Category Archives: Robots

Technology Speeds Up Timeline on Quarterly Close

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Companies are taking four-and-half days to collect the quarterly snapshot of their financial position, down from six days in 2009

Duke Energy reduced its quarterly closing timeline by 30% to 40% to just a handful of days by 2010.
Duke Energy reduced its quarterly closing timeline by 30% to 40% to just a handful of days by 2010. PHOTO: MONICA HERNDON/ZUMA PRESS

As accounting becomes more reliant on technology, finance chiefs across a range of sectors are reaping substantial benefits from closing their books faster.

Companies including Red Hat Inc., RHT -1.07% Duke Energy Corp. DUK -0.51% and Dun & Bradstreet Corp. DNB -0.51% have sped up their quarterly close to gain quicker access to their results.

It takes most companies four-and-half days to capture a quarterly snapshot of their financial position in 2017, down from six days in 2009, according to PricewaterhouseCoopers LLP benchmarking studies. The consulting and accounting firm examined the practices of roughly 500 companies around the world with a median revenue of $2.5 billion.

Companies that have accelerated their quarterly close say having results in hand earlier makes decision-making easier and helps the organization become more nimble. The extra time allows the finance team to perform a deeper analysis, catch errors and invest more time in planning for the next quarter.

Dash to CloseCompanies are reducing the number ofdays spent on closing their books eachquarter.THE WALL STREET JOURNALSource: PricewaterhouseCoopers LLP
.daysTop quartileMedianLower quartile200920170.

A faster quarterly close was the priority for Eric Shander when he joined open-source software solutions company Red Hat as chief accounting officer in 2015. Mr. Shander and his team spent 14 months streamlining and accelerating the process.

Tasks such as account reconciliation were previously left to the end of the reporting period, contributing to the last-minute rush. Now, accounts are reconciled every few weeks. Mr. Shander also redistributed book-closing responsibilities across the finance team to ensure a more equitable workload.

Red Hat now closes its books comfortably in two days, down from five days previously, said Mr. Shander, who was named chief financial officer in April.

The finance team has been more productive as a result of the extra time, Mr. Shander said. They have caught and fixed errors, dug deeper into the data before announcing results and pivots to identifying priorities for the next quarter earlier, he said.

“We’re actually considering moving up some of our earnings announcements as a result of it,” he said. “It’s been a huge success.”

Advances in technologies are helping companies accelerate their book-closing process. More companies are automating their close to reduce the amount of manual activities, such as journal entries, said William Marchionni, senior business adviser at consulting firm Hackett Group HCKT -1.31% Inc.’s Finance Operations Advisory Program.

“Some top performers are getting management reporting data on revenue, shipments, cost for goods sold, and other key metrics on a daily basis from their information systems,” Mr. Marchionni said.

For Dun & Bradstreet CFO Rich Veldran, the lure of cost savings has prompted investments in robotics and automation technology that accelerate the quarterly reporting process. The data and analytics company closes its books in four days, despite operating across more than 200 countries, which adds to the complexity of its financial reporting process.

“There’s a real opportunity for us to do things in a much more automated, faster way, within finance,” Mr. Veldran said, adding that his team is already testing several potential applications for robotic process automation in the finance function.

Steven Young, CFO of Duke Energy.
Steven Young, CFO of Duke Energy. PHOTO:DUKE ENERGY

A new software system was key to helping Duke Energy streamline its quarterly close, said CFO Steven Young. The electric utility in 2007 launched a three-year revamp of its financial infrastructure, after a series of acquisitions burdened the company with a patchwork of financial systems and processes, Mr. Young said. Duke reduced its closing timeline by 30% to 40% to just a handful of days by 2010, Mr. Young said, though he declined to state the exact number of days. The company has continued to improve its quarterly close through new technologies.

“The advantage is that you get data disseminated through the organization quicker, you can then communicate trends, patterns and that can result in quicker decisions to take tactical actions in response to the data,” Mr. Young said.

Companies that operate across multiple geographies and sell different types of products and services often require more time to close their books than a single-product, single-geography business, said Beth Paul, a partner at PwC.

CFOs in a particular sector, such as airlines, autos or retail, often aim to close their books and report results around the same time to keep in line with industry norms.

