Time was, outages on the power grid were the result of downed tree limbs. Trees and branches are still an issue, but power companies increasingly are worried about hackers and computer viruses. To wit, the ominously named malware Black Energy took out a grid in Ukraine in 2015 and caused 800,000 people to lose power. The threat is only increasing — year over year, cyberattacks on industrial control systems have increased by 55 percent.

Most computers have some kind of antivirus software today, but protecting control systems from hackers requires a completely different approach, says Justin John, a controls engineer who leads the controls algorithms team at GE’s Global Research labs in Niskayuna, New York. That’s why he and his team are developing the “Digital Ghost.”

John says the software is the industrial version of an immune system — an invisible presence in GE’s machines that keeps watch 24/7. It uses sensors and controls to detect, locate and neutralize threats much like the body responds to viruses.

Designing it, the team applied the old adage that the best defense is offense. “In cybersecurity, finding new ways to protect critical industrial assets from cyber threats is a never-ending job,” John said. “With Digital Ghost, we’re creating brand new layer of defense and offense that will protect the brains of these cyberphysical systems and even neutralize threats.”

There will be some 50 billion things connected to the internet by 2020, according to Cisco. As physical assets become more digitally driven, the need for technologies like Digital Ghost will only increase, said Lalit Mestha, a principal engineer leading the Digital Ghost program. “The integration of digital technologies into the industrial world are transforming it and opening up an abundance of new growth opportunities for companies and dramatic improvements in the overall quality of life people can live,” Mestha said. “But in parallel, we must remain vigilant in developing new and better ways to protect and sustain the operation of these assets from being compromised, as is the case in the human body.”

Mestha and John are giving their Digital Ghost a layer capable of learning about intruders much like the immune system’s killer T-cells. When it detects a threat, it will pounce. Says John: “In the world of cybersecurity, there are no such things as guarantees. But adding new layers of protection such as Digital Ghost will ensure we are putting our strongest effort forward.”

Top image credit: GE’s John says the software is the industrial version of an immune system. Images credit: Getty Images

Amazon may be the largest online retailer in the world, but the company is focused on having a positive impact on the ground as well. With an ever-expanding global network of fulfillment and data centers, Amazon has a growing demand for energy. Amazon also has an equal appetite for and commitment to renewable energy. In fact, Amazon Web Services (AWS), the company’s cloud computing business, has a long-term commitment to achieve 100 percent renewable energy usage for its global infrastructure footprint.

Amazon has become a big player in the renewable energy industry. Last fall, the company announced plans for its largest wind farm yet in a blustery corner of west Texas. Jeff Bezos, Amazon’s CEO, christened the farm today.

Built by Lincoln Clean Energy, the Amazon Wind Farm Texas includes a fleet of GE wind turbines. The farm will have the capacity to generate approximately 1 million megawatt-hours of electricity annually — enough to power almost 90,000 U.S. homes. Some 90 percent of the output energy will be sold to Amazon’s fulfillment arm.

Scott Stalica, manager for commercial operations in the Americas at GE Renewable Energy points out that wind is not only good for the climate but also for the wallet. The cost of wind power is about one-third of what it was six years ago. “Wind is very competitive versus alternative forms of generation,” Stalica says.

Top GIF:Amazon CEO Jeff Bezos christened the company’s new wind farm today. Image credit: Amazon. Above: Amazon today announced that its largest wind farm yet—Amazon Wind Farm Texas—is now up and running, adding more than 1,000,000 MWh of clean energy to the grid each year. Amazon has launched 18 wind and solar projects across the U.S., with over 35 more to come. Together, these projects will generate enough clean energy to power over 330,000 homes annually. These projects also support hundreds of jobs and provide tens of millions of dollars of investment in local communities across the country. Photographed Wednesday, Oct. 18, 2017, in Snyder, Texas. Image and caption credits: Jordan Stead/Amazon)

Data published by the Energy Information Administration shows that the cost of onshore wind energy — without federal tax and other financial incentives — is projected to reach $73.60 per megawatt-hour by 2020 and dropping as turbine technologies improve. That’s slightly cheaper than conventional coal, which costs about $75.20 per megawatt-hour.

The opportunity for corporations to leverage the cost-competitive nature of renewable energy is growing. In 2015, AWS announced the construction of Amazon Solar Farm US East, Amazon Wind Farm Fowler Ridge, Amazon Wind Farm US Central and Amazon Wind Farm US East. In 2016, it announced five additional solar farms and one more wind farm, bringing the total number of such AWS projects to 10. With the addition of Amazon Wind Farm Texas, Amazon is poised to generate almost 3.6 million megawatt-hours of renewable energy by year-end 2017.

Scurry County, Texas, was selected as the site for the Amazon Wind Farm Texas because of its plentiful wind and affordable production and transmission costs. “It makes good sense to build these large wind farms where the wind resource is strong and the local residents welcome the economic boost from such projects,” says Paul Parkes, senior account manager in Wind Energy at GE, “you need a really good wind resource, and it’s got to be close to transmission lines to integrate and connect to the grid.  This project is a model for connecting those dots and deriving the optimum energy solution for Amazon.”

Predicting power demand used to be a simple science: People use more power during certain times — like the morning, when they cook breakfast and turn on their lights — and less during others, like when they hit the sack. Relying on predictable sources of electricity — like gas- and coal-fired power plants — utilities were able balance supply and demand with some fairly straightforward math based on historical records and other data.

But the steady rise of renewable energy made the power landscape infinitely more complicated. On the supply side, changes in wind or cloud cover can sharply shift the amount of power available. Demand has also become harder to nail down as more consumers manage their power use with smart thermostats and appliances like connected ACs.

At the same time, market forces demand better power forecasts. Power plants and fuel are expensive, and they don’t want to operate or buy more equipment than they may need. “In some countries, regulators are asking power generators to guarantee the quality of their forecasts,” says Olivier Cognet, CEO of Swiss-based startup Predictive Layer. “It’s no longer possible to say ‘We’ll sell you 20 turbines and see what they produce.’ It’s ‘We’ll produce x amount of energy by noon, y amount of energy in two hours and z energy in one month.”

Cognet’s company, a 2016 graduate of GE Digital’s Paris-based European Foundry startup accelerator program, is using the power of big data, machine learning and artificial intelligence to make better predictions about how much power will be generated and when. Predictive Layer starts with the basics, using a variety of consumption and production models to estimate supply and demand. But its software is designed to teach itself and fix its mistakes.

Energy forecasting may seem simple — people need more power during their waking hours and less overnight. But the rise in inherently variable power sources like wind has complicated matters. New machine-learning tools that can crunch mountains of data and project future energy output and demand can lead to more efficient and profitable outcomes for utilities. Image credit: GE Ecomagination

For example, the software incorporates data about how much power an area consumes and produces, integrating information from power plants — both fossil fuel and renewable — as well as from a host of other sources, including holiday calendars, sports schedules, weather forecasts and historical weather data. By correlating the data, the software can predict spikes and drops in usage and tie them to holidays or major sports games. The goal is to come up with the most accurate energy consumption predictions. In France, its energy usage predictions are already 0.79 percent more accurate than next-best predictions on the market.

That sounds like a miniscule fraction. But in the case of France’s energy consumption, it translates into 300 megawatts that doesn’t need to be produced. “That’s the equivalent of 300 wind turbines or a gas-fired power plant,” Cognet says.

Processing this volume of data would take an experienced mathematician a month, Cognet says; by the time they were done, the resulting energy forecast would be horrendously out of date. But with the help of Predix, GE’s software platform for the Industrial Internet, Predictive Layer can perform these calculations automatically, producing constant, self-correcting updates to its forecasts.

This isn’t to say that Predictive Layer is foolproof. While it learns from the past, it cannot predict something that has never happened before. So, when a disaster like a record-breaking storm hits, the program’s predictions suffer. But it’s able to constantly learn. As unforeseen “hundred-year storms” may become more common, this could become vital.

Ultimately, Cognet hopes, Predictive Layer will enable the industry — and all of its customers — to work with a much greater level of profitability and efficiency. “We’re not looking to disrupt the power industry,” he says. “We’re helping it to transform so it can do its job so much better.”

Scientists working at GE labs in upstate New York have spent decades building computer vision systems that can study diseased tissue, and hunt for microscopic cracks in machine parts and other features often invisible to the naked eye. “Computer vision can be used to find things we either can’t see or may not know to look for,” says Joseph Vinciquerra, who runs the Additive Research Lab at GE Global Research in Niskayuna, New York.

