The day after Christmas last year, a massive cargo ship called the Benjamin Franklin docked in the port of LA. As wide as 14 freeway lanes, longer than three football fields and 20 stories tall, the megaship was the largest ever to land in North America.

Aboard the vessel were more than 18,000 containers carrying everything from refrigerators to girls’ shoes. Workers unloaded the goods in three and a half days—a record. But the operation was preceded by a months-long logistical exercise required to have the right equipment in place for moving the merchandise to trucks and trains for distribution to stores and warehouses. The operators felt there was room for improvement.

“That experience with the megaship tested the limits, while also revealing the power of information sharing,” says Jennifer Schopfer, executive director of customer performance analytics business at GE Transportation. “They did it by manually implementing information sharing. It made us all think: How can we do this better and faster? We started looking to digitize the process.”

A cargo ship in the Port of Los Angeles. The port will pilot GE’s Predix system to improve its operations. Top and above images credit: Getty Images

As a result, the port will start using GE software that makes different kinds of cargo shipment data visible in advance in 2017. The pilot project, called the Port Information Portal, will help the port coordinate resources more efficiently across the complex system that includes shippers, terminal operators, trucks, rail cars and other components. The partners will test the system for two to three months at a single terminal, with the possibility of expanding it across all 16 terminals in the future.

Seth Bodnar, GE Transportation’s chief digital officer, says the port resembles a giant restaurant. “In the past, we didn’t know who to serve until the customer showed up — you didn’t know what was coming off the ship until a couple of days before the ship arrived,” he says.

That may seem like enough time, but such short notice can lead to bottlenecks. The new GE software system makes data available to the ports two weeks before the ship arrives, giving everyone plenty of time to synch their assets. The system will also tell workers the cargo’s final destination so that trucks and machines can be ready to move the goods in the most efficient way possible. The payoff can be huge. Bodnar says that a 1 percent improvement in efficiency at just one port can net $60 million in savings.

“In the past, we didn’t know who to serve until the customer showed up — you didn’t know what was coming off the ship until a couple of days before the ship arrived,” says GE’s Seth Bodnar. Image credit: Getty Images

Port of LA Executive Director Gene Seroka says he worked for more than a year to bring together everyone to get the pilot off the ground. The team had to securely pool terabytes of data from several different databases. They brainstormed with GE on a dashboard to make sense of the data and deliver real-time, comprehensive insights to the right people at the right time. “To keep pace with the rapidly changing shipping landscape, operations at our ports must evolve,” Seroka says.

There are other benefits. Bodnar says that efficiency can also help reduce the port’s impact on the environment by reducing the number of idling trucks.

The partners say that if pilot is successful, it could scale to other ports across the country. As the world becomes more connected, ships are getting bigger and more complex: Between Asia and the U.S. West Coast the average container ship size has risen 14 percent in the past two years, and seaports account for roughly 90 percent of trade worldwide.

Says Schopfer: “This is the first solution of its kind. With successful completion of this pilot the possibilities are huge.”

The post Chips Ahoy: The Port Of LA Will Get A Digital Upgrade appeared first on GE Reports.

One day, when he was still barely a teenager, the film director Steven Spielberg came to visit his father, Arnold, at work. It was the late 1950s and the elder Spielberg was building computers for GE in Phoenix. His designs included a revolutionary machine that a group of computer scientists at Dartmouth College later used to write BASIC, the programming language that revolutionized personal computing. “I walked through rooms that were so bright, I recall it hurting my eyes,” Steven Spielberg told GE Reports about the factory. “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.”

Arnold Spielberg, who will be 100 in February, may have been a pioneer, but standing in that bright room in Arizona he was in the dark about many things our digital future held in store. “At the time I never envisioned anything like the internet,” he said during a recent visit at his bungalow high above Los Angeles.

Surrounded by photographs with President Barack Obama, Hollywood personalities, family and framed patent certificates — he received 12 patents in total — Arnold Spielberg talked about computers, his love for science fiction and his work on Hollywood blockbusters such as Christopher Nolan’s “Interstellar.” What follows is an edited version of our discussion.

GE Reports: When you started designing computers back in the 1950s, the technology was still very new. How did you choose that line of work?

Arnold Spielberg: I was always interested in electricity. I liked working with magnets, and I liked working with radios. I knew about Edison and Tesla, but not in detail. I got my first crystal radio set when I was 9. It’s basically a diode that can detect radio waves, and I played around with it. But I never could get it working until a radio repairman who lived next door helped me set it up.

GER: What else were you building?

AS: Once I saw an Erector Set in a hardware store. I went inside and asked the owner if I could use it to make a steam shovel and put it in the shop window so they could sell more Erector Sets. He grudgingly agreed and I sat in the back every day after school until it was finished. Later, I brought my mom over and showed her what I built. Sure enough, I got the construction set for Hanukkah. But I was also influenced by science fiction. There were twins in our neighborhood who read one of the first sci-fi magazines, called Astounding Stories of Science and Fact. They gave me one copy, and when I brought it home, I was hooked. The magazine is now called Analog Science Fiction and Fact, and I still get it.

GER: How did you end up in GE?

AS: I studied electrical engineering at the University of Cincinnati, and I got my degree in 1949. The first job I had was with RCA. I was designing electronic circuits for missile systems. When they started working on computers, I joined that group. After that, I moved to GE.

I joined GE’s computer department in Schenectady, New York, in 1955. My first job was designing circuits for the first computer process controls. The department was just starting. I stayed at the YMCA and visited my family, which was still back in New Jersey, on the weekends.

Top: Arnold Spielberg at his house in Los Angeles in 2016. Image credit: GE Reports. Above: Spielberg helped build computers that monitored steel mills, steam turbines and other technology. His GE-225 machine even correctly predicted election results. Image credit: Museum of Innovation and Science Schenectady

GER: Who were the computers for?

AS: The first ones were used for the industrial market. Our customers were paper mills and steel mills like Jones and Laughlin Steel Company in Pittsburgh, Youngstown Sheet and Tube in Ohio, and McLouth Steel in Michigan. They were the first customers ever to have a control system for a hot strip mill.

GER: What did the computers do?

AS: The first computers I built were data-acquisition systems. Their job was to monitor defects. They were a wire-programmed system, which means that they were uniquely designed to do just that job. Another computer called GE-312 monitored a turbine for Southern California Edison. We didn’t dare to control it because that required stops and starts, which could have endangered the machine’s life. The function then was just to make sure that it stayed within specified temperature ranges and that all the contacts were opened or closed as prescribed.

Students and professors at Dartmouth University used a GE-225 machine like the one pictured above to write the first version of BASIC in 1964. Image credit: Museum of Innovation and Science Schenectady

GER: Tell me about the computer Dartmouth used to write BASIC.

AS: Unlike the previous computers, the GE-225 — as it was called — was a business computer. It stored its own software, handling the input and output of data. We relocated the factory to Phoenix and sold it within GE as well as to the external market. GE used them for general business applications and some scientific work, but mostly to do business processing. I was in charge of the small-computer-systems group, whose job it was to design the circuits, design the logic, plan the system and put it all together.

Arnold Spielberg in 1961. Image credit: Museum of Innovation and Science Schenectady

GER: How small was this small computer?

AS: The computer consisted of three racks of equipment. Each rack was 2 feet wide and 7 feet tall. There was air conditioning at the bottom of each rack to cool it off because the circuits ran pretty warm. The memory could range from 8,000 to 16,000 20-bit words. It had an auxiliary memory that could go to 32,000 20-bit words. The computer interfaced with magnetic tapes, with punch cards and punch tapes, among other things.

One of our colleagues, Bill Bridge, designed a computer interface for Dartmouth that could transfer information from the computer to dumb terminals. They had no memory and no capability of doing computation. These were just input and output devices with keyboards. People could connect between 15 to 20 terminals to one computer and use that for time sharing. GE was one of the first companies to do time sharing and allow multiple terminals to talk to a computer.

Dartmouth had one of our computers, and they programmed it to develop the computer language BASIC. It allowed people to use the system to solve problems and handle data coming in out of the computer. Steve Wozniak may have used one such remote terminal to write software for Macs.

GER: Did your friends or family understand what you were doing?

AS: Back then I didn’t have that many friends who were interested in computers. It was like a big mystery to them. My son Steven came to visit once, and I showed him the factory and the engineering floor. I tried to get him interested in engineering, but his heart was in movies. At first I was disappointed, but then I saw how good he was in moviemaking.

GER: You were also involved in movies.

AS: I went to Caltech, and met with the astrophysicists Kip Thorne and Lisa Randall and several other scientists, and we sat there and brainstormed ideas about black holes for the movie “Interstellar.” It was a lot of fun because we kicked around all kinds of ideas about the size of black holes and how feasible they are and how likely there actually may be one.

GER: You didn’t turn Steven into an engineer, but he turned you into a moviemaker.

AS: It’s in the family now.

The post The First Spielberg Blockbuster: GE Computers [Video] appeared first on GE Reports.

Hackathons are like Olympic-level gymnastics competitions but for software developers. Competitors set aside their lives and work like crazy with the hopes of coming home the victor. For a team of five software engineers from data science product company Arundo Analytics, a recent Hackathon at GE’s annual Minds + Machines conference in San Francisco meant virtually nonstop coding over a 30-hour period fueled by Red Bulls and Diet Cokes. But in the end, the judges were impressed, and their app, called Power Scheduler, won the top prize.

Power Scheduler serves a simple but important function: It generates an automated schedule for power plant machines, balancing the supply between how much energy is available and how much electricity is needed. “A lot of factories have, say, a 20-year-old piece of equipment and it’s only 60 percent efficient, and it doesn’t need to be running all the time,” says team leader Jeff Jensen.

Maybe think of it as Nest for industry. Nest performs the same function with a home thermostat that learns when its users are home and creates an energy-saving schedule based on that information. Arundo’s app reads live data from a source like a solar grid and then measures that against web-connected devices or machines that need that power to run. Using machine-learning technology, it determines the best time to turn the machines on and power them down.