“There’s a view that they need to be consistent with their peers because if you’re lagging, it could lead people to wonder why,” Ms. Paul said, adding that straggling behind the pack could raise doubts about management’s competency.

She also noted that certain sectors, such as banks and financial services, tend to close their books faster due to greater investments in technology.

Still, for many CFOs accelerating the quarterly close process remains a low priority. Instead, these companies have focused on meeting increasing regulatory demands and deployed resources to operational projects such as entering new markets or launching new product lines.

“Account-to-report has historically been the last place where companies invest. It isn’t client facing, and they have ended up doing things on a shoestring,” said Hackett Group’s Mr. Marchionni.

Next Leap for Robots: Picking Out and Boxing Your Online Order

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Developers close in on systems to move products off shelves and into boxes, as retailers aim to automate labor-intensive process

Your Next Online Order Could Be Picked Out by a Robot
Facing more pressure to speed orders more quickly to customers, a rising number of companies are using high-tech robots in their manufacturing process. But could it render humans obsolete? The WSJ takes a look inside.

Robot developers say they are close to a breakthrough—getting a machine to pick up a toy and put it in a box.

It is a simple task for a child, but for retailers it has been a big hurdle to automating one of the most labor-intensive aspects of e-commerce: grabbing items off shelves and packing them for shipping.

Several companies, including Saks Fifth Avenue owner Hudson’s Bay Co. HBC -0.27% and Chinese online-retail giant Inc., JD 1.07% have recently begun testing robotic “pickers” in their distribution centers. Some robotics companies say their machines can move gadgets, toys and consumer products 50% faster than human workers.

Retailers and logistics companies are counting on the new advances to help them keep pace with explosive growth in online sales and pressure to ship faster. U.S. e-commerce revenues hit $390 billion last year, nearly twice as much as in 2011, according to the U.S. Census Bureau. Sales are rising even faster in China, India and other developing countries.

That is propelling a global hiring spree to find people to process those orders. U.S. warehouses added 262,000 jobs over the past five years, with nearly 950,000 people working in the sector, according to the Labor Department. Labor shortages are becoming more common, particularly during the holiday rush, and wages are climbing.

Mechanical engineer Parker Heyl adjusts a robotic arm at RightHand Robotics’ test facility in Somerville, Mass.
Mechanical engineer Parker Heyl adjusts a robotic arm at RightHand Robotics’ test facility in Somerville, Mass.PHOTO: SIMON SIMARD FOR THE WALL STREET JOURNAL

Picking is the biggest labor cost in most e-commerce distribution centers, and among the least automated. Swapping in robots could cut the labor cost of fulfilling online orders by a fifth, said Marc Wulfraat, president of consulting firm MWPVL International Inc.

“When you’re talking about hundreds of millions of units, those numbers can be very significant,” he said. “It’s going to be a significant edge for whoever gets there first.”

Until recently, robots had to be trained to identify and grab each item, which is impractical in a distribution center that might stock an ever-changing array of millions of products.

Automation companies such as Kuka AG KU2 -0.45% , Dematic Corp. and Honeywell International Inc. unit Intelligrated, as well as startups like RightHand Robotics Inc. and IAM Robotics LLC are working on automating picking.

In RightHand Robotics’ Somerville, Mass., test facility, mechanical arms hunt around the clock through bins containing packages of baby wipes, jars of peanut butter and other products. Each attempt—successful or not—feeds into a database. The bigger that data set, the faster and more reliably the machines can pick, said Yaro Tenzer, the startup’s co-founder.

Hudson’s Bay is testing RightHand’s robots in a distribution center in Scarborough, Ontario.

“This thing could run 24 hours a day,” said Erik Caldwell, the retailer’s senior vice president of supply chain and digital operations, at a conference in May. “They don’t get sick; they don’t smoke.” is developing its own picking robots, which it started testing in a Shanghai distribution center in April. The company hopes to open a fully automated warehouse there by the end of next year, said Hui Cheng, head of’s robotics-research center in Silicon Valley.

Swisslog, a subsidiary of Kuka, sells picking robots that can be integrated into the company’s other warehouse automation systems or purchased separately. The company sold its first unit in the U.S., to a large retailer, earlier this year, said A.K. Schultz, Swisslog’s vice president for retail and e-commerce. Mr. Schultz declined to name the retailer.