Now Vinciquerra and his team are using their insights to improve the way 3D printers work.

Even though companies like GE already print parts for jet engines, additive manufacturing is still a young field. It can take days to weeks to print large parts such as a compressor blade. If something goes wrong near the end of the process, precious machine time and money could go to waste.

The GE researchers are building a system that could speed up the process and eventually achieve “100 percent yield,” an engineer’s Nirvana where machines only produce good parts, beginning with the very first build. “We do a tremendous amount of work on additive powders to understand what characteristics lead to a good build,” says materials scientist Kate Gurnon, a member of the team. “We want to apply this automatically to the machines and, in real time, observe the dynamic behavior of the powder delivery to the build plate. In this way, we will have a better chance of getting to the 100 percent yield, faster.”

It can take days to weeks to print large metal parts. If something goes wrong near the end of the process, precious machine time and money could go to waste. Top and above images credits: Avio Aero

3D printing and other additive manufacturing methods print parts directly from a computer file. They can shape a component by fusing together thin layers of metal powder with a laser, for example. But even these highly-advanced machines are prone to variability. There are a number of culprits “that can make the difference between a good build and a build that has sub-optimal properties,” Vinciquerra says. They include variation in the size of the powder particles, as well as “the complex dynamic of adding new powder layers,” which can be as thin as a human hair. “We know that things happen during this re-coating process that you cannot control mechanically,” he says. “We also know that the more we reuse powder, the more opportunities exist for that powder to change and behave differently over time.”

AI and machine learning can help. “Using artificial intelligence and machine learning, we will turn 3D printers into essentially their own inspectors,” Vinciquerra says. “By eliminating the need to inspect parts after they’re completely built, we can shave days, even weeks off the entire manufacturing process and lead to a breakthrough in productivity.”

The team starts by printing simple geometric shapes like flat bars and cylinders. They use high-resolution cameras to film every layer and record streaks, pits, divots and other patterns in the powder practically invisible to humans. Next, they run the samples through a powerful CT scanner and hunt for flaws.

All of the data is stored in computer memory and a proprietary machine-learning algorithm correlates defects revealed by the scanners with powder patterns recorded on the particular layer. “The more often you do it, the smarter the system gets,” Vinciquerra says. “The computer vision alone will eventually have enough training to tell us whether we are going to have a problem.”

“Using artificial intelligence and machine learning, we will turn 3D printers into essentially their own inspectors,” says GE’s Joe Vinciquerra. Image credit: Concept Laser

But Vinciquerra and Gurnon are going deeper. They are working with other members of the team to loop the defect-spotting ability into machine controls to make the 3D printer smarter. When the computer vision spots a familiar streak that it knows will lead to cavities, for example, the printer can automatically add more power or speed to the laser beam to adjust, or change the thickness of the next layer. “The idea is that the machine has a compensation strategy based on what the computer vision sees,” Vinciquerra says. “That’s the long-term goal here.”

One way to get there is to build a “digital twin,” a virtual representation of the production process that can compare ideal conditions with reality in real time and suggest changes to reach a flawless result. Vinciquerra says that the digital twin is “sort of a recipe card” that “represents the gold standard of how the material should be processed” in the 3D printer. “It’s telling me that if I use these parameters to build a part from a certain material, I can expect this kind of behavior in the final product,” Vinciquerra says.

The next generation of the twin will be able to gather computer vision data but also collect information from other sensors monitoring the printing process, such as the shape of the tiny pool of metal rendered molten by the laser.

Vinciquerra notes that some of GE’s most advanced 3D-printed parts for GE Aviation can take more than a week to complete and require several more hours after that for processing and validation. “If we could recognize a defect very early in a part build, we would have an opportunity to stop and start over,” Vinciquerra added. “On the other hand, if a part is more than halfway through a build, we could evaluate whether the defect could be fixed by adjusting the rest of the layers being printed. We have never had this degree of flexibility in manufacturing.”

Today, GE released its third-quarter results for 2017. The company reported $0.29 earnings per share, down 9 percent compared to the third quarter in 2016. Industrial cash from operating activities was $1.7 billion and industrial operating profit fell by 7 percent, organically. Orders increased 11 percent and GE returned $10 billion to shareowners so far this year through dividends and share buybacks. While a majority of the company’s businesses performed well this quarter, the results were more than offset by a decline in Power and Oil & Gas profit.

In GE’s Power business, performance was weaker than the company expected. The Power market was tough, driving fewer outages and upgrades for our services business and fewer sales of our high margin aero derivative units. The company said it also had poor execution that resulted in project delays and cost of quality.

“Throughout our 125-year history GE has been known as a company that combines innovation and technology with execution intensity to produce outstanding results for our customers and shareowners,” said John Flannery, GE chairman and CEO. “We are focusing on redefining our culture, running our businesses better, and reducing our complexity.”

Cathay Pacific signed a $1 billion order in jet engines and services to power a fleet of 32 new Airbus A321neo aircraft with LEAP-1A engines. Image credit: Airbus

GE highlighted several large deals and important partnerships from the quarter. GE Renewable Energy won a contract to supply America’s largest wind farm, Invenergy’s Windcatcher project in Oklahoma, with 800 GE turbines using the company’s Digital Wind Farm technology. Cathay Pacific signed a $1 billion order in jet engines and services to power a fleet of 32 new Airbus A321neo aircraft with LEAP-1A engines.

GE has also been expanding its digital business, GE Digital, which grew orders more than 50 percent in the third quarter. Its most recent partnership with Apple, for example, will bring Predix, GE’s software platform for the Industrial Internet, to Apple’s iPhone smartphones and iPad tablets used by hundreds of millions of people around the world.

The company also accelerated its efforts to cut spending and boost profits, reporting $500 million in structural cost out this quarter. This brings the total to $1.2 billion year-to-date or $200 million higher than our total year plan.

GE also made progress in streamlining and simplifying its portfolio, closing transactions to sell the GE Water & Process Technology business for $3.4 billion and signing a deal to sell its Industrial Solutions unit for $2.6 billion. Earlier in July, GE also announced the completion of the combination of GE’s oil and gas business with Baker Hughes, creating the world’s first fullstream oil and gas company.

On November 13th, John Flannery will provide an update on the company and its strategy at GE’s Investor Update. The meeting will be webcast live on GE’s investor website. Sign up for our investor newsletter to learn more over the coming weeks.

Scientists in the U.K. created a Terminator-like programmable metal, their peers in London found a way for teeth to fix themselves, and spray-concrete developed in Canada can withstand even the most powerful temblor. We’ve seen some earthshaking science this week.

A Bridge To The Future

The team printed used a customized printer to lay down layers of concrete, one after another, and include steel reinforcement at the same time. Image credit: Eindhoven University of Technology.

What is it? Officials in the Netherlands opened the world’s first bridge 3D-printed from pre-stressed concrete. The bicycle bridge is 8 meters long, 3.5 meters wide, and can handle 5 tons.

Why does it matter? The team at the Eindhoven University of Technology that printed the bridge said it required “much less concrete” than bridges made the traditional way: filling a mold with concrete. Less concrete also mean less cement, the production of which generates a lot of carbon emissions. 3D printing also gives designers the freedom to create any shape they desire.

How does it work? The team printed used a customized printer to lay down layers of concrete, one after another, and include steel reinforcement at the same time. “When laying a strip of concrete the concrete printer adds a steel cable so that the bridge is ‘pre-stressed’ so that no tensile stress can occur in the concrete, because this is something that concrete is not able to cope with adequately,” the university said.

Terminator 2D

What is it? Scientists at the University of Sussex and Swansea University have developed a new liquid metal they can manipulate, Terminator-style, with electrical current to form two-dimensional shapes and letters. “While the invention might bring to mind the film Terminator 2, in which the title character morphs out of a pool of liquid metal, the creation of 3D shapes is still some way off,” the university cautioned. “More immediate applications could include reprogrammable circuit boards and conductive ink.”

Why does it matter?“The team says the findings represent an ‘extremely promising’ new class of materials that can be programmed to seamlessly change shape,” according to the University of Sussex. “This opens up new possibilities in ‘soft robotics’ and shape-changing displays.”

How does it work? The team used electric fields programmed by a computer to shape the material. “One of the long-term visions of us and many other researchers is to change the physical shape, appearance and functionality of any object through digital control to create intelligent, dexterous and useful objects that exceed the functionality of any current display or robot,” said University of Sussex professor Sriram Subramanian.