Competitors set aside their lives and work like crazy with the hopes of coming home the victor. Image credit: GE Digital. Top image: The hackathon took place during GE’s Minds+Machines conference in San Francisco. Getty Images

The app runs on Predix, GE’s operating system for industrial apps, which increasingly enables machines such as jet engines or locomotives to be monitored remotely or even “talk” to one another.

Jensen thinks that his team was picked out of more than 20 others in part because they built their app from scratch, which was no easy feat in itself.

The team put the basic building blocks of the app together on their laptops in a vast, white tent on the outskirts of the Minds + Machines conference on Pier 48 on San Francisco Bay. As the Tuesday night chill settled in and their fingers became too numb to type, the team piled into an Uber car and headed back to the townhouse they’d rented across town near the city’s scenic Presidio district.

At 8 p.m., they spread their equipment out in the main room, ordered some pizzas and worked flat out until 2:30 a.m. A short rest later and the team convened at 7 a.m. to finish off the app, handing it in just in time for the hackathon’s 1 p.m. deadline on Wednesday. The finished product runs on the Predix platform and uses Predix analytics to authenticate users and track live data from sensors on machines.

A panel of judges from Intel and GE, with backgrounds in everything from engineering to marketing evaluated the app and put Power Scheduler in the top three. Each finalist then pitched their app to an audience of 500 Minds + Machines attendees. When the moderator announced the team from Arundo had won, co-founder Stuart Morstead stood and cheered.

A panel of judges from Intel and GE, with backgrounds in everything from engineering to marketing evaluated the app. Image credit: GE Digital

The win is even more impressive considering that until a week before the event, the team didn’t even know how to code on Predix. Jensen says that GE’s free online training boot camp was enough to help them pull the app together. Sometime in the next few months the team will travel to Paris — a trip worth $50,000 that makes up their “best in show” prize — where they’ll work with senior Predix developers at GE Digital’s European Foundry in Paris to finesse their app. Down the line, the team plans to launch Power Scheduler on the Predix catalog.

“We believe in the open eco-system that GE is building and look forward to deploying the app in both the Predix and Arundo environments,” says Morstead.

While Arundo won the Hackathon, there were two runners-up who each went home with $25,000. The first, Azuqua, built an app called FLO Force Once, which automatically senses when machines are malfunctioning and finds and dispatches the closest maintenance technician. The other runner-up, called Ship Twin, uses Predix’s data and mapping services to monitor cargo ships and detect potential piracy threats.

The post Sticking The Landing: Behind The Winning App At GE’s Industrial Internet Hackathon appeared first on GE Reports.

Every year, GE Chairman and CEO Jeff Immelt hosts a meeting with analysts and investors to walk through the company’s strategy and financial goals for the upcoming year and review major wins from the past year. Earlier this afternoon, Immelt discussed GE’s transformation into the world’s largest digital industrial company and his plans to lead the digitization of industry and revolutionize how we make things by adopting 3D printing and other additive manufacturing technologies.

Highlighting past achievements, Immelt pointed to plans to merge GE’s Oil & Gas unit with Baker Hughes to create Baker Hughes, a GE Company. “The Baker-Hughes deal makes us one of the three big players in oil and gas,” Immelt said. “This is a good deal for investors in the right time.”

The combination will create a $32 billion fullstream oil services business — based on 2015 combined revenues — with operations in over 120 countries. He also noted that it’s been a year since GE’s acquisition of Alstom’s power and grid business — its largest single deal in history. He said that the integration of Alstom with GE’s energy businesses has already driven growth and synergies across the portfolio — on track with projections and growth targets. “Alstom and Baker Hughes are good deals and they add to the company strategically and financially,” Immelt said.

In addition to Alstom and the Baker Hughes announcement, Immelt said that GE has continued to expand its digital and additive manufacturing capabilities — the two key technologies the company is using to unlock new ways of working with customers and suppliers.

DIGITIZING INDUSTRY

In early 2016, GE opened Predix — the operating system for the Industrial Internet of Things (IIoT) — to businesses and partners to develop software solutions for their own operations and customers. Internally the platform has saved about $500 million in services and manufacturing productivity across GE, Immelt said. Companies such as Exelon, University of California San Francisco, BP and Proctor & Gamble have started using data insights from Predix apps to increase efficiency and productivity.

Overall, there are more than 20,000 developers working on Predix. For 2017, GE expects to grow the platform to 35,000 developers and continue to expand its digital capabilities. The company has acquired software companies such as Meridium, ServiceMax and Wise.io that bring together sensors, cloud-based algorithms and advanced field technology to help transform the way engineers and coders work together.

BUILDING A $1 BILLION ADDITIVE BUSINESS

Over the last few years, additive manufacturing has started changing the way we make things by bringing 3D printing from developing small-scale prototypes to industrial-strength products.  Today, GE has deployed additive technology in factories around the world to manufacture parts for jet engines from GE Aviation, GE Power turbines and GE Oil & Gas machines. At GE’s Global Research Center, GE has invested $1.5 billion to keep developing these new technologies.

Immelt said that additive manufacturing was also a perfect example of the GE Store — the practice of sharing expertise and technology across GE’s business portfolio. That’s because additive development and production centers can work on different parts for different businesses at the same site and learn from the process.

GE has launched a new GE Additive business to accelerate additive manufacturing across GE and for its customers. Earlier this week, GE announced that it recently closed deals to acquire a majority stake in Concept Laser GmbH and Arcam AB, two of the industry’s leading global additive manufacturing equipment businesses. With these two acquisitions, the company plans to grow its additive business to reach $1 billion in revenue by 2020 and become a leading supplier of additive machines, materials and software. The new business will not only serve GE’s industrial businesses — it will serve customers in other industries as well, including aerospace, tooling and automotive sectors.

Top image: The LEAP is the world’s first jet engine with 3D-printed fuel nozzles. It can be connected to the IIoT. Image credit: Adam Senatori for GE Reports. Above: The sand binder jetting machine at GE’s Center for Additive Technologies Advancement (CATA) uses a chemical binder to print casting molds from layers of fine sand, each 280 microns thick. Image credit: Chris New for GE Reports

A FOCUSED, DIGITAL INDUSTRIAL TRANSFORMATION 

GE has taken steps to sharpen its focus on its digital industrial side by continuing its sale of GE Capital assets. Since the April 2015 announcement to sell most of GE Capital, the business has repositioned itself ahead of schedule. To date, $195 billion of GE Capital asset sales have been signed, and $188 billion have been closed, Immelt said. The “new” GE Capital also achieved de-designation as a systemically important financial institution in the U.S. and plans to exit European regulation by 2017.

NEXT STEPS FOR GE

Today, Immelt reaffirmed the company’s 2016 operating framework. For 2017, GE forecasts stronger organic growth in comparison to other industrial companies, targeting 3-5 percent. The company set a goal of $1.60 to $1.70 earnings per share (EPS) for the year, with $16 billion to $20 billion of operating cash flow. GE expects to return $19 billion to $21 billion to investors through dividends and buybacks over the course of the year.

The company re-emphasized its EPS goal of $2 by 2018. As oil- and gas-related markets continue to face challenges, GE has announced new acquisitions, additional stock buybacks and a new cost-savings plan over the next two years to drive earnings growth and achieve its $2 EPS target.

Learn more about GE’s strategy for 2017.

Subscribe to GE’s investor newsletter for more GE financial news. You can watch the replay of GE’s Annual Outlook Investor Meeting here.

The post GE’s 2017 Annual Outlook: Changing The Game With A Digital Industrial Strategy appeared first on GE Reports.

There are nearly 2 billion children under the age of 15 living in the world, up from 1 billion in 1960. In fact, kids seem to be everywhere these days, but, strangely, the shockwaves of this population explosion — which shows no signs of abating — are being felt most acutely on the largely barren North Pole. “Santa is relying on the same technology just like 50 years ago, not only to make toys for twice as many kids, but also to distribute them,”said a source familiar with the matter. “Every year his stomach is tied into a knot like a pretzel. Something’s got to give.”

Or someone. Just in time for Santa’s busiest night — he currently has only 0.00004 seconds per child — GE proposed to create a digital twin for the old man, connect his toy factory and sleigh to Predix, optimize his flight path and, in general, take some of the pressure off. Predix, of course, is GE’s software gift to the industrial world. Unlike Santa, it creates magical moments for companies every day. “If Santa was using Predix, he would definitely be more efficient,” says Amy Sarosiek, spokeswoman for GE Digital.

One of Santa’s green-clad employees admitted that “the perfect toy was once simply fiction.”  But the GE pitch, which the company dispatched north over video, says elves could use Predix apps to figure out “what kids want now, and not later” and even reach for the Holy Grail of holidays: Determine which toy is best using the predictive power of analytics. Go figure!

The post Software For Santa? Using Data To Optimize The North Pole appeared first on GE Reports.

By the time you’ve gathered enough information to make a decision, the time to make that decision has already passed. This has been a periodic problem faced by managers for decades, but with the speed and volatility we face today, it’s become our default condition. How to adapt? By taking a page from nature.  In the second post of a new series on Medium, Beth Comstock, Vice Chair at GE, explores six ways companies can mimic nature so that an understanding of emerging problems and their solutions happens in real time and at market speed.

As we pass the tipping point toward a world fast enough and interconnected enough to be dominated by emergent systems, our methods of making decisions, and the tools available to help us make them, are changing.

Here are some rules of thumb and useful modes of understanding for managing ourselves and others in The Emergent Era.

1. Organize around information flows; ditch hierarchy and bureaucracy.

An adaptive business culture begins with a radically open communication system. It’s only when people have access to real-time data about what is happening and have permission to share it and act on it, that you get the speed and resiliency that characterize emergent structures. Nature is a good reminder of what the stakes are: erase the pheromone trails left by ants and the colony loses direction. Disrupt the human nervous system, and the result is confusion and paralysis.

Unlike natural systems, there is no automatic mechanism in human institutions to repair the lines of communication. That job falls to everyone who is responsible for shaping a company’s culture and core beliefs, at every level, and often at every moment of the day.