Previous waves of warehouse automation didn’t lead to sudden mass layoffs, partly because order volumes have been growing so fast. And automated picking is still at least a year away from commercial use, robotics experts say. The main challenge lies in creating the enormous databases of 3D-rendered objects that robots need to determine the best way to grip new objects.

RightHand Robotics co-founders Leif Jentoft, left, and Yaro Tenzer
RightHand Robotics co-founders Leif Jentoft, left, and Yaro Tenzer PHOTO: FOR THE WALL STREET JOURNAL

Some companies hope to speed development by making some research Inc. will hold its third annual automated picking competition at a robotics conference in Japan later this month. For the first time, entrants won’t know in advance all the items the robots will need to pick.

At the University of California, Berkeley, a team is simulating millions of attempts to pick 10,000 objects. Funded by Amazon, Siemens AG and others, the project is meant to build an open-source database for use in any automation system, said Ken Goldberg, the professor leading the project.

“With 10,000 objects, I’m surprised how well it did,” he said. “I would love to show it 100,000 examples and see how well it performs after that.”

Did You Hear That? Robots Are Learning The Subtle Sounds Of Mechanical Breakdown

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Fast Company

Expert mechanics can detect what’s wrong with a car without lifting the hood. So can deep learning robots, says startup 3DSignals.

Did You Hear That? Robots Are Learning The Subtle Sounds Of Mechanical Breakdown
[Photo: Flickr user David Hodgson]

Sometimes, machines just don’t sound right.

Brakes squeal, hard drives crunch, air conditioners rattle, and their owners know it’s time for a service call. But some of the most valuable machinery in the world often operates with nobody around to hear the mechanical breakdowns, from the chillers and pumps that drive big-building climate control systems to the massive turbines at hydroelectric power plants.

That’s why a number of startups are working to train computers to pick up on changes in the sounds, vibrations, heat emissions, and other signals that machines give off as they’re working or failing. The hope is that the computers can catch mechanical failures before they happen, saving on repair costs and reducing downtime.

“We’re developing an expert mechanic’s brain that identifies exactly what is happening to a machine by the way that it sounds,” says Amnon Shenfeld, founder and CEO of 3DSignals, a startup based in Kfar Saba, Israel, that is using machine learning to train computers to listen to machinery and diagnose problems at facilities like hydroelectric plants and steel mills

And while most current efforts are currently focused on large-scale machinery, Shenfeld says the same sort of technology might one day help detect failures in home appliances or in devices like self-driving cars or rental vehicles that don’t spend much time in the hands of an owner who’s used to their usual sounds.

“When you have car-as-a-service, the person in the car doesn’t know the car,” he says. “If it sounds strange, you’re losing this link with the human in the car deciding it’s time to take it to the mechanic.”

Initially, 3DSignals’ systems can detect anomalous sounds based on physical modeling of particular types of equipment, notifying an expert mechanic to diagnose the problem. And once the problem is fixed, the mechanic’s diagnosis is added to 3DSignals’ database, which it uses to train its algorithms to not only detect unusual sounds, but also interpret them to understand what kind of repair is needed.

“The next time we hit this signature on the same machine for the same customer or another customer using the same type of machine, it will not just be anomaly detection,” says Shenfeld.

And while 3DSignals focuses entirely on using its machine learning tools to process acoustic data—an area Shenfeld says is surprisingly neglected outside of speech recognition—other companies are using a variety of other types of data to detect and diagnose mechanical problems.

[Photo: Flickr user Sue Clark]

Systems from Augury, a startup with offices in New York and Haifa, Israel, monitor vibrations, temperature ultrasound, and electromagnetic emissions from machinery, typically large-scale heating and cooling systems. The company offers a portable tool a technician can use to capture a reading to an iPhone or Android device, where an app offers a real-time diagnosis as well as a continuous monitoring system, says cofounder and CEO Saar Yoskovitz.

“One of our customers, located in Ohio, had a thunderstorm at 2 a.m., and the whole building went dark,” he says. “The generator was supposed to pick up automatically but it didn’t, and the way that they learned about it was through an alert they got from Augury.”

In more complicated situations, the system uses machine learning-based algorithms and a growing library of signals of different types of errors to suggest what’s wrong and what technicians can do to repair the machine, he says.