Shaking Off Earthquakes

What is it? Researchers at the University of British Columbia have developed a spray-on, earthquake-resistant concrete and exposed it to simulated temblors “as high as the magnitude 9.0–9.1 earthquake that struck Tohoku, Japan in 2011.” It survived.

Why does it matter? Walls covered with layers of the material just 10 millimeters thick withstood “Tohoku-level quakes and other types and intensities of earthquakes,” said Salman Soleimani-Dashtaki, a Ph.D. candidate in the department of civil engineering at the university. “We couldn’t break them,” he added. The team plans to use it to “retrofit a school in Roorkee in Uttarakhand, a highly seismic area in northern India,” according to the university.

How does it work? The composite material is similar to steel and “engineered at the molecular scale to be strong, malleable, and ductile.” It combines “cement with polymer-based fibers, fly ash and other industrial additives, making it highly sustainable,” said Nemy Banthia, a civil engineering professor who supervised the work. The team said that instead of fracturing, the material bends during an earthquake.

Smart Skin

A technique called Hybrid 3-D printing, developed by Air Force Research Laboratory researchers in collaboration with the Wyss Institute at Harvard University, uses additive manufacturing to integrate soft, conductive inks with material substrates to create stretchable electronic devices. A potential application is to create sensors to enable better human performance monitoring. Caption and image credit: Harvard Wyss Institute.

What is it? Researchers working at Harvard’s Wyss Institute and Air Force Research Laboratory (AFRL) used “soft, conductive inks” to 3D print wearable electronics that could be used for skin sensors monitoring human performance and other devices.

Why does it matter? Dan Berrigan, a research scientist at the AFRL Materials and Manufacturing Directorate, said that “skin-worn electronics have the potential to provide feedback on movement, body temperature, fatigue, hydration and other metrics crucial to understanding” performance. When the team printed sensors on a stretchable sleeve, it was “able to respond to the movement of the wearer’s arm.

How does it work? Berrigan said that team used a 3D printer to trace out the sensor from “flexible, silver-infused polyurethane” and inserted microcontroller chips and LED lights into the material. The devices “were able to maintain function even after being stretched by more than 30 percent from original size,” AFRL reported.

Pulp Nonfiction

“The novel, biological approach could see teeth use their natural ability to repair large cavities rather than using cements or fillings,” the King’s University reported. Top and above images credit: Getty Images.

What is it? A team at King’s College London discovered that an experimental drug used to treat Alzheimer’s disease can stimulate stem cells in “tooth pulp” to fix teeth sans the drill.

Why does matter?“The novel, biological approach could see teeth use their natural ability to repair large cavities rather than using cements or fillings,” the university reported. Need we say more?

How does it work? The team infused a commercially available collagen sponge with low doses of the drug and applied it to the tooth. They observed that “the sponge degraded over time” and “new dentine replaced it, leading to complete, natural repair.” Dentine is the hard tissue under a layer of enamel that makes up most of the tooth. “The simplicity of our approach makes it ideal as a clinical dental product for the natural treatment of large cavities, providing both pulp protection and restoring dentine.”

Justin Eggart and fellow engineers working inside GE Power’s Monitoring and Diagnostics Center in Atlanta were halfway through their shift a few months ago when they noticed something strange. The center, the largest of its kind in the world, looks a lot like a smaller version of NASA’s mission control center. It has banks of computers and a wall-to-wall, colorful LED screen flashing real-time operating conditions inside 5,000 turbines, generators and other equipment churning away at 900 power plants located in 60 countries and serving 350 million people.

Every day, 1 million sensors attached to the machines send 200 billion data points to the cloud and to computers sitting directly on the machines. Eggart and his team slice it and dice the data with sophisticated software and “digital twins” — virtual versions of the power plans — and look for anomalies. “Our algorithms can run analysis on data that to other people appears as noise,” he says. “Within that noise, we can start to see patterns that allow us to make predictions.”

That afternoon, one of the power stations tracked by the center signaled an alert, even though it seemed to operate normally. “The plant never felt it, never heard it, never saw anything,” says Eggart, the general manager for fleet management technology at GE’s Power Services unit. “But we were sure it was there.”

The GE engineers in Atlanta called the power plant operators, who remained incredulous because they didn’t see any issues on their end, and told them to take a close look at a turbine bearing during the next scheduled maintenance session coming in a few weeks. “They came back and said: ‘You know what, you were right,’” Eggart says. “The bearing wasn’t getting the right lube oil feed, and it was going to fail.”

Spotting a problem early can save a utility a lot of money. Power plants get fined $50,000 if they “trip” and abruptly disconnect from the grid in some cases. This expense is in addition to the money they’re not making while the plant is offline. The costs can spiral into millions of dollars in cases like the bum bearing, especially if operators have to dock their plants for days or weeks because they don’t have spares on hand.

The technology Eggart’s team is using is already smart enough to spot hundreds of similar problems every year. But as of this fall, it has a new brain running on Predix, the software platform GE Digital developed for the industrial internet. The brain is GE’s new Asset Performance Management (APM) software application, and it will make the center’s predictive powers even more formidable, by giving customers more advance warning of issues that might trigger an outage. The “brain” also makes it easier for GE engineers and their customers to compare notes in real time and spot problems before they happen. Customers with the software see exactly what GE’s experts see. As a result, they minimize downtime and optimize power plant performance and save utilities money. “In the past, we had to call plant operators or send them an email,” Eggart says. “Now, they can see the same data I see. It allows us to interact on our smartphones, tablets and PCs and be much more collaborative.”

Top GIF: “Our algorithms can run analysis on data that to other people appears as noise,” says GE’s Justin Eggart. “Within that noise, we can start to see patterns that allow us to make predictions.” Above: The M&D center monitors in real-time operating conditions inside 5,000 turbines, generators and other equipment churning away at 900 power plants located in 60 countries and serving 350 million people. GIF credits: GE Power.

GE started remotely monitoring power plants two decades ago and has amassed a treasure trove of unique operations data. Machines made by the company also generate a third of the world’s electricity, giving it detailed insights into how turbines and generators are built and work. This domain knowledge allows the team at the center to also monitor turbines made by Alstom, Mitsubishi, Siemens and other makers. “We believe we have more data than anybody, and we’ve seen more than anyone,” Eggart says. “We also designed a lot of the equipment and know where to look. We can tailor our algorithms right around that knowledge.”

The most powerful Predix algorithms live inside the cloud. Using information about vibrations, pressure, temperature and other factors, the software, in combination with the specific machine’s digital twin, can predict what might happen in the future and recommend the best time for maintenance or the most optimal ways to run the plant.

But another set of algorithms and digital twins lives in computers located directly on the machines in the power plant, or, as GE calls it, on the edge. “The edge tends to be focused on the here and now, and the cloud allows me to think forward,” Eggart says. “The edge is like me putting a finger on the machine and feeling the vibrations and heat right there. The cloud is the brain that helps me figure out what it all means and what I need to do.”

Still, it’s humans who ultimately divine meaning from the data and decide how to respond to it. “You’ve got your edge and your cloud running your predictive software,” Eggart says. “But they inform the people who provide the service. The relationship is collaborative, not competitive. The AI is not taking over.”

Predix can operate in large cloud environments like Microsoft Azure and Amazon Web Services. Eggart says that this “makes it easy” to grow the system to whatever size he needs. “I can scale at the push of a button,” he says.

This is handy for solutions like the APM software, which can, say, monitor a gas turbine and run diagnostics, but also optimize maintenance strategy, manage safety and environmental compliance, handle reliability, among many other functions. “All of these pieces of software build upon each other,” Eggart says. “Customers can buy a license and choose whatever level of engagement they want to have.”

Right now, the M&D Center, as GE calls it, covers only thermal power plants, meaning those that use coal or gas as fuel to generate electricity. GE also has monitoring centers for renewable energy in places like New York, as well as globally. But in the future, a similar center could cover “the entire energy value network,” Eggart says. “There’s no reason why we cannot monitor transformers, inverters, power lines, batteries and other technology standing between the power plant and the consumer,” he says. “When it comes to Predix and the cloud, the sky is the limit.”

Asking Ajith Kumar to pick his favorite patent is a little like asking a father to choose his favorite child. But in this case, Kumar has 311 children. Press him hard enough, though, and he’ll admit to liking one best: technology that powers each wheel on a locomotive separately.

Kumar calls the technology “quite simple,” but in reality it has revolutionized the freight industry. Old direct current locomotives sent the same amount of voltage to each wheel, but that meant when rails were slippery, all of the wheels had to reduce power. Kumar’s AC technology makes it possible to send more power to wheels that need it at any given time, helping new locomotives run faster and stay on the tracks without slipping.