In my own work as a manager at GE, I make it a regular practice to ask my colleagues to tell me something they think I don’t want to hear, and then I take action to address it and communicate back what has changed. It’s valuable not just because of the new information I learn, but because it reinforces a culture of openness.

The opposite of openness and emergent organization is bureaucracy. The word itself is an artifact of old information technology. A bureau is a writing desk, a physical enclosure for information, fixed in one place, around which power and people tend to accumulate like fat around a cell. Bureaucracies were necessary when information was scarce. In our world where information flows everywhere, even through the objects around us, it’s a liability.

2. Empower individuals.

I mean really empower them. No matter what our official title in an organization may be, everybody needs to get over the illusion that by controlling others we can control outcomes. Because of accelerated change, we are all, by necessity, becoming collaborators rather than members of a command-and-control hierarchy. In any information-dependent network, the concentration of command in just a few nodes puts them at risk of becoming failure points.

In the Emergent Era, it’s best for organizations to mimic emergent systems in nature by distributing the decision making process as widely across the network as possible. In effect, to empower individual “cells” to relay signals and respond to their local conditions as they see fit.

For GE, it has meant a redistribution of people, specifically, putting more of them on the ground in markets around the world, wherever we do business. It’s also meant using every communications tool we have to create new nodes of intelligence, initiate new feedback loops, and officially empowering teams to make local decisions faster.

The challenge to this kind of distributed management is that it can be unsettling, especially for those who want to know all possible variables in advance. But once they’ve seen the level of responsiveness and speed that an emergent approach affords their teams, I’ve rarely seen them go back to a more bureaucratic approach.

An example of a Mandelbrot fractal, named after the mathematician Benoît Mandelbrot. Image credit: Getty Images.

3. Replace long lists of rules with a good M.O.

By m.o., I don’t just mean modus operandi, a characteristic way of doing business. I also mean “mission objective” and “mindset orientation.” A good m.o. is an intuitive habit of mind that connects the larger vision of an organization with the immediate, tactical objectives of a person or team. It is part habit and part intuition, somewhere between mission and mindset.

An m.o. can be a powerful tool for unleashing creativity within an organization, because it combines skilled perception with speed and fluidity of execution. A manager with a well-developed m.o. will have a knack for recombining the skills and assets of their organization in new ways in the same way that a jazz improviser recombines notes. Both make decisions partly according to a kind of muscle memory of the established rules and partly according to the unique possibilities and requirements of the moment.

I have made it a new practice now to manage in this way. At the outset of a project, I outline the goal at hand, offer a set of running rules and clarity about the constraints, along with an understanding that there are limits to what is knowable. Then I encourage teams to embrace the freedom and flexibility to get to the end result in their own way. The result is almost always better than I’d intended or imagined, and the working conditions are better suited to the speed and complexity of The Emergent Era.

4. Get used to living in the “in between.”

Our existing institutions and methods are being eroded by the digital information flow, while their replacements are arising quickly but not yet at sufficient scale. All our institutions, new and old, are caught in this “In Between,” and it’s there that they have to learn how to thrive.

Learning to live in the In Between is a mindset change — perhaps the defining mindset change — of The Emergent Era. It means abandoning the idea that we can operate with safety and with total knowledge, or even with the certainty that the tools we have are sufficient to address the possibilities and problems that face us.

5. Open up new feedback loops

Don’t be afraid of feedback, but make sure it’s the right feedback.

Healthy, adaptive systems tend to be highly feedback tolerant. That doesn’t mean they merely amplify the signals that flow through them. They also modify feedback and the resulting behavior based on it. In a company where the information flow is obstructed by bureaucracy, or by managers who only boost the signal of their own ideas, constructive feedback is impossible. For a system to be adaptive, it needs to create regular conditions tolerant of “negative” feedback.

In the moment, negative feedback, the kind that modifies behavior, can be uncomfortable to process. It means tolerating not just unpleasant information, but a certain amount of failure. It means going from a culture of “failure is not an option,” to one of “failure is not a problem,” as media theorist Clay Shirky puts it. Failure, when it’s the honest result of an attempt to adapt to change, is actually a symptom of organizational health. And tolerating a certain amount of it is inherent in building resilience. Feedback is what creates an organization’s “immune response” to change.

GE last year did away with annual performance reviews, opting instead for systems that allow individuals to give and receive feedback to anybody they interact with. It’s mobile and real time, allowing any employee to send to me, for example, feedback that I can use to change my behavior. Now, after any interaction, everybody has the chance to know if their intended outcome was or wasn’t successful and why. And, depending on how extensive the feedback was, directional guidance on where to begin making changes.

6. Tap into the power of minds and machines.

Simulation systems (many of which are themselves based on emergent properties) are on the verge of getting good enough to model, in real time, the way that information flows through organizations. In a world where detailed simulations can anticipate some changes in financial markets, and help predict the spread of disease, and when computer games house self-generating universes whose full detail and extent are unknown even to their creators, useful computer models of companies are a natural next step.

At GE, for example, our technologists are now building a simulation “engine,” what we call the Digital Twin, that creates a digital replica of every major technology system we make: every jet engine, locomotive, gas turbine, MRI, etc. Each Digital Twin is paired with a specific machine in the physical world. The Digital Twin of a particular jet engine, for example, would incorporate information from its design, how and where it was made, where it has operated and in what conditions. The Digital Twin is useful because it can tell you when an individual component is likely to fail or when it needs to be replaced before it actually happens, thus saving all the lost money and time that come with repairs and outages.

If this is the effect of artificial intelligence on machines, just imagine its effect on organizations: It is already possible to create Digital Twins of certain functions within organizations, thus eliminating a great deal of the grunt work, trial and error, and inefficiencies of management.

The government of Uganda is using a combination of artificial intelligence and predictive analytics to optimize the deployment of patrols that guard elephants against poachers. In the US, companies are using AI to streamline the hiring and employee review process, and advertising agencies are even using it to nudge the work of their creative towards themes that are proven to resonate with the largest population. Everywhere the pattern is the same: Repetitive work is being obviated, freeing up humans to provide the finesse, creativity, or strategic thinking needed to finish the job.

For companies and individual employees, the combination of a good m.o. and a powerful A.I. will seem at first impossible, then inevitable, and finally invincible. In the Emergent Era, companies will see solutions to their problems consistently and spontaneously emerge — before catastrophe or emergency make them necessary.

But, despite our new tools, emergent organizations will still need leaders to hire the right people, define goals, values, and beliefs, and provide and point to sources of inspiration and renewal.

Ant colonies and brain cells don’t need visionaries, but human institutions always will.

Top image: A digitally generated Mandelbrot set. These sets are vivid examples of emergence. They use simple rules to create complex and unexpected patterns. Image credit: Getty Images

This article first appeared in Medium and is the second installment in an ongoing series.

Beth Comstock is Vice Chair of GE. 

All views expressed are those of the author.

The post Beth Comstock: 6 Ways Companies Can Be Faster, Smarter And More Adaptive appeared first on GE Reports.

Virtual reality became domesticated last year — at least in America — when the VR viewer Google Cardboard arrived for the first time with the Sunday New York Times. Today, you could use it to explore Pluto’s frigid heart or climb to the top of 1 World Trade Center in downtown Manhattan.

As thrilling and immersive as these experiences are, they are just a playful precursor of what’s coming. Companies such as GE have started using VR to optimize the electric grid, service nuclear power plants and plan complex supply chains.

For example, for the past two years, GE engineers in Rugby in the U.K. have been using VR to optimize and even design factories, a task typically done with computers in two dimensions. As good as that approach is — virtually all modern factories have been designed this way — the method can make it difficult to anticipate problems that crop up once the building is in actual use in the three-dimensional world. But by then, it’s too late to fix the design without expensive retrofitting.

Above: “We’ve been looking for ways to optimize our factories and VR seemed to us like a good idea,” says GE’s Neha Prajapat, an engineering tool specialist in Rugby. She’s also a gamer. Top image: Prajapat and her team used Microsoft Kinect to study the movement of workers inside a GE factory. Images credit: GE

The GE team says VR, in combination with data coming from working factories, will help them avoid problems before they pop up. Real-world data allows the designers to see how workers move and where they gather in an existing plant and where production tends to back up. Design tweaks and more feedback then enable the team to improve new factory layouts. “We’ve been looking for ways to optimize our factories and VR seemed to us like a good idea,” says GE’s Neha Prajapat, an engineering tool specialist in Rugby who is leading the project.

Prajapat began working on factory-optimization projects in 2012 with the Manufacturing Informatics Centre led by Prof Ashutosh Tiwari at the nearby Cranfield University, a school that focuses on working with industry to develop new technologies. (Prajapat is pursuing a part-time Ph.D. there.)

Just like the New York Times, GE created VR tours of its gas turbine test stand in Greenville, South Carolina (above), and a locomotive testing facility in Pueblo, Colorado (below). Images credit: GE

Her GE team began working on VR as part of an Innovate UK funded project in 2014. They wanted to know if they could convert a standard 2-D factory model into a 3-D scale model and then tweak it for use in VR headsets or 3-D projection.

Prajapat plays video games, and so using the Microsoft Kinect gaming console to monitor movement in GE factories seemed to her like an obvious first step. The console can record objects’ positions and allows players to turn themselves into avatars inside games and perform tasks such as karate kicks and sword fighting.

The team decided to test the approach at a U.K.-based maintenance facility. They scouted 30 different locations at the plant and laser scanned them. “You could see people walking around the factory, where they were going, how long they were spending on operations, if people were crowding around one area,” Prajapat says.

So far, so good, but the following step — feeding the data into a 3-D model of the plant — was trickier. If the plant images were too high-definition, the computer would have trouble rendering them smoothly. The images shuttered and refreshed in a jerky manner. The researchers decided to strip some details from the digital record of the real world before they merged it the digital factory design.

The result is a visual experience that looks computer-generated but contains all the details of the real factory, including machines, doorways and signs. Managers can use the VR tour of the factory to analyze how shift changes work, as well as how people flow through the space, Prajapat says.