“Over time, we’ve collected probably the largest malfunction dictionary in the world for our types of machines,” says Yoskovitz.

For another startup, called Presenso, also based in Haifa, the exact type of data being monitored is less important than how it changes over time and what that signals about the machine’s operation. The company’s systems record data from sensors already installed in industrial equipment as part of existing control processes, streaming readings to Presenso’s cloud servers.

“We don’t care, or we don’t need to know, if the sensor we’re analyzing now measures temperature or voltage or flow,” says CEO and cofounder Eitan Vesely.

Presenso’s software tools use a variety of machine learning techniques to effectively build a model of a machine’s operations based on the sensor data it receives. The tools provide visualizations of unusual readings, and how different they are from normal operations.

“They don’t need any human guidance or [to] know what the physical attributes are that are being measured,” Vesely says. “The goal is for them to learn by themselves how the machine operates.”

And while real-time breakdown detection is obviously useful for companies operating machines in their own facilities, experts say it could also be useful to equipment vendors or insurance companies providing financial coverage in the case of downtime.

“If a company has downtime or business interruption insurance, that’s something where it becomes incredibly relevant and also a money saver,” says Ryan Martin, a senior analyst at ABI Research.

Having more reliable predictions of when machines need maintenance could also spur equipment makers to effectively offer time as a service, charging industrial users either extended warranties or even charging by the hour for the guaranteed use of their equipment without incurring too much risk to themselves, says Augury’s Yoskovitz.

“One of the problems with this business model is they hold all the risk,” he says. “If anything goes wrong, they pay for it, and they’re looking for ways to lower this risk.”

Helper Robots Develop Skills and Charm

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At CES 2017, robots gain physical skills and improve emotional connections to humans

LG Electronics Inc. Vice President David VanderWaal unveiled Airport Guide Robot  at the 2017 Consumer Electronics Show in Las Vegas on Wednesday.

LG Electronics Inc. Vice President David VanderWaal unveiled Airport Guide Robot at the 2017 Consumer Electronics Show in Las Vegas on Wednesday. PHOTO: ASSOCIATED PRESS

Robots that play chess, provide directions, go out for groceries—these are the helpful robots on display at this year’s CES tech trade show in Las Vegas. And while they don’t resemble humans, exactly, many are designed to accomplish their tasks with digital eyes, turning heads, waving arms and grabbing hands.

“We’re on the cusp of a robotic moment,” said J.P. Gownder, a robotics-focused senior analyst and vice president at the Forrester research firm. Not only are robots developing physical skills necessary to carry out domestic tasks, they’re also gaining emotional appeal so that humans accept them as a companion, not just an appliance.

While that quintessential humanoid domestic servant may yet be 20 years away, he said, what’s on display at the show is “a significant step toward the realization of robots that have been in our popular culture for 80 years or so.”

The C-3PO model—named after the chatty Star Wars droid—is a single, humanlike robot that is good at many different things. “The robots we’re seeing at CES are good at specific tasks instead of a little bit of everything,” he said. But many developers focusing on individual skills could bring down costs for robotics technologies overall.

As the tech world reveals the products that will impact the year ahead, Personal Tech columnists Geoffrey A. Fowler and Joanna Stern hunt for the most exciting and unusual, from AR glasses to breast pumps. Photo: Emily Prapuolenis/The Wall Street Journal

One of the big themes of CES 2017 is building intelligence into everyday objects, like ovens, refrigerators and other appliances. While a robot, in the end, may just be another device, the fact that it is designed to feel more like a companion will pay off, Mr. Gownder said.

“Having these humanlike features communicates something primal to the user, and when done properly it can make robots more useful and better because we have a connection to them.”

Here are a few robots at CES that demonstrate both skills and charm:

MoRo, a human-size assistant robot

MoRo is a nearly 4-foot tall robot that can help grab things at home or in the grocery store.

MoRo is a nearly 4-foot tall robot that can help grab things at home or in the grocery store. PHOTO: BEIJING EWAYBOT TECHNOLOGY LLC

MoRo is designed to run errands indoors and outdoors, as long as it isn’t raining. It has two six-joint arms with three fingers at each end. The arms move up and down its sides so it can grab things on the ground or from a not-too-high shelf. Its maker, Beijing Ewaybot Technology LLC, says it uses a mixture of cameras, sensors and algorithms to apply the correct amount of force for picking up either a piece of tissue or a can. Voice controlled—and capable of talking back—it stands nearly 4 feet tall and weighs 77 pounds. MoRo is set to go on sale in May for $30,000.