It’s the technology, not the achievement, that really excites Kumar, a consulting engineer with GE Transportation Systems who holds more patents than any other GE employee. “I’ve worked on every new product transportation has come up with from the conceptual stage to prototype and first production,” says Kumar, 65. “I really enjoy solving problems in a slightly different way.”

Kumar has seen enormous changes in technology over the past 40 years. The son of a math professor and a school superintendent in Trivandrum, Kerala, he was always interested in electricity on the grandest of scales, from large motors and transformers to transmission lines. He received a degree in electrical engineering from the University of Kerala in India, but when he arrived at Stanford University as a graduate student in 1976, he started learning about the smaller world of engineering. “It was all micro-electronics and micro-processors, totally different,” he laughs.

Kumar melded the two worlds by becoming an expert in controlling huge machines with tiny circuits. His focused on transportation equipment including locomotives, mining vehicles, subway cars and drilling equipment.

“I’ve worked on every new product transportation has come up with from the conceptual stage to prototype and first production,” says Ajith Kumar, a consulting engineer with GE Transportation Systems who celebrated his 40th work anniversary last month. And he’s got the patents to prove it — 311 of them, to be exact. Images credit: GE Transportation.

After graduating from Stanford, he considered going back to India, but decided to take a chance and try for a job at GE. “I wrote a letter telling them I’m interested in working in high power and its control,” he says. “I just asked, ‘Do you have a position?’ ”

In response he received a telegram from Erie, Pennsylvania, that said, “Please call me collect.” He had to look Erie up on a map. “I didn’t know where Pennsylvania was, but they said come for an interview, so I went,” Kumar says. There was a telegram with a job offer waiting for him when he arrived back at his dormitory.

Kumar still lives in Erie, where he works on developing new products. He married his wife, Meera, in 1982, and has two daughters and two grandchildren. When he’s not working, Kumar loves to travel and spend time with his family and friends. He’s still collecting patents. He was awarded his most recent patent just last month for a GPS-based enhancement to the axles that decreases slipping and increases locomotives’ pulling power.

Having marked his 40^th work anniversary in September, Kumar is considering retirement but not quite yet. He’s still enjoying himself way too much.

“When there’s no more interesting work,” says Kumar, “that’s when I’m going to leave.”

Kumar holds more patents than any other GE employee, and he’s still racking them up, having received one just last month for a GPS-based locomotive axle enhancement. “I really enjoy solving problems in a slightly different way,” he says. Image credit: GE Transportation.

The California duck sounds like a dish straight from the state’s famously progressive kitchens. But you can’t order it at any restaurant — nor would you want to.

The evocative name refers to the strange shape of California’s energy demand curve caused by the ever-expanding renewable energy menu. The curve sags gently like a saddle during the day, when plentiful solar panels provide much of California’s electricity. But it spikes sharply like an angry mallard’s neck when the sun sets. That’s when the state’s fossil fuel power plants kick into high gear and rapidly increase load to keep the lights on.

These gas- and coal-fired plants will remain a fixture in the state’s landscape for now, even though Californians keep bolting more solar panels to their roofs and erecting wind farms in the countryside to meet the goal of receiving half of the state’s electricity from renewables by 2030. “It’s a great paradox,” says Justin John, a controls engineer at GE Global Research. “The more renewables you have, the less stable the grid becomes because the wind and solar farms depend on the weather. You need conventional power plants to be able to produce more megawatts very, very quickly to meet customer demand.”

But rapid starts and stops take a heavy toll on the legacy power plants. “Every time you peak fire a power plant, you are running the turbine inside hotter than it would normally operate, and consuming a lot of its life,” John says. “If you do it too often, you will have to shut it down months or a year earlier than planned to overhaul the equipment, and lose a lot of revenue.”

But software is lighting the way out. A GE app called Dispatch Optimizer allows power plant operators to monitor what’s happening on the grid and inside their power plant, optimize operations and release the right amount of energy at the best time and in the most profitable way. “The software helps us solve some of the big energy questions, like: How do we bring in more renewables, protect existing power plants and keep the grid stable?” says John, who developed the app with his colleagues working at the research center and at GE’s Digital and Power businesses.

“It’s a great paradox,” says Justin John, a controls engineer at GE Global Research. “The more renewables you have, the less stable the grid becomes because the wind and solar farms depend on the weather.” But now there’s an app for that. Top image credit: Getty Images. Above: GE Power.

The app, which runs on Predix Edge, GE’s software for the industrial internet, gives customers like NRG Energy and PSEG in the U.S., and E.ON and A2A in Europe, the ability to crank up the gas turbines poweing their power plants and “peak fire” when demand and electricity prices are high. But it also allows them to offset the wear and tear caused by the power generation spike by running the turbines cooler when conditions are right and demand drops. “We are modeling how much life we are consuming when you peak fire and balancing it with the opportunity to run cooler, which is less efficient but it saves life and essentially banks megawatts you can use at another time,” John says.

The modeling takes place inside computers located directly on the machines in the power plant — or, as GE calls it, “on the edge.” The engineers built a virtual replica of each machine, its “digital twin.” The twin collects data about the ambient temperature and conditions inside the turbine and supplements it with information from the cloud about energy demand and prices, fuel cost, and the weather. “The digital twin is a personalized model of an asset,” John says. “It tracks that asset over time, so as the power plant degrades, the digital twin will follow and give you a very realistic prediction of how that asset will operate.”

John says that utilities as well as energy traders, who can work with power plants to get direct access to the app, can use the Dispatch Optimizer not only to compensate for renewables but also to respond to the energy market and take advantage of spikes in energy prices. “We are giving them a way to peak fire when the price of electricity is high without destroying their hardware,” John says.

John says that the app’s purpose is to allow utilities and energy traders to make more money from a power plant without buying new machines. How much more money? He says the app could bring an 800-megawatt power plant an additional $1.5 million in additional annual revenue. “Just using software and digital controls, I know that if I spend additional $400,000 on natural gas, I can bank $1.1 million in profit,” John says. “It’s really just advanced math, a giant optimization problem. We’re mapping out all the possibilities into a function and smartly using it to figure out what the quickest optimum solution is at any given point in time.”

The band Lynyrd Skynyrd may implore fans to stop lusting “for the rich man’s gold,” but there’s no way industry will listen.

Demand for platinum, also known as the rich man’s gold, has been growing because of a long list of evolving industrial applications, including computer memory chips, dental crowns, defibrillators, catalytic converters for cars and even wedding bands. The metal is so rare that miners and smelters literally move mountains to extract only a few hundred tons of the metal out of the earth’s crust every year. Following an expensive and time-consuming process, it takes them half a year and around 12 tons of ore to produce just a single troy ounce, or 31.1 grams, of platinum worth around $1,100. No wonder producers like Lonmin platinum-mining company in South Africa, where 70 percent of the world’s platinum is produced, are looking for an upgrade.

Percy French, operations manager at Lonmin, is betting on a digital solution. A decade ago, he began using a smelter software application from GE’s Digital Mine suite to help make his operation more efficient. By 2016 the software had helped him significantly increase throughput at Lonmin.

Based on this early success, French upgraded his systems to include a new application that allows him to track plant performance and key performance indicators and also automate operations. The app, called Operations Performance Management (OPM), uses real-time and historical data along with advanced analytics to help Lonmin make better-informed operational decisions and help the plant troubleshoot and prevent issues with its assets. So far, the app has reduced chemical waste at Lonmin by 3 percent and has led to a 10 percent improvement in throughput.

Lonmin platinum-mining company in South Africa has been using GE software for a decade to boost its efficiency. Now, it’s adding a new app, called Operations Performance Management, which uses real-time and historical data to help Lonmin make better-informed operational decisions and help troubleshoot and prevent issues with its assets. Images credit: GE Digital.

French, who has been working in the industry for 20 years, concedes that “operators in the mining environment” aren’t typically drawn to using sensors, software and robots. But he says that metals miners have yet to appreciate the full impact of software and big data that has lifted other industries. “It’s exciting to be in this world now,” he says.

The Digital Mine software system gathers data from thousands of sensors throughout Lonmin’s mining complex, which includes a smelter plus a slag plant for removing waste. It analyzes the data to help operators make better decisions.

The software oversees an incredibly complex process: mining the ore, crushing it into dust, then blasting it with heat in a furnace at more than 1,500 degrees Celsius. This dust is then churned in something that resembles a giant cake mixer, blended with a host of other chemicals used for extraction, like copper, and transferred to an electric smelter to eventually yield a shiny, silvery trickle of platinum.