Prajapat says GE factory designers will soon be able to use information from the pilot to create plans for brand-new plants. “They will then be able to build factories that are as people-friendly and as flexible as possible,” she says.

Several projects already are underway using the technology for different GE businesses, including GE Grid Solutions, GE Aviation, and GE Oil and Gas.

The research team presented its mock-ups for the U.K.-based maintenance facility in January at the UK’s GE Energy Leadership Workshop, where it won the award for Best Showcase.

Says Prajapat: “I don’t think I’ve ever given out so many business cards at an event.”

The post Call Of Duty: This Woman’s VR Simulation Makes Factories Work Better appeared first on GE Reports.

Jeff Immelt, GE chairman and CEO, recently sat down with CNBC host Jim Cramer to talk about GE’s transformation into the world’s largest digital industrial company. Here are the highlights from the interview.

Cramer started by asking Immelt about turning GE into a “top 10 software company” by 2020. Immelt explained that jet engines, medical scanners and other industrial machines GE sells are already full of sensors that gather large amounts of data. “Seven years ago, we kind of got started as a way to protect our installed base, to grow our service business,” Immelt said. Today the company is “kind of half the way to our goal to be $15 billion [in digital orders] by 2020,” he said.

GE has 28,000 people working on digital projects, and Immelt said that orders were growing 25 percent a year. “We’re kind of first among equals in the Industrial Internet,” Immelt said. “We can play, we can do this.” He added: “Every industrial company is going to have to stake its digital claim about how you do a better job with customers, how you drive cost down, and we can lead this.”

Above: Arterys is using data generated by GE MRI scanners to see the heart in seven dimensions — three in space, one in time, and three in velocity direction. The system allows physicians to see actual blood flow in the heart as a 3D image. This picture illustrates speed and direction of blood flow with color-coded vectors. Image credit: Arterys. Top: GE wants to build a digital model, or twin, of every GE machine, from a jet engine to a locomotive, and use it to use to anticipate maintenance needs and outages, measure performance and test different operating modes. Image credit: GE Digital

Immelt told Cramer the current size of the digital market was $100 billion. “It’s a big idea,” he said, adding that software can optimize assets as diverse as jet engines, pipelines and MRI scanners. Immelt acknowledged that there will be “a ton of competitors.” But GE also has “$225 billion of contractual agreements already signed with customers that are productivity-based,” he explained. “So we have this kind of connection with customers that nobody else really has, and we can add analytics on top of that in ways that IBM and Siemens can’t do.”

For example, Immelt said, GE medical scanners generate 45 million images a day. “IBM doesn’t have that, really,” he said. “The Industrial Internet is going to break very differently than the consumer internet or the enterprise internet.”

GE’s deep industrial expertise is another advantage, Immelt said. “What’s hard in this world is knowledge of the assets,” not finding a qualified coder, he said. “What we have that the other guys don’t have is we know the material history of every jet engine, right? We can build digital twins around gas turbines. I think we bring the physics along with the analytics. We can kind of see this happening.”  GE’s operating system for the Industrial Internet, Predix, will be a key driver, he said. “We’ll get a billion dollars in Predix orders this year, so it’s real.”

When asked about GE quickly capitalizing on machine learning and artificial intelligence, Immelt pointed to another example from healthcare. He said that a radiologist uses just 10 percent of what a medical scanner can deliver on the first read. “The other 90 percent can be modeled using AI post-processing,” Immelt said. “We saw that 10 or 15 years ago. So these are concepts that are well known inside the company, and ones we think we can leverage across the installed base.”

You can watch the interview here:

The post A $100 Billion Idea: GE’s Jeff Immelt Talks To CNBC’s Jim Cramer About Industry’s Digital Transformation appeared first on GE Reports.

Home to the Valley of the Muses, Greece’s Mount Helicon has been hailed by Ovid and Hesiod as the font of inspiration and poetry. But today, the plains between Helicon’s foothills and the cool blue waters of the Gulf of Corinth are yielding a more prosaic kind of material: aluminum. Instead of verse, raw red bauxite — a mixture of aluminum oxides — flows freshly mined from the hills to a large smelter operated by Aluminium of Greece (AoG) in the town of Agios Nikolaos. On the other end, 185,000 tons of the pure silvery metal comes out every year, ready to be shipped all over the world.

The smelter’s location may be unique, but its owner, Mytilineos Group, is dealing with a global challenge affecting the entire smelting industry: The price of aluminum has dropped by almost half in the last 10 years, while the cost of production has dropped by only about 30 percent. Electricity is the biggest single contributor to cost, accounting for between 30 and 40 percent of production costs. Like other smelters, AoG found ways to become more efficient and remain profitable by putting in place successive cost-reduction programs.

“The key variables AoG is continuously looking to improve include energy use, raw-material consumption and preview of pot leakages,” says Bhanu Shekhar, chief digital officer for GE Power in the Middle East and Africa. “GE’s digital smelter solutions, data mixed with analytics, and physics can help them do just that and more.”

Top and above: AoG has three potlines consisting of 780 smelting pots running around the clock. Images credit: AoG

Current efficiency, or the relationship between the current intensity and the amount of aluminum a smelter produces, is the most important element of the smelting process. “Generally in a smelter, current efficiency runs around 93 to 94 percent, but just 1 percent increase in efficiency per year could be $2 million to $3 million in savings,” Shekhar says.

This benchmark is closely ties to “specific energy consumption”— a rate that describes how many kilowatt-hours it takes to produce a ton of aluminum. To improve it, AoG needed to find a way to optimize its smelting process.

The smelter is using a variant of the Hall-Héroult process, an industrial technique that has changed remarkably little since it was developed in 1886. AoG makes pure aluminum by first dissolving aluminum oxide, or alumina, in electrolytic cells filled with the molten aluminum compound cryolite. This bath lowers pure aluminum’s melting temperature from more than 2,000 degrees Celsius to about 940 degrees.

AoG has three potlines consisting of 780 smelting pots running around the clock. Each cell is insulated with a layer of high-silica bricks and lined with stainless steel and carbon, which serves as the cathode. There are also carbon anodes immerse in the metallic bath. When workers run a strong electric current through the bath, the reaction, called electrolysis, separates pure aluminum from the solution and pulls the metal towards the cathode on the bottom, where it can be periodically siphoned off.

These are high temperatures and extreme voltages, and slight mistakes can lead to major problems. The overheating of the pots, for example, can damage the brick lining and steel sheet and cause “pot leakage.” On the the other hand, a prolonged break in energy supply can potentially ruin the potline by “freezing” the molten bath and the aluminum.

To limit these problems and increase efficiency, AoG is deploying the world’s first digital smelter technology built on Predix, GE’s platform for the Industrial Internet. “As the largest vertically integrated bauxite, alumina and aluminum production and trading unit in the European Union, we are constantly looking at innovative technologies to enhance performance standards,” says Dimitris Stefanidis, CEO of AoG.

Opting for GE’s digital smelter solutions seemed like an obvious choice to Stefanidis. “After all, there is no potential downside of adopting these solutions, but if they work, the upside gains are tremendous.”

The digital smelter will use virtual sensors to “facilitate the ongoing collection and evaluation of parameters such as temperature and chemistry that are not ordinarily monitored continuously,” says Ammar Bustami, general manager for GE Power’s Digital Smelter Global COE. “We’re measuring almost 100 parameters per pot, and the digital solutions can explain why there is a variance between different pots and optimize the values within.” Bustami says that “physics models and analytics are applied to the data to not only understand what is happening in the pots but also to predict how they will react under a variety of circumstances and stimuli.”

Using the digital smelter solutions, AoG can accurately estimate a variety of conditions in the pots. It can then predict how they will function in the short and long term and recommend adjustments to maximize efficiency.

The system can be constantly adjusted. For example, as pots are taken offline, repaired and returned to use, they can quickly incorporate the new parameters, not only maximizing the efficiency of each pot, but also integrating them with the rest of the production line, Bustami says.

Constructing these first-of-their-kind digital smelter solutions isn’t an easy undertaking, but Bustami estimates that it will bring AoG a more than tenfold return on the investment needed to create them.

The solutions are a product of the GE Store, being created by a team of software engineers and developers based in San Ramon, California; GE Power’s Digital Smelter Center of Excellence (COE) in Dubai, United Arab Emirates; and GE’s Global Research Center in Bangalore, India.

The post Metalmorphoses: This Greek Digital Smelter Uses Software To Keep A River Of Molten Aluminum Moving appeared first on GE Reports.

The Jean Jaurès elementary school in the town of Rueil-Malmaison outside of Paris is full of French charm. Light streams into a room on the second floor through colored glass casting playful reflections on the floor. Like all schools, the place is an incubator for young brains but also for a piece of cutting-edge technology: the world’s first “green” blockchain.

The system, which was developed by the energy tech startup Evolution Energie, enables users to track renewable power as it moves through the electrical grid and mixes with energy from other sources. “Using blockchain, you can sell energy from your renewable sources to your neighbor without the help of a utility managing the process,” says Fabien Imbault, Evolution Energie’s managing director. “You could share your energy with neighbors or even sell it to a parked electric car on your street and get paid securely.”

Evolution Energie started by building an interface that was simple enough for students at the school to purchase “green” energy from renewable energy sources. They’ve since rolled the system out to the town’s municipal buildings. Up next: businesses and homes.

Blockchain is the distributed ledger technology best known as the underpinning of the virtual currency bitcoin. As people minted and then traded bitcoins, the blockchain recorded every transaction on a digital ledger that was shared by thousands of different computers. This innovation created a permanent, accurate, searchable, and anonymous record that can be quickly updated. Unless otherwise compromised, its decentralized nature also makes it extra secure.

Top illustration: “Using blockchain, you can sell energy from your renewable sources to your neighbor,” says Fabien Imbault, Evolution Energie’s managing director. Image credit: Getty Images. Above: An image of the ledger of the green blockchain. Image credit: Evolution Energie.