ITRI’s chess-playing Intelligent Vision System robot

The ITRI Intelligent Vision System robot uses cameras and sensors to play chess and pour coffee.

The ITRI Intelligent Vision System robot uses cameras and sensors to play chess and pour coffee. PHOTO:INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE

A robot that can play chess with humans while also pouring them a cup of coffee: That is what research lab ITRI Taiwan brought to CES to demonstrate its Intelligent Vision System. Cameras help the robot recognize the chess pieces and cups, and perceive depth so that it can reach for the right piece without knocking over another, or pick up the coffee without tipping it. ITRI says it plans to license its technology, so while you may see these sort of abilities in other robots, you won’t be able to buy a robotic chess partner from the lab itself.

Yumii Cutii, a robot friend for seniors

Yumii's Cutii robot in action at the CES 2017 trade show.

Yumii’s Cutii robot in action at the CES 2017 trade show. PHOTO: WILSON ROTHMAN/THE WALL STREET JOURNAL

The Cutii is built to “make you feel good,” says Yumii, the French startup making the robot. It is designed to help senior citizens continue living at home instead of going into an eldercare facility. Its LCD-screen head can bob up and down, to show off its smiling face and host video calls from friends, family and doctors. It can recognize the faces of its human companions. Since it is voice controlled, it can ask them if they want to take part in pre-determined activities like visiting a museum or taking a yoga class—then listen for a response.

Hease Robotics Heasy hospitality robot

The Heasy uses a swiveling set of eyes to express emotion.

The Heasy uses a swiveling set of eyes to express emotion. PHOTO: HEASE ROBOTICS

Need to find your way around a hotel resort? Looking for a specific item in a mall? Trying to find departure times at an airport? Heasy is a robot built to do all of that, and provide any other information you might need. It is a robot made for commercial use, and it offers a bit of personality thanks to a swiveling pair of eyes. Hease, the French startup behind it, calls Heasy a “robot as a service.” It is set to go on sale to businesses later this year.

LG Airport Guide Robot

LG's Airport Guide Robot can escort people to their gate.

LG’s Airport Guide Robot can escort people to their gate. PHOTO: JOHN LOCHER/ASSOCIATED PRESS

Korean electronics giant LG Electronics Inc. showed off a similar robot of its own at CES. The aptly named Airport Guide Robot is set to arrive in Seoul’s Incheon International Airport later this year. When it does, it’ll be able to answer questions in English, Chinese, Japanese and Korean. It can scan a passenger’s ticket to offer boarding times and gate locations, and directions inside of the airport, with estimated distances and walking times. If needed, it can escort lost or late travelers to their gates, LG said.

The Robotics Revolution: The Next Great Leap in Manufacturing

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SEPTEMBER 23, 2015
Boston Consulting Group. By Harold L. Sirkin, Michael Zinser, and Justin Rose
  • By 2025, the share of tasks performed by robots will rise from a global average of around 10 percent to about 25 percent across all manufacturing industries.
  • Wider robotics adoption will boost manufacturing productivity by up to 30 percent.
  • As a result of higher robotics use, average manufacturing labor costs are projected to be 33 percent lower in South Korea and 18 to 25 percent lower in China, Germany, the US, and Japan than they otherwise would have been.

It has been roughly four decades since industrial robots—with mechanical arms that can be programmed to weld, paint, and pick up and place objects with monotonous regularity—first began to transform assembly lines in Europe, Japan, and the U.S. Yet walk the floor of any manufacturer, from metal shops to electronics factories, and you might be surprised by how many tasks are still performed by human hands—even some that could be done by machines. The reasons are simple: economics and capabilities. It is still less expensive to use manual labor than it is to own, operate, and maintain a robotics system, given the tasks that robots can perform. But this is about to change.