One part of the software, the “advanced controller,” acts as a kind of brain for the plant. It monitors and controls its various components, and then provides French with a complete and holistic performance report each morning. For instance, he will receive notice if one of his furnaces appears to be malfunctioning. The advanced controller also has the ability to adjust metrics like furnace temperature and makes quick decisions based on its own algorithms. “It replaces a human being for certain activities,” French says.

French says that the software has helped him better manage the smelter’s slag, the stony waste that gets separated from metals during the refining process. Calculating the right mix of crushed ore, chemicals and water can be an inexact science. At times, as much as 40 percent of what ends up as slag could be used in the metallurgical process. “If the plant doesn’t perform efficiently, we have lots of chemical waste,” French says.

The new OPM system helps French reduce chemical waste by enabling his operators to make those calculations more accurately. Elsewhere at his plant, the software has been used to help reduce bottlenecks in production — by around 2 percent — by monitoring the plant’s controllers and better anticipating downtime.

Now he’s looking at expanding the Digital Mine software to other parts of his plant, like the fan systems. “We will be implementing quite a lot of smart instrumentation and equipment on our machines in 2018,” he says.

GE and Microsoft announced today that starting Nov. 30, North American customers and developers using Predix, GE’s application development platform for the Industrial Internet, will be able to build powerful industrial apps on Microsoft Azure, the cloud for enterprises. The Predix-Azure combination will expand to additional markets next year.

John Flannery, GE chairman and CEO, and Satya Nadella, Microsoft CEO, made the announcement at Minds + Machines, GE’s flagship industrial software conference taking place this week in San Francisco.

“It’s really two market leaders coming together to accelerate the adoption on the Industrial Internet of Things,” says Kevin Ichhpurani, GE Digital’s executive vice president in charge of ecosystem and channels. “It’s one of the biggest value drivers for customers.”

Experts estimate productivity gains from connecting jet engines, gas turbines and locomotives to the Industrial Internet of Things and using it to make them work better will add $10 trillion to $15 trillion to global GDP — the size of the U.S. economy today — in coming years. “We are bending the productivity curve … [for industrial customers] looking to digitize their products, be it a jet engine or an elevator,” says Kevin Dallas, Microsoft’s corporate vice president of business development, Intelligent Cloud. He says that the notion of shipping a machine and not being able to communicate with it and gain insight into how it’s being used “is a thing of the past.”

Dallas says that insights delivered by Predix apps built on Azure will allow users to transform products, optimize operations, empower employees and improve communications with customers.

Ichhpurani says that Predix developers will benefit from a network of Azure regions sprinkled all over the globe. He says that customers can use them to get “instant access,” work with real-time data and build apps without switching between different platforms.

Ichhpurani says that customers have been calling for closer integration with Azure since GE first announced its partnership with Microsoft last year. He says that many companies using Predix are already storing data and running enterprise software from Oracle, SAP and other providers on Azure. “It’s now sitting in the same cloud,” he says. Dallas says that the solution has “the right connectors that allow you to communicate seamlessly with [Microsoft] Office … as well as existing business applications that may use SAP,” for example.

But Dallas says the collaboration between GE and Microsoft extends beyond apps, products and efficient data integration. “This is a very unique element of this partnership,” he says. “Many [GE] customers in oil and gas, transportation, energy and healthcare are Microsoft customers. The intent is to go to market together.”

Scandinavian power company Fortum is the top producer of certified renewable electricity in Finland and Sweden. Much of it comes from 169 hydroelectric plants, some more than a century old, that use fast-flowing water to spin turbines and generate power. How do you make sure that something built during the flapper era remains reliable and up to snuff?

Enter data. Digitizing the century-old plants could give the utility new insights, help it predict problems, improve maintenance and generally pull the plants into the 21st century. It also could help keep prices down, says Check Haris, digital sales leader at GE Renewable Energy.

But in order to bring technology to its plants, Fortum had to first find a partner that understood both big hydroturbines and big data. With that in mind, the utility invited GE to examine data from an actual malfunctioning hydroelectric turbine — including information about vibrations and temperature, output and efficiency.

“We found the issue, which was a vibration that happens when you change from a low load to a high load,” Haris says. “We suggested that they use another type of runner, or turbine blade. They hadn’t considered that solution.”

Based on that, Fortum decided to test out GE digital software at two of its plants in Sweden and Finland. In September, GE installed its suite of digital hydro software on one unit at each of the two plants, where it will run for six months for a pilot trial. It collects data on metrics like vibration, temperature and output, and uploads it to the cloud, where Predix — GE’s platform for the Industrial Internet — organizes and analyzes it. The software monitors the health of the equipment, looks out for problems and uses the insights it gains to recommend the best time for maintenance.

GE’s digital hydro software collects hydropower plant data on metrics like vibration, temperature and output, and uploads it to the cloud, where Predix — GE’s platform for the Industrial Internet — organizes and analyzes it. Image credit: GE Renewable Energy

GE also will install edge analytics at Fortum’s 127 megawatt Höljes station in Sweden later this year and use the data it collects to create predictive models of the power plant.

Edge analytics complement data analysis that happens at the cloud level by acting as a gateway through which machines, like turbines and engines, can connect to the cloud to create a computing continuum from the machine all the way to the cloud.

The edge capacity will allow operators to learn and adjust based on their own experiences. So, for example, by analyzing constant feedback about the health of different parts at the hydro plant, they will be able to move the plant from a calendar-based maintenance schedule to a more flexible scenario where equipment can get taken out of commission and repaired at times that are convenient, rather than when it breaks down. This will help reduce down time at the plant, saving money and allowing for more consistent energy production.

The cloud-based aspect of the new software pairs well with the edge analytics by also incorporating data from other sources, such as other machines, weather forecasts and market conditions, to help operators run the plant at peak efficiency.

The addition of edge analytics should reduce maintenance costs by 10 percent and increase plant availability by 1 percent, bringing Fortum closer to its goal of completely reliable, low-cost hydropower.

GE estimates that the edge and the cloud together can increase revenues by 3 percent. “The energy market is changing drastically,” Haris says. “This will help Fortum rise to that challenge.”

The scene plays out on Oct. 15 at New York’s LaGuardia Airport, dull, annoying and all too routine. A gate agent announces the flight to St. Louis will be delayed. The crew has to summon a new plane because of a failed part. The passengers groan resignedly. Finally, 90 minutes later, the departure.

More than 60 percent of frequent flyers cite delays among the things about air travel that they find most dismaying. And the bill for such delays? For passengers, the costs are spread around — an extra $25 in parking here, a missed business meeting there. Carriers, meanwhile, pay an estimated $62 per minute in crew, fuel, maintenance and other costs. It adds up. The Federal Aviation Administration and the research group Nextor calculated that such delays cost U.S. passengers and airlines tens of billions of dollars last year.

Most of those costs and all of the annoyance for the passengers on that flight from LaGuardia could have been avoided if the airline had been able to predict that the part was going to fail and prevent it from happening, says Karen Thomas of Teradata, a data and analytics company. By combining flight analytics and sensor data from engines with customer data, airlines can better manage flight disruptions, increase operational efficiencies and improve customer experiences, she says.

Teradata has entered a strategic partnership with GE Aviation using its asset performance management and operations data to analyze thousands of terabytes of data in real time to help airlines fly safer, protect the environment and provide a better passenger experience.

Commercial aviation today accumulates vast lakes of data each year, around 15 billion terabytes — a billion times the size of the Library of Congress. (One terabyte of data can hold 200,000 songs or 500 hours of movies.) Being able to fish out that data will open up untold avenues for problem solving.

A pair GEnx jet engines powering a Boeing 787 Dreamliner (top image) generate 1 terabyte of data per day. GIF credit: GE Reports. Top image credit: Adam Senatori for GE Reports.

Predictive maintenance is just one solution that will be available to airlines when Teradata combines its consumer and supplier analytics with GE’s data from 320 million flight hours, Thomas says. “Full flight data hasn’t been connected to customer data,” she says. “Now it is, and that can be a game changer for the aviation industry.”

The melded analytics will enable airlines to zero in on specific issues. In the past, data from GE’s Predix platform for the Industrial Internet might identify a particular wing part that failed more often than expected. The solution would be to examine every plane until all the bad parts could be found and replaced. With merged data, it will be possible to determine which supplier sold the failed parts, which planes had them and what date they were installed.