The jury is still out on whether bitcoin will ever rise to the level of a currency like the dollar, but blockchain holds the promise of revolutionizing any industry that requires recorded transactions.

Power is one of them. A rising percentage of electricity comes from renewable energy — small wind farms, factories generating excess electricity and individual homes and offices producing power from solar panels. We need a system that can track the buying and selling of electricity generated by these distributed, Imbault says.

Imbault and his colleagues realized that by using the blockchain, they could connect all of those producers in a secure way, and develop a new marketplace where anyone can sell energy at the right price as easily as they can sell shares on a stock exchange.

The blockchain can be also used to certify renewable energy as authentically “green,” Imbault says. This could enable the trading of renewable energy certificates and lead to a world where green energy commands a premium price, if demand is high enough. The area around the environmentally-friendly Rueil-Malmaison is a good location to test the idea because of the town’s eco-district called Arsenal.

Evolution Energie — which makes software for energy monitoring and environmental reporting as well as commodities trading and risk management — is building the system on Predix, GE’s platform for the Industrial Internet. Its engineers are working at the European Digital Foundry in Paris, where, among other things, GE seeds startups that are developing innovative applications for the Industrial Internet. The firm was one of the five winners of GE’s Digital Industry Europe competition, where GE selected startups to work with on Predix-based products.

Evolution Energy plans to offer its blockchain electricity trading system to energy-sharing communities around the world by the end of the year. Imbault says that without collaborating with GE, the French startup would have struggled with the global nature of the challenge. Says Imbault: “GE gives us the ability to provide this service at the city scale around the world.”

The post Vive La Révolution Digitale: A Parisian Suburb Started Testing A Renewable Energy Blockchain appeared first on GE Reports.

Outside of the Island of Sodor, where Thomas the Tank Engine and his magical friends live, trains don’t usually speak. That’s about to change in Europe, where locomotives are set to start talking to their operators and maintenance crews through data collected from thousands of sensors.

Across Germany, Britain, France and Poland, 250 locomotives run by Deutsche Bahn Cargo (or DB Cargo), the region’s largest rail-freight company, are being retrofitted with GSM connections to transfer information from sensors and failure data. They will work with GE’s Rail 360 Asset Performance Management (APM) Software, which will analyze the terabytes of input streaming in for insights, and make the freight mover smarter.

DB Cargo trains haul almost everything, from raw resources like coal to finished products like cars. But like all rail and freight operators, they sometimes run into unscheduled delays. A locomotive stuck somewhere on the track can get expensive. ”That’s where our solutions come into the game,” says Huschke Diekmann, GE´s general manager for transportation in Germany.

Above: A locomotive stuck somewhere on the track can get expensive. ”That’s where our solutions come into the game,” says GE”s Huschke Diekmann. Image credit: Deutsche Bahn. Top image: Across Germany, Britain, France and Poland, 250 locomotives run by Deutsche Bahn Cargo (or DB Cargo), the region’s largest rail-freight company, are being retrofitted with GSM connections to transfer information from sensors and failure data. Image credit: Getty Images.

Here’s how: Many modern rail freight operators still perform maintenance checkups on a set schedule driven by mileage or time rather than the actual condition of the parts. But DB Cargo is outfitting each of its locomotives with devices to gather data from sensors that will monitor brake performance, motor temperature and other conditions.

This approach doesn’t apply just to trains. The energy and aviation industries, for example, have started looking at digitizing power plants, oil rigs and jet engines, as well, and connecting them to the Industrial Internet. “Every industrial company is going to have to stake its digital claim about how you do a better job with customers, how you drive cost down, and we can lead this,” GE Chairman and CEO Jeff Immelt told CNBC’s Jim Cramer last year.

The data from the sensors will move to a shoebox-sized “telematics box” in the back of the driver’s dashboard. From there it will travel every couple of seconds to a control center at DB Cargo’s head office in Frankfurt, Germany, and pop up on screens at one of the dozen or so maintenance depots across Europe. Technicians there can then analyze the data with DB Cargo’s prediction system.

By “2020, we want to have 2,000 locos equipped with intelligent diagnostics — an important step to build ‘self-aware’ trains,” says DB’s Matthias Thomas. Image credit: Deutsche Bahn.

The GE part of the system is running on Predix, GE’s platform for the Industrial Internet. DB Cargo can use that information to predict when components such as the brakes or the water tank might need maintenance. The rail operator also gets daily, weekly and monthly reports and advisories on, say, whether the engine coolant level has dropped and what action to take. “In the old days the maintenance depots didn’t have that information available before something happened,” Diekmann says. “The benefit of this Predix APM solution is you have all the prediction available when necessary.”

Mathias Thomas, vice president for asset projects at DB Cargo, predicts that “the locomotives from the project with GE deliver a significant reduction of service failures and thus help us to improve our overall fleet availability.”

Says Thomas: “The cooperation with GE is an essential part of our ‘TechLOK’ system, where already about 900 locomotives deliver data regularly. [By] 2020, we want to have 2,000 locos equipped with intelligent diagnostics — an important step to build ‘self-aware’ trains.”

The post On The Right Track: Software Is Helping Make European Trains Smarter appeared first on GE Reports.

Dirk Uhde isn’t the kind of guy who talks a lot about software. So when a team of data scientists and software developers from GE Digital’s European Foundry met him amid the sparks, grime and welding equipment of the industrial plant he manages in southeastern France, he struggled to follow their technical parlance. When he tried to explain how his machinery worked, they didn’t have an easy time either. Yet it was the most productive meeting he’d had in years, he now says. It brought together two very different worlds: the traditional industrial world and the digital world that’s changing how we make things.

Uhde’s plant in Aix-les-Bains, a thermal spa town in eastern France, builds components for gas-insulated substations, which transform high voltage on the electrical grid. As part of the process, he cuts and assembles aluminium pipes for substations working around the world. These pipes come in two sizes: 9 and 11 meters long, and the plant makes about 20 kilometers’ worth per year for these substations.

Uhde’s challenge was really a math problem. The small team that handles pipe cutting must make on average about 600 cuts to fulfill orders each month, or 150 cuts per week. The problem for years had been that about 10 percent of those cut pipes ended up wasted. That’s not because the workers make mistakes but because of the challenge of calculating exactly how to cut up the standard pipe sizes to leave close to zero remnants. It’s the same problem that comes with figuring out exactly how many floorboards you’d need to put down for a room and how best to cut them to avoid squandering your material. The plant can sell the leftover pipe pieces as scrap, but for less than 30 percent of their wholesale price.

“The process used to be completely manual,” Uhde says. One worker would spend at least an hour making calculations and trying to optimize the sequence of cutting, including how many pipes were available to cut, what their sizes were and what sizes were needed by the end of the day. “We’d done it like this for 30 years and tried to find improvements,” he says.

Top: The team figured out there were more ways of making those 600 pipe cuts each month than there were atoms in the universe — roughly 4×1079 possibilities. GIF credit: GE Digital. Above: “Running a plant, you try to improve productivity all the time,”Dirk Uhde says. “And then comes a tool like this which is a quick hit. The key was to bring an expertise into the process which we didn’t have, which was digital.” GIF and image credit: GE Digital

Then in late 2016, GE’s European Digital Foundry contacted Uhde as part of a pilot project to see whether industrial businesses could use software to improve performance. When Vincent Champain, general manager of the European Foundry, arrived from Paris at the plant along with his team of four other digital mavens in January 2017, he had grand plans to fix things. But the two worlds, manufacturing and software, found it difficult to communicate with each other. “My team was looking at them and saying, ‘This cannot work,’” Uhde recalls.

Understanding emerged when both teams put on helmets and safety goggles and moved down to the factory floor where workers were cutting and welding aluminium pipes. For some of the digital team, this was the first time they had actually been on a manufacturing floor. “It was amazing,” says Igor Dniestrowski, a project manager for app development at the Foundry. “This is the moment where we saw the field reality, the production process as well as the people dedicated to their jobs. It is when the concept becomes a true digital industrial application.”

For example, being able to see how heavy the pipes were and how difficult it would be to shift them from the bottom of a pile to elsewhere in the production hall helped the digital Foundry team to start improving the cutting process.

The most efficient method would be to test all the possible solutions first. But that would take a huge amount of time and processing power for any computer. The team figured out there were more ways of making those 600 pipe cuts each month than there were atoms in the universe — roughly 4×10⁷⁹ possibilities, Champain says.

The problem for years had been that about 10 percent of those cut pipes ended up wasted. GIF credit: GE Digital

Yet calculating all those options was possible thanks to cloud computing and Predix, GE’s digital platform for the Industrial Internet. After their tour of the plant, Champain, Dniestrowski and the others went back to their office in Paris. Within just four weeks — by the end of February — they had built an app that calculated how and where to cut each pipe at the Aix-les-Bains plant for maximum efficiency.

Now Uhde uploads his daily pipe-cutting requirement to the app, and “it’s just a few seconds before Predix spits the results out,” he says.

Crucially, the app has reduced scrap waste from 10 percent to 4 percent, which should save the plant an estimated $200,000 this year alone.

Down the line, the app can be revamped to cut waste in other parts of the plant too. Developers at the European Foundry are now working on an algorithm that can suggest the most efficient way to pack the finished pipes into shipping crates. Dniestrowski says it should take about a month to upgrade the app, which Uhde estimates could double or even triple the annual savings from the pipe-cutting algorithm.

“Running a plant, you try to improve productivity all the time,” he says. “And then comes a tool like this which is a quick hit. The key was to bring an expertise into the process which we didn’t have, which was digital.”

The post Waste Not: This App Just Solved A Manufacturing Riddle Larger Than All The Atoms In The Universe appeared first on GE Reports.

The day after Christmas in 2015, workers at the Port of Los Angeles set a personal record. They unloaded a massive cargo ship called the Benjamin Franklin, the largest ever to land in North America, in just three and a half days.

Such brisk efficiency takes lots of planning. The right equipment has to be in place to move the merchandise from the ship and onto trucks and trains for distribution. In this case, it was a months-long logistical exercise — carried out mostly by telephone and spreadsheets.