The real robotics revolution is ready to begin. Many industries are reaching an inflection point at which, for the first time, an attractive return on investment is possible for replacing manual labor with machines on a wide scale. We project that growth in the global installed base of advanced robotics will accelerate from around 2 to 3 percent annually today to around 10 percent annually during the next decade as companies begin to see the economic benefits of robotics. In some industries, more than 40 percent of manufacturing tasks will be done by robots. This development will power dramatic gains in labor productivity in many industries around the world and lead to shifts in competitiveness among manufacturing economies as fast adopters reap significant gains.

A confluence of forces will power the robotics takeoff. The prices of hardware and enabling software are projected to drop by more than 20 percent over the next decade. At the same time, the performance of robotics systems will improve by around 5 percent each year. As robots become more affordable and easier to program, a greater number of small manufacturers will be able to deploy them and integrate them more deeply into industrial supply chains. Advances in vision sensors, gripping systems, and information technology, meanwhile, are making robots smarter, more highly networked, and immensely more useful for a wider range of applications. All of these trends are occurring at a time when manufacturers in developed and developing nations alike are under mounting pressure to improve productivity in the face of rising labor costs and aging workforces.

To assess the potential impact of the coming robotics revolution on industries and national competitiveness, The Boston Consulting Group conducted an extensive analysis of 21 industries in the world’s 25 leading manufacturing export economies, which account for more than 90 percent of global trade in goods. We analyzed five common robot setups to understand the investment, cost, and performance of each. We examined every task in each of those industries to determine whether it could be replaced or augmented by advanced robotics or whether it would likely remain unchanged. After accounting for differences in labor costs, productivity, and mix by industry in each country, we developed a robust view of more than 2,600 robot-
industry-country combinations and the likely rate of adoption in each.

The Global Impact of the Robotics Takeoff

The following are some of the key findings of this research:

  • Robotics use is reaching the takeoff point in many sectors. The share of tasks that are performed by robots will rise from a global average of around 10 percent across all manufacturing industries today to around 25 percent by 2025. Big improvements in the cost and performance of robotics systems will be the catalysts. In several industries, the cost and capabilities of advanced robots have already launched rapid adoption.
  • Adoption will vary by industry and economy. Among high-cost nations, Canada, Japan, South Korea, the UK, and the U.S. currently are in the vanguard of those deploying robots; Austria, Belgium, France, Italy, and Spain are among the laggards. Some economies, such as Thailand and China, are adopting robots more aggressively than one might expect given their labor costs. Four industrial groupings—computers and electronic products; electrical equipment, appliances, and components; transportation equipment; and machinery—will account for around 75 percent of robotics installations during the next decade.
  • Manufacturing productivity will surge. Wider adoption of robots, in part driven by a newfound accessibility by smaller manufacturers, will boost output per worker up to 30 percent over the medium term. These gains will be in addition to improvement from other productivity-enhancing measures, such as the implementation of lean practices.
  • Savings in labor costs will be substantial. As a result of higher robotics use, the average manufacturing labor costs in 2025—when adjusted for inflation and other costs and productivity-enhancing measures—are expected to be 33 percent lower in South Korea and 18 to 25 percent lower in, for example, China, Germany, the U.S., and Japan than they otherwise would have been.
  • Robots will influence national cost competitiveness. Countries that lead in the adoption of robotics will see their manufacturing cost competitiveness improve when compared with the rest of the world. South Korea, for example, is projected to improve its manufacturing cost competitiveness by 6 percentage points relative to the U.S. by 2025, assuming that all other cost factors remain unchanged. High-cost nations—such as Austria, Brazil, Russia, and Spain—that lag behind will see their relative cost competitiveness erode.
  • Advanced manufacturing skills will be in very high demand. As robots become more widespread, the manufacturing tasks performed by humans will become more complex. The capacity of local workers to master new skills and the availability of programming and automation talent will replace low-cost labor as key drivers of manufacturing competitiveness in more industries. There will be a fundamental shift in the skills that workers will need in order to succeed in advanced-manufacturing plants.

Few manufacturing companies will be left untouched by the new robotics revolution. But getting the timing, cost, and location right will be critical. Investing in expensive robotics systems too early, too late, or in the wrong location could put manufacturers at a serious cost disadvantage against global competitors.

Preparing for the Robotics Revolution

The right time for making the transition to advanced robotics will vary by industry and location. But even if that time is several years away, companies need to prepare now.