“It might turn out a supplier had a bad lot, so you only need to check the 24 planes with parts delivered on that specific day to that specific location from that particular supplier,” says Andrew Coleman, chief commercial officer for GE Aviation’s Digital Solutions business.

The partnership has benefits for long-term matters such as safety or environmental initiatives because it will make solving problems easier by crunching enormous amounts of data quickly. Coleman says problems that might have required months or years to solve now will potentially take hours or even minutes.

In addition to accessing data from Predix apps such as FlightPulse, which connects pilots to various flight metrics when they land, airlines will be able to build custom apps.

“Beyond taking the high bar of safety within aviation even higher, Qantas has already saved 8 million gallons of fuel using FlightPulse,” Coleman says. “Those two facts alone make us incredibly proud. Airlines are going to create ROI from this integrated level of insight that far exceeds our goals.”

Will more flights from LaGuardia take off on time? That’s up in the air, but if they don’t, GE and Teradata will know all about it, and so will GE Aviation’s customers.

The huge Chicago-based energy company Exelon generates enough electricity to supply millions of customers in 48 states and parts of Canada. Its wind and solar farms, hydroelectric plants and nuclear power stations also pump out a lot of valuable data. In 2015, the company started gathering information about wind speeds, swings in consumer demand, the purpose and frequency of repair crew trips, and other valuable details. It pooled this data in the cloud and started trawling it for insights to make its power plants smarter.

Exelon is now getting a bigger net. The power company’s utilities division just signed a deal with GE Power to sift the data with Predix, GE’s software platform for the Industrial Internet. “Predix is going to dip into the data lake and make the most use of it by pulling out the most helpful data,” says Andy Gay, the Exelon program manager for GE Power.

A good place to start is with reducing the cost of maintenance throughout the power grid. Predix can evaluate historical information and current performance to recommend when parts need to be fixed or replaced. By only taking equipment out of commission when it needs work, instead of on a regular maintenance schedule, Exelon can avoid costly downtime and reduce maintenance costs. Starting in 2019, the Predix system will be able to make recommendations about the millions of devices — transformers and circuit breakers, for example — throughout the grid.

Chicago-based energy company Exelon generates enough electricity to supply millions of customers in 48 states and parts of Canada. Its assets also pump out tons of valuable data. The company just signed a deal with GE Power to use GE’s Predix software solutions to crunch that data, helping it reduce downtime due to maintenance, better prepare for storms, and keep the grid humming when renewable energy sources like solar and wind power waver. Above image credit: Getty Images.

Using proprietary algorithms, Predix also will allow Exelon to better prepare for storms and other natural disasters that lead to power outages. Using data from previous storms, such as wind speeds, information about trees and other vegetation in the area, and maintenance records, Predix can identify probable trouble spots and what will be needed to bring those areas online again. The idea is that customers will get their electricity back faster. “Instead of waiting to see where the outages are, they’ll be able to get crews and equipment in place before a storm hits,” Gay says.

Predix also will help sustain optimal output as more renewable energy is added to the grid. Energy grids need to maintain a delicate balance of supply and demand or risk shutting down. Renewables make it especially hard to keep that balance because the wind doesn’t always blow and the sun doesn’t always shine, making supply uncertain. The system will help the utility to predict demand and also run in the most optimal way the gas-fired power plants that must pick up the slack when renewables falter.

The seven-year program will start by looking at five major categories: network connectivity, asset health, outage prediction, storm response and outage history. Exelon has the opportunity to add 13 other electricity grid analytics over time. “At the beginning, there’s going to be a massive training push,” Gay says. “But once they get used to the system, they’re going to be able to develop their own (algorithms) to perform tasks that haven’t been thought of yet.”

Scientists have genetically engineered skinny pigs that are more tolerant to cold, ocean mussels could lead to self-healing plastic, and transparent solar panels are soaking up the sun. It’s been a bright week for science.

Clearing The Way For More Solar Power

What is it? Michigan State University scientists have developed a transparent solar panel that can be used as a window.

Why does it matter? Clear solar panels could be used to tap the sun’s power in buildings, cars and even tech devices. There are 5 to 7 billion square meters of glass surfaces in the United States, according to the researchers, who say these clear panels have the potential to provide approximately 40 percent of the country’s current energy demands. Besides making new power-generating window panels, the technology could be also used to retrofit existing windows.

How does it work? The MSU team used organic molecules to create a thin material similar to plastic that captures the sun’s ultraviolet and near-infrared light and moves to the edge of the window panel, where a solar cell converts it to energy. “Highly transparent solar cells represent the wave of the future for new solar applications,” said lead engineering researcher Richard Lunt. While the transparent panels are far less efficient than normal solar panels, buildings have a lot more surface area where they could be deployed. “Ultimately, this technology offers a promising route to inexpensive, widespread solar adoption on small and large surfaces that were previously inaccessible,” Lunt said.

Welcome To The Neighborhood

Top image: The Pan-STARRS1 Observatory on Halealakala, Maui, opens at sunset to begin a night of mapping the sky. Image and caption credit: Institute of Astronomy the University of Hawaii. Photo by Rob Ratkowski. Above: Animation showing the path of A/2017 U1 through the solar system. Image and caption credit: NASA/JPL.

What is it? Astronomers are marveling over the discovery of a small rock hurtling through space that they say came from outside our solar system.

Why does it matter? Although astronomers had predicted such a visitation, this is the first time they have recorded one. Now they’re scrambling to amass information about the object while they can. They’d better hustle: It’s swung past the sun and is already zooming away at about 25 miles per second.

How does it work? Rob Weryk, an astronomer at the University of Hawaii Institute for Astronomy, discovered the object while reviewing images from the university’s Pan-STARRS 1 telescope on Maui. What gave it away as an interstellar interloper: its unusual speed and trajectory. “It’s moving so fast that the sun can’t capture it into an orbit,” Weryk said. It also was apparent to astronomers that this object has a “hyperbolic orbit” rather than the elliptical orbits seen in our solar system.

These Pigs Need No Blankets

The scientists hope to prevent “millions of piglets” from perishing each year because of cold weather and also save farmers money in heating and feeding bills. Image credit: Getty Images.

What is it? Chinese scientists have genetically engineered pigs with a gene that allows them to stay warm by burning fat, rendering them 24 percent leaner than their peers.

Why does it matter? The scientists hope to prevent “millions of piglets” from perishing each year because of cold weather and also save farmers money in heating and feeding bills. As an added bonus, “People like to eat the pork with less fat but higher lean meat,” said lead researcher Jianguo Zhao of the Institute of Zoology at the Chinese Academy of Sciences in Beijing.

How does it work? Most mammals have a gene called UCP1, which helps regulate body temperature. Pigs, however, are missing this gene, so the scientists used a gene-editing tool called CRISPR-Cas9 to insert mouse UCP1 into pig DNA. From these modified cells, the scientist created cloned pig embryos, which eventually emerged as 12 leaner but otherwise normal piglets. The hardest work, however, might be convincing people to eat genetically modified bacon: “I very much doubt that this particular pig will ever be imported into the USA — one thing — and secondly, whether it would ever be allowed to enter the food chain,” the research paper editor, R. Michael Roberts, a professor in the department of animal sciences at the University of Missouri told NPR.

Ocean Mussels Inspire A New Type of Plastic

New plastics made from this polymer could be “tough enough to glue together disparate materials such as wood and metal, and even able to heal themselves when damaged,” according to Science magazine. Image credit: Getty Images.

What is it: Researchers have developed a stretchy, strong polymer that is similar to the flexible material saltwater mussels use to cling to the ocean’s rocks. New plastics made from this polymer could be “tough enough to glue together disparate materials such as wood and metal, and even able to heal themselves when damaged,” according to Science magazine.

Why does it matter? There are a lot of polymer materials out there that are stretchy and springy: wetsuit fabric, tire rubber and silicone. The problem is that scientists have never been able to make these materials sturdier because they become brittle when you add more polymer strands to the chemical makeup. A tough, flexible synthetic polymer (plastic or resin) would be a welcome ingredient in biomaterials, like artificial tendons and robotic joints.

How does it work? After studying mussels’ chemical makeup, researchers at the University of California, Santa Barbara added iron ions to synthetic polymer bonds. They were able to mimic the mussels’ strong clinginess and self-healing properties, even out of the water. “We found that the wet network was 25 times less stiff and broke at five times shorter elongation than a similarly constructed dry network,” explained co-lead author Emmanouela Filippidi. “That’s an interesting result, but an expected one. What’s really striking is what happened when we compared the dry network before and after adding iron. Not only did it maintain its stretchiness but it also became 800 times stiffer and 100 times tougher in the presence of these reconfigurable iron-catechol bonds. That was unexpected.”