Port operators knew they could do better. So they partnered with GE to create a pilot program making cargo shipment data visible with GE software. The pilot, which went live this week, will help the port’s complex system of shippers, terminal operators, trucks, rail cars and other components run more efficiently.

A cargo ship in the Port of Los Angeles. The port will pilot GE’s Predix system to improve its operations. Top and above images credit: Getty Images

The companies in the pilot include Maersk Shipping and Mediterranean Shipping, as well as retailers such as The Home Depot and Lowe’s. They will test the system for two to three months at the port’s APM Terminals, with the possibility of expanding it across all 16 Port of LA terminals in the future.

Seth Bodnar, GE Transportation’s chief digital officer, says the port resembles a giant restaurant. “In the past, we didn’t know who to serve until the customer showed up — you didn’t know what was coming off the ship until a couple of days before the ship arrived,” he says.

Such short notice can lead to bottlenecks. The new GE software system makes data available to the ports two weeks before the ship arrives, giving everyone plenty of time to synch their assets. The system will also tell workers the cargo’s final destination so that trucks and machines can be ready to move the goods in the most efficient way possible. The payoff can be huge. Bodnar says that a 1 percent improvement in efficiency at just one port can net $60 million in savings.

“In the past, we didn’t know who to serve until the customer showed up — you didn’t know what was coming off the ship until a couple of days before the ship arrived,” says GE’s Seth Bodnar. Image credit: Getty Images

There are other benefits. Bodnar says that efficiency can also help reduce the port’s impact on the environment by reducing the number of idling trucks.

Port of LA Executive Director Gene Seroka says pulling the pilot program together was a logistical feat in itself. The team had to securely pool terabytes of data from several different databases. They brainstormed with GE on a dashboard to make sense of the data and deliver real-time, comprehensive insights to the right people at the right time. “To keep pace with the rapidly changing shipping landscape, operations at our ports must evolve,” Seroka says.

The partners say that if the pilot is successful, it could scale to other ports across the country. As the world becomes more connected, ships are getting bigger and more complex: Between Asia and the U.S. West Coast the average container ship size has risen 14 percent in the past two years, and seaports account for roughly 90 percent of trade worldwide.

GE’s “In The Wild” video series recently visited the port and talked to Seroka. Take a look.

The post Chips Ahoy: The Port Of LA Is Getting A Digital Makeover appeared first on GE Reports.

Speaking at an annual gathering of industrial executives, Wall Street analysts and investors Wednesday in Florida, GE Chairman and CEO Jeff Immelt outlined GE’s strategy as a simplified, digital industrial company with an increased focus on digital and additive technologies like 3D printing.

During his presentation at the Electrical Products Group Conference in Longboat Key, Florida, Immelt reaffirmed GE’s operating framework for the year and illustrated how the company is increasing productivity and gaining market share in a tougher global environment. Immelt added that GE’s cash and capital allocation goals remained on track for 2017. Last quarter, GE’s cash performance was below expectations, but the company expects sequential improvement in cash flow from operating activities throughout the year. GE made no change to its original cash targets for 2017.

In addition to its operating framework and focus on cash, GE is committed to expanding margins and simplifying the company. In the first quarter, GE was $200 million ahead of its original plan to reduce costs throughout the company.

By 2018, GE expects to cut $2 billion in structural costs, with about 100 basis points of margin expansion and 3-5 percent organic growth per year. To date, GE has kicked off several significant actions to reduce the cost of its operations, and the company already is seeing lower costs from optimizing its newest technologies like the H-turbine. Making a more focused company will help GE be more profitable and competitive, Immelt said.

Top image: A titanium bracket for the Airbus A350 XWB passenger jet 3D-printed on a Concept Laser machine (in the front) is 30 percent lighter than its conventionally manufactured predecessor. Image courtesy of Airbus. Above: The first offshore wind farm in the United States near Block Island, Rhode Island, uses GE technology. Image credit: Chris New for GE Reports.

GE also is focusing on improving supplier productivity in its industrial businesses. GE acquired LM Wind Power and combined its engineering and supply chain capacity with one of the world’s largest wind turbine manufacturers. GE Aviation also acquired AirVault, a supplier for cloud-based digital records management, which will boost GE’s asset management and maintenance optimization for its aviation arm.

In the oil and gas sector, GE plans to combine GE Oil & Gas with Baker Hughes to build a new fullstream digital industrial services company. With about $1.6 billion in growth and cost synergies expected by 2020, the new company – a combination of GE’s technology expertise and Baker Hughes’ service capabilities – is uniquely positioned to deliver fullstream solutions to the market, Immelt said. The deal is expected to close in mid-2017.

Throughout the presentation, Immelt highlighted the strength of GE’s portfolio, pointing to innovative products in aviation, power, healthcare and wind. He emphasized that the company’s record $240 billion long-term services backlog brought a number of benefits to GE and its customers, including predictable maintenance costs, higher margins and returns, and more comprehensive services.

For these products and services, digital and additive technologies are changing the way GE operates across its industrial businesses. Earlier this year, GE acquired ServiceMax – a company that brings GE a new set of software and expertise in cloud-based field service management across industries. Last year, GE acquired Concept Laser and Arcam AB – two leading industrial additive companies – to help GE and other customers make more 3D-printed parts and increase productivity. These machines use a combination of software, digital design and additive materials like metal powder to create parts and structures not possible with traditional manufacturing. The GE Store, which is the transfer of technology, expertise and talent across GE’s businesses, allows businesses like Aviation, Healthcare and Oil & Gas to share some of these technologies, Immelt said.

GE’s customers have noticed the company’s progress in digital and additive manufacturing. Recently, the Port of Los Angeles launched a first-of-its-kind pilot program to digitize shipping data. In Europe, GE is creating  a self-aware, digitized fleet of 250 locomotives to optimize freight schedules. Over the weekend, GE announced a $15 billion memoranda of understanding and agreements with Saudi Arabia, including data analytics initiatives across its multiple industries. Approximately $7 billion of these announcements are GE technology and service solutions. In April, GE signed a $3 billion deal with Sonelgaz in Algeria to bring power to  8 million Algerian homes. As the largest services deal in GE Power’s history, it also marks the second-largest Industrial Internet software deal for the business. These are important milestones for GE, and the company is executing its digital industrial strategy, Immelt said. With this strategy, GE will create value for its shareowners, customers and employees, he concluded.

The post Immelt Updates Investors On GE’s Digital Industrial Strategy appeared first on GE Reports.

Many energy experts view Europe as a sort of crystal ball for the energy industry — one that’s showing a decidedly mixed future.

On the one hand, renewable sources like wind and sun provide more power than ever. They are also the fastest-growing sources of energy, accounting for 86 percent of all new generation capacity added to the European market in 2016.

On the other hand, traditional power generation (think coal, gas and nuclear) still plays a role. In 2016, more than two-thirds of power in Europe came from nonrenewable sources. Globally, renewables are expected to reach parity with coal and gas around 2040.

Nevertheless, the speed with which intermittent renewables — the sun doesn’t always shine and the wind doesn’t always blow — are coming on board is making it harder for European utilities to balance the grid. That’s because the grid, as large as it is, is also a delicate system where supply must match demand at all times or there’s a risk of blackouts. In France, for example, strong winds in the north mixed with a sunny week on the Riviera in the south can lead to a surfeit of electricity that puts the balance at risk.

The intermittency also makes profits hard to find, with European utilities on average struggling to increase profits 1 percent in 2016. Countries around the world are watching how Europe uses thermal generation to keep the grid balanced; prioritizes low-cost, clean and renewable energy; and keeps utilities profitable amid a rapidly changing energy network.

Top: Wind and solar power are intermittent and unpredictable — making them a challenge for energy traders seeking profits. Image credit: Chris New for GE Reports. Above: The Business Optimization app within GE’s new Digital Utility software suite supplies real-time data to traders that can help them make more informed decisions. Image credit: GE Power

The good news is that the Industrial Internet of Things can help. GE, for example, just released Digital Utility, a new software suite that gives energy traders machine and operations data they can use to make more profitable trades.

The suite’s new Business Optimization app supplies real-time data to energy traders, who play a key role in ensuring that supply matches demand and utilities stay in the green. “Traders looking at the day ahead will be able to bid in the most optimal way,” says Scott Bolick, head of software strategy for GE Power. “They can not only make sure that the electricity is able to be dispatched, but also that the best-performing plants are dispatched first.”

Today, most trades are typically based on long-term outlooks — for example, anticipating a surge in demand in the winter when everyone turns on their heaters. But as wind and solar installations depend on fickle weather and make anticipating supply increasingly difficult, more sales are starting to happen on the spot market. This market, at least in theory, soaks up the electricity that needs to be bought and sold immediately.

The challenge is that the spot market requires a speed and accuracy that Wall Street is all too familiar with. Better trades, and profits, depend on better information. But Bolick says the power industry uses only about 2 percent of the energy industry’s data — including the real-time information about a plant’s ability to produce electricity, its efficiency, weather forecasts and consumer demand, as well as forecasting information about how much energy to expect from renewable sources and when to expect it. In some cases, traders rely on spreadsheets or separate information systems to inform market bids.

The Digital Utility software suite brings utility data together by stacking the Business Optimization app on top of GE’s Asset Performance Management, a machine reliability app, and GE’s Operations Optimization, an efficiency and productivity app. Used as a full suite, utilities get an end-to-end view of how the energy network is functioning in real time.

The apps rely on analytics from a catalog of more than 100,000 digital twins, or virtual representations based on actual data from energy assets like power plants. They can model future scenarios, predict potential outcomes, make trading more efficient and help keep the grid stable. “When something goes wrong, traders will know immediately,” says Anna Geevarghese, chief product manager at GE Power Digital. “So when a water pump breaks or a gas turbine needs to go down, they know that information.”