To gain competitive advantage, companies need to adopt a holistic approach to the robotics transition. We recommend that companies take the following actions:

  • Understand the global landscape. First, companies need a clear picture of the trends in robot adoption around the world and in their industries. They need to know how the price and performance of robots are likely to change in comparison with the total cost of labor in each economy where they manufacture—and how this comparison is likely to change in the years ahead. They must also factor in other considerations, such as the flexibility of labor rules and the future availability of workers, that support or hinder wider robotics adoption in a given economy. It is important to keep in mind that these are moving targets.
  • Benchmark the competition. Companies need to be well aware of what their competitors are currently doing and understand what they will do in the future. If robotics adoption is expected to rapidly increase in their industry, they should assume that the total cost of systems will fall. This knowledge will help companies more accurately estimate the cost and timing of investments as well as make decisions about where to locate new capacity.
  • Stay technologically current. Rapid advances in technology mean that companies must stay abreast of the evolving capabilities of advanced robotics systems. They should have a clear view of whether and how quickly innovation is resolving technical barriers that so far have inhibited the use of robots, such as the ability to manipulate flexible or oddly shaped materials or to operate safely alongside workers. Just as important, when will these new applications be cost-effective? As they take stock of the new capabilities and the improvements in price and performance, many companies—even small and midsize manufacturers—may discover that installing robotics is more cost-effective than they once thought. In some cases, having a view on the evolution of robotics and automation can help a company determine whether it is better to wait for a better technology to emerge or to implement a new process that allows them to upgrade technology without having to duplicate what they have already done. In many ways, timing is crucial.
  • Prepare the workforce. As more factories convert to robotics, the availability of skilled labor will become a more important factor in the decision about where to locate production. Tasks that still require manual labor will become more complex, and the ability of local workforces to master new skills will become more critical. The availability of programming and automation talent will also grow in importance. Companies and economies must prepare their workforces for the robotics revolution and should work with schools and governments to expand training in such high-compensation professions as mechanical engineering and computer programming.
  • Prepare the organization. Even if the economics don’t yet favor major capital investment, companies should start preparing their global manufacturing operations now for the age of robotics. They should make sure that their networks are flexible enough to realize the benefits of robotics as installations become economically justified in different economies and as suppliers automate. They should get themselves up to speed on new advanced-manufacturing technologies and think about how they will transform their current production processes so that these technologies can achieve their potential. For many manufacturers, adapting to the age of robotics will require a transformation of their operations.

Manufacturers do not have the luxury of waiting to act until the economic conditions for robotics adoption are ripe. Our projections show that when the cost inflection point arrives, robotics installation rates are likely to accelerate rapidly. This will provide the opportunity to create a substantial competitive advantage. Companies and economies that are ready to capitalize on the opportunity will be in a position to seize global advantage in manufacturing.

This Swimming Robot Digests Pollution And Turns It Into Electricity

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This Swimming Robot Digests Pollution And Turns It Into Electricity

The Row-Bot powers itself by cleaning up bodies of water.


This is the Row-Bot, a robot that walks on water, and gets its energy by eating the microbes in dirty ponds and “digesting” them in its artificial stomach. Using this method, it generates more than enough power to propel itself on the hunt for more bacteria to feed its nature-inspired engine.

The bot, inspired by the water boatman bug, comes from a team at Bristol University in the U.K., and it consists of two main parts. One is a propulsion mechanism, which uses a paddle driven by a tiny electric motor. The other is the stomach, which uses a microbial fuel cell (MFC) to power the paddle. The robot gulps in water, turns it into electricity, and uses it to make a few paddle strokes, the movement lets it gulp down another mouthful of dirty water, and the process starts over.

An MFC is like a regular fuel cell, only it uses bacteria. When those bacteria metabolize organic matter, they produce carbon dioxide and water. However, if you keep the bacteria away from oxygen, they produce carbon dioxide, protons, and electrons, and these can be harnessed to flow between an anode and a cathode, just like the electrons flow between terminals in battery acid.

The Row-Bot’s MFC has has a secret weapon. It uses “electrogenic” bacteria. That is, the electrons it produces can run directly to the “battery” terminal, instead of depositing it into oxygen or another substance first. This is more efficient, and allows the Row-Bot to generate enough power from its tiny stomach to both move around, and to open and close its maw.