A Shortcut For Reprogramming Cells

“This work also has important implications for regenerative medicine and tissue engineering, since it provides a blueprint for generating any desired cell type,” explained stem cell biologist Max Wicha. Image credit: Getty Images.

What is it? Using a mathematical algorithm, University of Michigan scientists may have found a new way to directly reprogram ordinary cells to become whatever type of cell they wish, just like stem cells.

Why does it matter? This would be a faster way to create specialized cells on demand as well as potentially enable the reprogramming of cells to fight cancer or genetic diseases. “This work also has important implications for regenerative medicine and tissue engineering, since it provides a blueprint for generating any desired cell type,” explained stem cell biologist Max Wicha.

How does it work? Right now, the only way to reprogram adult cells is by using a lengthy process that involves coaxing skin or blood cells into an embryonic-like state, and then reprogramming these cells, called induced pluripotent stem cells, into new cells for therapeutic purposes. The Michigan researchers’ algorithm helps detects patterns in 3D genome representations and can predict when it is the right time to inject a specific cell with a protein that assists with the reprogramming. The team is now looking to move its theoretical work into the lab.

Ask industry leaders about the Industrial Internet of Things (IIoT) and they’ll tell you it will revolutionize business. But ask them what they’re doing to prepare for that, and they’ll acknowledge their organizations don’t have a strong plan in place.

That’s the feedback GE Digital received from a survey of 250 IT and operations executives across five key industries — manufacturing, utilities, power and energy, transportation, and aviation and aerospace. While the Internet of Things connects consumer goods such as televisions, doorbells and cars, the IIoT collects and analyzes data from machines and factories. “The industrial proposition is entirely unique and often daunting,” says Bill Ruh, CEO of GE Digital.

The survey, which GE commissioned ahead of this year’s Minds + Machines, the company’s digital conference taking place this week in San Francisco, found a gap between optimism and readiness for the IIoT.

The survey found that 80 percent of respondents believe the IIoT will transform their companies and industries, and 86 percent say digital transformation is important to maintain competitiveness. The optimism is easy to explain. Experts estimate productivity gains from the IIoT will add $10 trillion to $15 trillion to global GDP — in coming years.

But at the same time, only 8 percent of respondents say their business has fully made the leap to digital, and only 41 percent say their companies are working on updating their businesses with IIoT-ready solutions. Most respondents seem slow to act when it comes to initial digital transformation because they believe it may take up to eight years before their industry realizes the potential of the Industrial Internet. They also say they believe that there will be an ongoing evolution across all industries.

A survey of 250 IT and operations executives across five key industries reveals that the majority of business leaders believe digital transformation is key to staying competitive. But they also cite roadblocks to such a transformation, including skills and knowledge gaps in the workforce. Top gif credit: GE Digital. Above: Lonmin.

Ruh has a greater sense of urgency. “We need to get there faster because it matters to the world,” he says. “It is about entirely new ways to power the world, heal the sick, build our economy and transport people and goods safely and efficiently.”

What’s holding these companies back? According to the survey, the leading barrier to digital transformation — cost — was the highest concern among transportation executives (54 percent) and the lowest among respondents from the manufacturing world, where 34 percent of respondents still ranked it as their top concern. Others flagged return on investment as a high-ranking concern

The survey also sheds light on the gap between workforce readiness and IIoT business needs. Among the top skills respondents believe are necessary but lacking in the current workforce are expertise in using digital interfaces and processes (59 percent); understanding of AI and machine learning (48 percent); and ability to read technical data (48 percent).

GE is helping customers tackle these concerns by showing them how the IIoT can improve the way they do business. For example, working with Australian airline Qantas, GE tapped the power of Predix — the company’s platform for the Industrial Internet — to process more than 10 billion data points covering everything from average engine speeds to maintenance records for individual planes to help the airline become more efficient.

The resulting app, dubbed FlightPulse, gives pilots insight into their own flight data, and alerts them to opportunities where they can conserve fuel and thus reduce carbon emissions. Pilots can also use the app to compare themselves to their peers. This visibility gives pilots real-time feedback to change behavior and improve metrics. The app has helped Qantas nearly double its fuel savings compared to a year ago.

At the Port of Los Angeles, the nation’s biggest, GE is helping operators use data to reduce bottlenecks and get cargo moving more quickly. Previously the port was only able to tell what cargo was arriving in the next two days, making it difficult to have the right equipment, crews and transportation for distribution in place. By pooling data coming from several different databases and presenting that information in real time, GE was able to provide visibility up to two weeks before a ship arrives.

Expect to see more of this in the future as digital technology transforms the way everything in industry operates, finding hidden efficiencies that save money and reduce emissions. “The industrial company of the future will build machines that have the capacity to sense, predict, and respond — with greater speed and insights than ever before,” Ruh says. “A few years ago, the notion of a digitized industrial company was just an idea — with no precedent or playbook. Today, it is a reality.”

When Hong Kong started planning a road tunnel 50 meters (164 feet) below sea level in 2012, local engineers had to find a way to keep the cutters in the massive boring shield in shape and the blades sharp enough to cut stone. Workers would squeeze between the shield, which is 17 meters in diameter, and the living rock to inspect the business end of the machine — a tight spot the Hong Kong team wanted to avoid as much as possible.

The founders of OC Robotics, a U.K.-based builder of “snake arm” robots, thought they could help. They suggested replacing the human inspectors entirely with OC’s innovative machines that can thread their 6-foot-long mechanical limbs into tight spots.

Today, an OC robot not only inspects the shield but also cleans it with a high-pressure water jet and measures the sharpness of the cutting surface with a laser. “This is faster and easier, and it keeps people safe,” says Andrew Graham, OC Robotics co-founder.

The robot’s dexterity and skills so impressed engineers from GE Aviation that they acquired OC Robotics last week. The company believes snake-arm robots will be useful for jet engine maintenance, allowing workers to do as much work with the engine still on the wing as possible. That’s because removing an engine not only takes time, but also could take a plane out of service for weeks, impacting an airline’s bottom line.

Top: OC Robotics designs “snake arm” robots that can inspect areas that are hard for humans to reach. Above: The machines also can clean and cut surfaces in locations as varied as underground tunnels and nuclear facilities — with human operators controlling them from more comfortable environs. Images credit: OC Robotics.

Other GE businesses also could use the robots — to inspect power plants and trains, for example, or even for uses in healthcare. “Aviation applications will just be the starting point for this incredible technology,” says Lance Herrington, a leader at GE Aviation Services.

OC’s Graham developed an interest in robotics while working on his master’s degree in mechanical engineering. He developed a primitive control system for snake-arm robots for his thesis. “It was the most interesting-looking project on the notice board,” he laughs. “I’d never done anything like that, and it was pretty cool.” So far, Graham has 11 patents relating to snake-arm robotics.

Behold: “LaserSnake,” which packs a 5kw laser cutter that can chew through 1.5-inch-thick steel. Image credit: OC Robotics.

He co-founded OC Robotics in Bristol, U.K., in 1997 with a college friend.

Although it wasn’t the first company to design a snake-arm robot, their robot could support itself. Most similar robots are crawling or swimming snakes that rely on the ground or buoyancy to move around.

OC Robotics’ snake-arm robots “live” in a cigar-tube-shaped garage. They use a 10-pound motor to move interchangeable arms that can be as long as 14 feet.

The machines aren’t afraid of any jobs. Last year Craig Wilson, the company’s managing director, led the deployment of “LaserSnake” — an integrated snake-arm robot and 5kw laser cutter — to successfully disassemble parts of a nuclear fuel processing facility in the U.K. LaserSnake cut a 5-ton, 1.5-inch-thick stainless steel tank into 40-pound pieces. It took only four weeks to do what would have taken human workers, each wearing single-use $2,500 protective suits, years to complete. The team won a prestigious award from the U.K.’s Nuclear Decommissioning Authority for their innovation and technology.

GE Aviation expects the snake-arm robots to help maintenance crews do more of the work with the engines still on the plane, limiting costly downtime for airlines. Image credit: OC Robotics.

Silicon Valley is famous for developing products in sprints, failing fast and trying again — a cycle that, superficially at least, bears little resemblance to the painstaking, multiyear process of building industrial engines.

Yet, when Eric Ries, an entrepreneur and author, first visited GE in 2012, he envisioned possibilities for how the company could apply the Silicon Valley playbook to the development of a new “flexible” diesel and natural gas engine, called the Series X, which could be used to generate electricity as well as drive a locomotive. The idea was to make the engineers think more like they were working for a startup.