This transparency can also help plants better manage operations so that traditional fuel sources are used when both profitable and necessary. Shutting down and starting up coal-fired plants, for example, is an incredibly labor-intensive — and expensive — procedure. Without having good information about coming electricity demand and supply, plants have to keep burning fuel, running at low levels so that they’re ready to ramp up when needed. With better information, utilities can make informed decisions about whether to shut down a plant or to keep that plant running and trade into the ancillary market, which helps grid stability. Cutting back on unnecessary plant idling will also help reduce emissions.

As the energy market becomes more transparent, Bolick says, it will ease the transition to renewables. “Essentially, we’re trying to provide safe, reliable, secure, affordable and sustainable electricity,” Bolick says. “At the end of the day, what we’re doing here digitally is going to make sure that those five goals are met even as we go through a substantial fuel source change.”

The post Renewable Energy Makes Things Tough On The Grid, But New Software Could Help appeared first on GE Reports.

Talia Kohen exudes enough personal energy to light up a ballroom. But her goals are much grander. “I want electricity to be the factor that unites all of Europe, just like the euro,” she says.

That’s why earlier this year, she pulled together a mostly Israeli team to fly from Tel Aviv to a “hackathon” in Berlin, where they designed a prototype for a virtual currency called ElectroEuro. The currency could allow European utilities to price and trade clean power. “It’s like a bitcoin for energy,” she says. The Ecomagination Challenge Hackathon took place alongside GE’s Minds + Machines Europe digital summit, and team ElectroEuro was one of the winners sharing in €50,000 ($56,000) in cash prizes.

Some 100 developers took part in the event on a sightseeing boat anchored in one of Berlin’s industrial harbors. Most of the participants were men, but Kohen, 32, wasn’t intimidated. The American native has a degree in electrical and computer engineering from Cornell University. Upon graduation, she joined Raytheon, where she worked on radar and missile technology. Still wanting to learn more, she moved to Israel’s Bar Ilan University in Tel Aviv and enrolled in a master’s program focusing on computer science, artificial intelligence and natural language processing.

But she never stopped looking for opportunities. A few years ago, she applied for Google’s prestigious Anita Borg Memorial Scholarship designed to bring more women into computer science. She made it into the final round, but she didn’t make the cut. So she founded her own group in Israel for female computer scientists called FemTech, which now has more than 1,000 members.

Top: Kohen (center) and Koretzki’s (left)  the team included Haim Bender, Isaack Rasmussen and Idan Nesher. Bender and Rasmussen integrated the prototype with GE’s Predix platform for the Industrial Internet, and Nesher created its user interface. Above: The team arrived in Berlin on Sunday and went straight to the “hacker boat,” as the venue became known. Images credit: GE Reports

Kohen learned of the hackathon when Ira Blekhman, a GE employee in Israel, posted information about it on FemTech’s Facebook page. It said that GE would fly the first 10 applicants to Germany. “I knew that women don’t usually step out of their comfort zone and compete in coding competitions,” Kohen says. “Naturally, I jumped on it.”

Kohen put together a small team and called on the skills she’d learned through Google Outstanding, a public speaking training program. “I didn’t want to leave anything to chance,” she says.

The team arrived in Berlin on Sunday and went straight to the “hacker boat,” as the venue became known. She and her teammates, which included Ran Koretzki, a computer science graduate student from Israel’s Technion technical university, got to work. They gathered information about the amount of electricity different European countries produced and consumed and from what sources. Next, they designed an algorithm that allowed utilities to trade the surplus. “It’s like an energy bank,” Koretzki says. “You can use the ElectroEuro to buy and sell electricity, based on the source.”

In addition to Kohen and Koretzki, the team included Haim Bender, Isaack Rasmussen and Idan Nesher. Bender and Rasmussen integrated the prototype with GE’s Predix platform for the Industrial Internet, and Nesher created its user interface.

When connected to Predix, the prototype would monitor energy production data from eight different sources, including wind and solar, but also coal and nuclear. It could then price the electrons based on availability, distance, stability and friendliness to the environment. “Wind, for example, is very green, but it’s also fickle,” Kohen says. “Coal, on the other hand, is very predictable, but also pollutes the air.”

The team says its solution would enable European governments to promote “clean” energy by allowing utilities to bid on power from the energy source they want. “The whole idea is to promote decarbonization,” Kohen says.

A team from Munich presenting their solution to the jury. Image credit: GE Reports.

The two-day hackathon featured two main challenge areas: electrification (moving to renewable power use and generation) and advanced manufacturing to decarbonize the economy. Kohen’s team won in the electrification category and placed second in building solutions on Predix. (See all the winners here.)

Various European industries had submitted real-world problems for competitors to solve. “It’s really powerful, because they have a real need and are hoping one of the teams finds a solution,” says Elizabeth Wayman, GE’s global director for Ecomagination, which sponsored the hackathon. Eurelectric and Intel also partnered on the hackathon while ESB Networks, European Heat Pump Association, Fraunhofer and Stelia Aerospace contributed data. Competitors, working individually or in groups, had about 36 hours to design a working app prototype.

As the winners in the electrification category, Kohen and her team will be invited to present their app next week at the European electric utility consortium Eurelectric’s annual convention and conference in Brussels.

Ecomagination director Deb Frodl (upper right in pink sweater) with Kohen and the two other winning teams in Berlin. Image credit: GE Reports.

The post Building The Bitcoin For Energy: This Woman Came Up With A Promising New Idea For Trading Clean Power appeared first on GE Reports.

Jeff Immelt, GE chairman and CEO, recently sat down with CNBC host Jim Cramer to talk about GE’s transformation into the world’s largest digital industrial company. Here are the highlights from the interview.

Cramer started by asking Immelt about turning GE into a “top 10 software company” by 2020. Immelt explained that jet engines, medical scanners and other industrial machines GE sells are already full of sensors that gather large amounts of data. “Seven years ago, we kind of got started as a way to protect our installed base, to grow our service business,” Immelt said. Today the company is “kind of half the way to our goal to be $15 billion [in digital orders] by 2020,” he said.

GE has 28,000 people working on digital projects, and Immelt said that orders were growing 25 percent a year. “We’re kind of first among equals in the Industrial Internet,” Immelt said. “We can play, we can do this.” He added: “Every industrial company is going to have to stake its digital claim about how you do a better job with customers, how you drive cost down, and we can lead this.”

Above: Arterys is using data generated by GE MRI scanners to see the heart in seven dimensions — three in space, one in time, and three in velocity direction. The system allows physicians to see actual blood flow in the heart as a 3D image. This picture illustrates speed and direction of blood flow with color-coded vectors. Image credit: Arterys. Top: GE wants to build a digital model, or twin, of every GE machine, from a jet engine to a locomotive, and use it to use to anticipate maintenance needs and outages, measure performance and test different operating modes. Image credit: GE Digital

Immelt told Cramer the current size of the digital market was $100 billion. “It’s a big idea,” he said, adding that software can optimize assets as diverse as jet engines, pipelines and MRI scanners. Immelt acknowledged that there will be “a ton of competitors.” But GE also has “$225 billion of contractual agreements already signed with customers that are productivity-based,” he explained. “So we have this kind of connection with customers that nobody else really has, and we can add analytics on top of that in ways that IBM and Siemens can’t do.”

For example, Immelt said, GE medical scanners generate 45 million images a day. “IBM doesn’t have that, really,” he said. “The Industrial Internet is going to break very differently than the consumer internet or the enterprise internet.”

GE’s deep industrial expertise is another advantage, Immelt said. “What’s hard in this world is knowledge of the assets,” not finding a qualified coder, he said. “What we have that the other guys don’t have is we know the material history of every jet engine, right? We can build digital twins around gas turbines. I think we bring the physics along with the analytics. We can kind of see this happening.”  GE’s operating system for the Industrial Internet, Predix, will be a key driver, he said. “We’ll get a billion dollars in Predix orders this year, so it’s real.”

When asked about GE quickly capitalizing on machine learning and artificial intelligence, Immelt pointed to another example from healthcare. He said that a radiologist uses just 10 percent of what a medical scanner can deliver on the first read. “The other 90 percent can be modeled using AI post-processing,” Immelt said. “We saw that 10 or 15 years ago. So these are concepts that are well known inside the company, and ones we think we can leverage across the installed base.”

You can watch the interview here:

The post A $100 Billion Idea: GE’s Jeff Immelt Talks To CNBC’s Jim Cramer About Industry’s Digital Transformation appeared first on GE Reports.

Virtual reality became domesticated last year — at least in America — when the VR viewer Google Cardboard arrived for the first time with the Sunday New York Times. Today, you could use it to explore Pluto’s frigid heart or climb to the top of 1 World Trade Center in downtown Manhattan.

As thrilling and immersive as these experiences are, they are just a playful precursor of what’s coming. Companies such as GE have started using VR to optimize the electric grid, service nuclear power plants and plan complex supply chains.

For example, for the past two years, GE engineers in Rugby in the U.K. have been using VR to optimize and even design factories, a task typically done with computers in two dimensions. As good as that approach is — virtually all modern factories have been designed this way — the method can make it difficult to anticipate problems that crop up once the building is in actual use in the three-dimensional world. But by then, it’s too late to fix the design without expensive retrofitting.

Above: “We’ve been looking for ways to optimize our factories and VR seemed to us like a good idea,” says GE’s Neha Prajapat, an engineering tool specialist in Rugby. She’s also a gamer. Top image: Prajapat and her team used Microsoft Kinect to study the movement of workers inside a GE factory. Images credit: GE

The GE team says VR, in combination with data coming from working factories, will help them avoid problems before they pop up. Real-world data allows the designers to see how workers move and where they gather in an existing plant and where production tends to back up. Design tweaks and more feedback then enable the team to improve new factory layouts. “We’ve been looking for ways to optimize our factories and VR seemed to us like a good idea,” says GE’s Neha Prajapat, an engineering tool specialist in Rugby who is leading the project.

Prajapat began working on factory-optimization projects in 2012 with the Manufacturing Informatics Centre led by Prof Ashutosh Tiwari at the nearby Cranfield University, a school that focuses on working with industry to develop new technologies. (Prajapat is pursuing a part-time Ph.D. there.)

