fuel-cost savings of up to $105 million each year.

Think about all that the next time you’re stuck on the tarmac waiting for a gate.

GE held its fourth annual Minds + Machines conference in San Francisco last week. The big themes included opening Predix, the company’s software platform for the Industrial Internet, to outside developers and the launch of the world’s first digital power plant.

This year the event drew 1,300 visitors, a record. The roster of speakers included GE’s Chairman and CEO Jeff Immelt and GE Digital chief Bill Ruh as well as leading thinkers and practitioners in the field like MIT’s Andrew McAfee, NASA’s Adam Steltzner, the engineer behind the Sky Crane that helped land the rover Curiosity on Mars, futurist Mickey McManus, theoretical neuroscientist Vivienne Ming and Ed Catmull, president of Pixar Animation Studios who started out as a computer scientist. Take a look at the highlights and explore GEreports.com for more Minds + Machines content.