In his newest book, The Startup Way, Ries describes how he started working with GE and encouraged the engineers on the Series X development team to figure out whether customers would want the engine before GE spent hundreds of millions of dollars and five years on production.

In his words, he shifted the conversation from “can this product be built?” to “should this product be built?” It was the beginning of GE’s creation of FastWorks, a process designed to get products out fast, learn and iterate, and then adjust the design.

The first challenge was to test what Ries calls the team’s “leap-of-faith assumptions” about the engine: What percentage efficiency gains were customers looking for? Would the company sell or lease the product?

Top and above: Ries shifted the conversation from “can this product be built?” to “should this product be built?” Images credit: GE.

In the same way Facebook might beta test a new feature on a small group of users, GE’s engineers came up with a plan: They would modify one existing engine, a model called the 616, for the power-generation functionality they wanted in the Series X. They could make this “minimum viable product,” or MVP, in six months instead of five years. “What Eric really helped us think about was how do we identify what the customer wants?” said Viv Goldstein, GE’s global director of Innovation Acceleration and co-founder of FastWorks. “How do you learn from your experiment? How do you make progress? Don’t assume you know the answer.”

The mantra of FastWorks soon spread. Goldstein noted that she ceased counting FastWorks projects at 800 because the method had become so embedded in the organization.

In a recent interview, Ries recalled one of his favorite FastWorks success stories, not with product developers but with a 25-person IT team supporting a finance department. When Ries started talking about adopting a customer-service mentality to deliver a tool that company employees would want to use, “I was afraid they were going to laugh me out of the room,” he said. “They said, ‘What do you mean, customer? If we tell everybody they have to do this, they’re going to do it.’”

But after a few days of FastWorks training, the team consolidated down to five people who would be fully dedicated to the project and began thinking of employees as customers. They offered different divisions the chance to be early adopters of the new product and promised to roll out a new version of the tool every month that the divisions could take or leave. “It’s one of my favorite stories because nobody believes it,” Ries said. “These people started acting like entrepreneurs.”

Ries said that when companies give their employees the freedom to experiment with new solutions, get results fast, tinker and try again, work becomes more than just work — it becomes something people are personally invested in. That’s what keeps innovation going, he said.

This is also a key to one of GE’s greatest passions: digital transformation. “Real digital transformation is almost indistinguishable from magic — it’s incredible when it works,” Ries said. “But it can’t be outsourced or delegated. In order to do digital transformation, you have to approach it like a managerial problem: How do I rebuild my company for continuous innovation?”

Andrea Pasquali has 3D-printed products as big as a working car engine and as small as a set of dentures.

Pasquali is the co-owner Zare, an Italian company focusing on additive manufacturing, a catchall term that includes 3D printing. In 2015, he was curious to see what kind of consumer luxury goods he could create using his industrial-strength 3D printers. He invited Christoph Nussbaumer, an Austrian designer known for creating ergonomic sports equipment such as skis and helmets, to mull over the options with him. “We assessed possible products, such as bicycles, lamps and jewelry,” Nussbaumer says.

What they settled on was MIO, the world’s first 3D-printed metal toothbrush. Nussbaumer designed the MIO, named after the Italian word for “my own,” after working with dentists to determine the most comfortable hold possible, and to make sure it met dental hygiene standards.

The humble toothbrush might seem like an odd choice. “[It] is not your typical status symbol,” Nussbaumer concedes. But it fits perfectly into Pasquali’s vision: showcasing the capabilities of 3D printing by transforming everyday objects into luxury items.

Printed from titanium or stainless steel, the toothbrush pays homage to one of Italy’s most famous designs — the Ferrari sports car. Users can choose between two designs that are customized for left- or right-handed brushers, and they can specify whether they want a polished, matte or galvanized finish.

Top: Italian additive-manufacturing company Zare is betting consumers will put their money where their mouths are by buying its 3D-printed toothbrushes. Above: Zare makes the toothbrushes, available in titanium or stainless steel, using 3D printers from Concept Laser, in which GE bought a majority stake last year. Images credit: Zare

The MIO won’t get your teeth cleaner than your average drugstore toothbrush, but as with many luxury items, that’s not the point. Pasquali and Nussbaumer expect that people will pay as much as 1,500 euros for the thrill of owning one.

Zare prints the toothbrush by fusing together thin layers of powdered metal with a high-energy laser inside a 3D printer. The printer, made by Concept Laser, prints the customized toothbrushes directly from a computer file. “Additive manufacturing gives designer freedom at virtually no cost,” Nussbaumer says.

The benefits are not lost on companies like GE, which bought a majority stake in Concept Laser last year. GE businesses already use 3D printing to make parts for jet engines, gas turbines and other industrial machines.

Pasquali will soon find out whether consumers are as intrigued by his concept as he is. While the company hopes to generate a new revenue stream from its first branded consumer product, there’s more to gain here than just money. MIO has the potential to become an ambassador for 3D printing, demonstrating its vast capabilities to the consumer-goods industry.

And, finally, the lowly toothbrush will gain the status it deserves.

The energy market was once a largely impersonal affair for customers. They’d pay utilities, get service in return, and that was about it. But demand for renewable energy has ushered in an era of hands-on consumerism, with green-minded corporations now directly supporting its growth.

Case in point: Microsoft, which just signed a 15-year contract to buy 100 percent of the wind energy from a new 37-megawatt wind farm in the Irish countryside, built and owned by GE. The software company will use all energy produced from the farm to power its Irish data center.

The crossover between the worlds of kilobytes and kilowatts is not unheard of. Tech companies like Microsoft, Amazon, Facebook and Apple have made similar deals tapping wind and solar installations to power their massive, power-hungry data centers. What’s different about Microsoft’s latest investment is how it came together. GE Capital financed the farm, which uses GE turbines and battery solutions, and partnered with GE Renewable Energy to arrange the power contract, in effect making GE a one-stop-shop for connecting Microsoft to an individual wind farm. The farm is also using GE software to manage wind power.

Until recently, that wasn’t possible. “It’s not like power supply of the past where you had a bunch of nuclear power plants, a couple coal plants and some gas-fired generation with the odd renewable asset thrown in, and then a jumbled mix of grey and green power being sold at the consumer end,” says Uli Suedhoff, a director at GE Renewable Energy in Europe. “Now you have thousands of different wind farms.”

The new model being pioneered by GE sees wind farms channeling power straight to energy buyers like Microsoft, Suedhoff says. That means a turbine manufacturer like GE can take on the role of enabler for the first time. “It’s new in the sense that [GE] is arranging the whole equation between demand and supply,” he says.

Top: Tech companies are increasingly looking to green energy for power, especially as prices become more competitive. “It’s not just fluffy corporate responsibility strategies,” says Uli Suedhoff, a director at GE Renewable Energy in Europe. “They want to buy competitively priced energy.” Above: GE is helping create a direct channel between wind farms and energy buyers like Microsoft, which just signed a 15-year contract to buy 100 percent of the wind energy from a new 37-megawatt wind farm in Ireland. Image credit: GE Renewable Energy.

Corporate power contracts are good for small and medium-size wind farms, whether they’re owned by a project developer, investment fund or are a community wind farm. Traditional available power contracts tend to be short term — because power prices can quickly change — and as renewable energy subsidies disappear, wind farms will need long-terms contracts to secure financing. Suedhoff believes the agreement GE is pioneering with Microsoft can serve as a model for future wind purchases.

The wind farm has other new features. For example, given that wind generation can be highly irregular — the wind doesn’t always blow — the farm will use Predix, GE’s software platform for the Industrial Internet, to smooth out its output.

Apps running on Predix can also alert wind farms to needed maintenance. Over time that can lower costs by up to 5 percent and boost the farm’s power by roughly the same amount, Suedhoff says.

Tech companies are increasingly looking to green energy for power, especially as prices become more competitive. “It’s not just fluffy corporate responsibility strategies,” Suedhoff says. “They want to buy competitively priced energy.”

Future customers won’t necessarily be technology companies. It could be an industrial company, says Suedhoff. To that end, GE is currently talking to many members of the renewable 100, a list of large companies that includes The Coca-Cola Company, Ikea, BMW and others. They have all committed to going 100 percent carbon-free over time and might also prefer to buy their power directly from a wind farm. The appetite is certainly there. “There are more companies getting serious about their green supply,” Suedhoff adds. “Their shareholders are asking for it.”