Just like the New York Times, GE created VR tours of its gas turbine test stand in Greenville, South Carolina (above), and a locomotive testing facility in Pueblo, Colorado (below). Images credit: GE

Her GE team began working on VR as part of an Innovate UK funded project in 2014. They wanted to know if they could convert a standard 2-D factory model into a 3-D scale model and then tweak it for use in VR headsets or 3-D projection.

Prajapat plays video games, and so using the Microsoft Kinect gaming console to monitor movement in GE factories seemed to her like an obvious first step. The console can record objects’ positions and allows players to turn themselves into avatars inside games and perform tasks such as karate kicks and sword fighting.

The team decided to test the approach at a U.K.-based maintenance facility. They scouted 30 different locations at the plant and laser scanned them. “You could see people walking around the factory, where they were going, how long they were spending on operations, if people were crowding around one area,” Prajapat says.

So far, so good, but the following step — feeding the data into a 3-D model of the plant — was trickier. If the plant images were too high-definition, the computer would have trouble rendering them smoothly. The images shuttered and refreshed in a jerky manner. The researchers decided to strip some details from the digital record of the real world before they merged it the digital factory design.

The result is a visual experience that looks computer-generated but contains all the details of the real factory, including machines, doorways and signs. Managers can use the VR tour of the factory to analyze how shift changes work, as well as how people flow through the space, Prajapat says.

Prajapat says GE factory designers will soon be able to use information from the pilot to create plans for brand-new plants. “They will then be able to build factories that are as people-friendly and as flexible as possible,” she says.

Several projects already are underway using the technology for different GE businesses, including GE Grid Solutions, GE Aviation, and GE Oil and Gas.

The research team presented its mock-ups for the U.K.-based maintenance facility in January at the UK’s GE Energy Leadership Workshop, where it won the award for Best Showcase.

Says Prajapat: “I don’t think I’ve ever given out so many business cards at an event.”

The post Call Of Duty: This Woman’s VR Simulation Makes Factories Work Better appeared first on GE Reports.

Home to the Valley of the Muses, Greece’s Mount Helicon has been hailed by Ovid and Hesiod as the font of inspiration and poetry. But today, the plains between Helicon’s foothills and the cool blue waters of the Gulf of Corinth are yielding a more prosaic kind of material: aluminum. Instead of verse, raw red bauxite — a mixture of aluminum oxides — flows freshly mined from the hills to a large smelter operated by Aluminium of Greece (AoG) in the town of Agios Nikolaos. On the other end, 185,000 tons of the pure silvery metal comes out every year, ready to be shipped all over the world.

The smelter’s location may be unique, but its owner, Mytilineos Group, is dealing with a global challenge affecting the entire smelting industry: The price of aluminum has dropped by almost half in the last 10 years, while the cost of production has dropped by only about 30 percent. Electricity is the biggest single contributor to cost, accounting for between 30 and 40 percent of production costs. Like other smelters, AoG found ways to become more efficient and remain profitable by putting in place successive cost-reduction programs.

“The key variables AoG is continuously looking to improve include energy use, raw-material consumption and preview of pot leakages,” says Bhanu Shekhar, chief digital officer for GE Power in the Middle East and Africa. “GE’s digital smelter solutions, data mixed with analytics, and physics can help them do just that and more.”

Top and above: AoG has three potlines consisting of 780 smelting pots running around the clock. Images credit: AoG

Current efficiency, or the relationship between the current intensity and the amount of aluminum a smelter produces, is the most important element of the smelting process. “Generally in a smelter, current efficiency runs around 93 to 94 percent, but just 1 percent increase in efficiency per year could be $2 million to $3 million in savings,” Shekhar says.

This benchmark is closely ties to “specific energy consumption”— a rate that describes how many kilowatt-hours it takes to produce a ton of aluminum. To improve it, AoG needed to find a way to optimize its smelting process.

The smelter is using a variant of the Hall-Héroult process, an industrial technique that has changed remarkably little since it was developed in 1886. AoG makes pure aluminum by first dissolving aluminum oxide, or alumina, in electrolytic cells filled with the molten aluminum compound cryolite. This bath lowers pure aluminum’s melting temperature from more than 2,000 degrees Celsius to about 940 degrees.

AoG has three potlines consisting of 780 smelting pots running around the clock. Each cell is insulated with a layer of high-silica bricks and lined with stainless steel and carbon, which serves as the cathode. There are also carbon anodes immerse in the metallic bath. When workers run a strong electric current through the bath, the reaction, called electrolysis, separates pure aluminum from the solution and pulls the metal towards the cathode on the bottom, where it can be periodically siphoned off.

These are high temperatures and extreme voltages, and slight mistakes can lead to major problems. The overheating of the pots, for example, can damage the brick lining and steel sheet and cause “pot leakage.” On the the other hand, a prolonged break in energy supply can potentially ruin the potline by “freezing” the molten bath and the aluminum.

To limit these problems and increase efficiency, AoG is deploying the world’s first digital smelter technology built on Predix, GE’s platform for the Industrial Internet. “As the largest vertically integrated bauxite, alumina and aluminum production and trading unit in the European Union, we are constantly looking at innovative technologies to enhance performance standards,” says Dimitris Stefanidis, CEO of AoG.

Opting for GE’s digital smelter solutions seemed like an obvious choice to Stefanidis. “After all, there is no potential downside of adopting these solutions, but if they work, the upside gains are tremendous.”

The digital smelter will use virtual sensors to “facilitate the ongoing collection and evaluation of parameters such as temperature and chemistry that are not ordinarily monitored continuously,” says Ammar Bustami, general manager for GE Power’s Digital Smelter Global COE. “We’re measuring almost 100 parameters per pot, and the digital solutions can explain why there is a variance between different pots and optimize the values within.” Bustami says that “physics models and analytics are applied to the data to not only understand what is happening in the pots but also to predict how they will react under a variety of circumstances and stimuli.”

Using the digital smelter solutions, AoG can accurately estimate a variety of conditions in the pots. It can then predict how they will function in the short and long term and recommend adjustments to maximize efficiency.

The system can be constantly adjusted. For example, as pots are taken offline, repaired and returned to use, they can quickly incorporate the new parameters, not only maximizing the efficiency of each pot, but also integrating them with the rest of the production line, Bustami says.

Constructing these first-of-their-kind digital smelter solutions isn’t an easy undertaking, but Bustami estimates that it will bring AoG a more than tenfold return on the investment needed to create them.

The solutions are a product of the GE Store, being created by a team of software engineers and developers based in San Ramon, California; GE Power’s Digital Smelter Center of Excellence (COE) in Dubai, United Arab Emirates; and GE’s Global Research Center in Bangalore, India.

The post Metalmorphoses: This Greek Digital Smelter Uses Software To Keep A River Of Molten Aluminum Flowing appeared first on GE Reports.

The Jean Jaurès elementary school in the town of Rueil-Malmaison outside of Paris is full of French charm. Light streams into a room on the second floor through colored glass casting playful reflections on the floor. Like all schools, the place is an incubator for young brains but also for a piece of cutting-edge technology: the world’s first “green” blockchain.

The system, which was developed by the energy tech startup Evolution Energie, enables users to track renewable power as it moves through the electrical grid and mixes with energy from other sources. “Using blockchain, you can sell energy from your renewable sources to your neighbor without the help of a utility managing the process,” says Fabien Imbault, Evolution Energie’s managing director. “You could share your energy with neighbors or even sell it to a parked electric car on your street and get paid securely.”

Evolution Energie started by building an interface that was simple enough for students at the school to purchase “green” energy from renewable energy sources. They’ve since rolled the system out to the town’s municipal buildings. Up next: businesses and homes.

Blockchain is the distributed ledger technology best known as the underpinning of the virtual currency bitcoin. As people minted and then traded bitcoins, the blockchain recorded every transaction on a digital ledger that was shared by thousands of different computers. This innovation created a permanent, accurate, searchable, and anonymous record that can be quickly updated. Unless otherwise compromised, its decentralized nature also makes it extra secure.

Top illustration: “Using blockchain, you can sell energy from your renewable sources to your neighbor,” says Fabien Imbault, Evolution Energie’s managing director. Image credit: Getty Images. Above: An image of the ledger of the green blockchain. Image credit: Evolution Energie.

The jury is still out on whether bitcoin will ever rise to the level of a currency like the dollar, but blockchain holds the promise of revolutionizing any industry that requires recorded transactions.

Power is one of them. A rising percentage of electricity comes from renewable energy — small wind farms, factories generating excess electricity and individual homes and offices producing power from solar panels. We need a system that can track the buying and selling of electricity generated by these distributed, Imbault says.

Imbault and his colleagues realized that by using the blockchain, they could connect all of those producers in a secure way, and develop a new marketplace where anyone can sell energy at the right price as easily as they can sell shares on a stock exchange.

The blockchain can be also used to certify renewable energy as authentically “green,” Imbault says. This could enable the trading of renewable energy certificates and lead to a world where green energy commands a premium price, if demand is high enough. The area around the environmentally-friendly Rueil-Malmaison is a good location to test the idea because of the town’s eco-district called Arsenal.

Evolution Energie — which makes software for energy monitoring and environmental reporting as well as commodities trading and risk management — is building the system on Predix, GE’s platform for the Industrial Internet. Its engineers are working at the European Digital Foundry in Paris, where, among other things, GE seeds startups that are developing innovative applications for the Industrial Internet. The firm was one of the five winners of GE’s Digital Industry Europe competition, where GE selected startups to work with on Predix-based products.

Evolution Energy plans to offer its blockchain electricity trading system to energy-sharing communities around the world by the end of the year. Imbault says that without collaborating with GE, the French startup would have struggled with the global nature of the challenge. Says Imbault: “GE gives us the ability to provide this service at the city scale around the world.”

The post Vive La Révolution Digitale: A Parisian Suburb Started Testing A Renewable Energy Blockchain appeared first on GE Reports.