This robot has plenty of practical uses. It works in any kind of water, from fresh to seawater to waste water. Sic a fleet of Row-Bots into a polluted lake, and they could rove for months, feeding on the filth and cleaning as they go. The same principles could also be used for land-based or airborne robots, but water is a lot easier because the bots are swimming in their own food source, and tricky problems like gravity are removed from the equation. Looking at it like this, it’s easy to see why life first sprang into being in the world’s oceans.

New Robots Designed to Be More Agile and Work Next to Humans

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Wall Street Journal

ABB introduces the YuMi robot at a trade fair in Germany

German Chancellor Angela Merkel and Indian Prime Minister Narendra Modi, far right, look at a YuMi robotic arm in Hannover, Germany, on Monday. ENLARGE
German Chancellor Angela Merkel and Indian Prime Minister Narendra Modi, far right, look at a YuMi robotic arm in Hannover, Germany, on Monday. PHOTO: WOLFGANG RATTAY/REUTERS

Robot makers are promoting a new generation of robots designed to work safely alongside people and take on tasks such as assembly of small parts that require more dexterity than older robots can muster.

On Monday, ABB Ltd., a Zurich-based maker of automation equipment, introduced the latest such robot, dubbed YuMi, at an automation trade fair in Hannover, Germany.Fanuc Corp. of Japan is preparing to launch a rival offering called CR-35iA.

These robots will compete with other so-called collaborative robots introduced by smaller competitors in recent years that are touted as being more flexible, much easier to program and safer for humans. Older types of robots, designed to do such tasks as weld or hoist heavy objects, are so fast and powerful that they need to be surrounded by fences to avoid injuring workers. The newer robots have sensors and cameras, telling them to slow down or halt when people get too near.

“We have taken the robot out of the cage,” said Ulrich Spiesshofer, ABB’s chief executive, in an interview.

ABB said its new YuMi robot, with a starting price of about $40,000, can help assemble such products as smartphones, laptops and tablet computers that have been assembled largely by hand by workers in lower-cost countries like China.

It also could be used for quality inspections and packaging, he said. Auto makers long have been the biggest users of robots, but Mr. Spiesshofer said sales are growing quickly in other industries, including electronics, food and beverages. Sales to the auto industry now are less than half of ABB’s total robot business, he said.

How hard is it to build a robot today? Not as hard as you’d think. MarketWatch’s Jurica Dujmovic discusses. Photo: Lego

YuMi is dexterous enough to thread a needle, he said, though ABB isn’t working on robots for sewing at this stage.

ReThink Robotics Inc. of Boston and Universal Robots AS of Denmark have been selling collaborative robots for several years and continue to upgrade them. Last month, ReThink unveiled a new model called Sawyer, joining its earlier Baxter line, to do such work as tending factory machines and testing circuit boards. Sawyer is priced at about $29,000. Universal last month released a model called UR3, priced at roughly $23,000 and designed to do assembly in electronics and other industries.

ABB’s YuMi is designed to work with small parts weighing as much as 1.1 pounds. Fanuc’s CR-35iA, by contrast, can pick up items weighing as much as 77 pounds. The new robot is expected to be used for such things as stacking boxes on pallets, moving materials into place for assembly, and driving in screws.

Many repetitive tasks in factories are still done by people because they require a delicate sense of touch and dexterity that eludes most machines. Robot makers say they are making progress toward matching human dexterity, though. At the Hannover trade show, Kuka Roboter GmbH of Germany demonstrated new capabilities, developed in cooperation with Microsoft Corp., in Kuka’s two-year-old LBR iiwa robot. For instance, the robot installed a tube inside a dishwasher.

“The robot is able to wiggle it into place like a human would” by using sensors that measure such things as torque and resistance, said Dominik Bösl, Kuka’s innovation manager. “It knows how much force it should apply” and what kind of resistance it should meet.

The future is here today: How GE is using the Internet of Things, big data and robotics to power its business

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By Danny Pal in Computing
12 Mar 2015

When your business supplies over 30 per cent of the planet’s power and produces engines for everything from cars to aircraft, it’s important to ensure that both the means of production and the products themselves operate as efficiently as possible.

That’s why General Electric (GE) – the fourth largest company in the world – has invested heavily in the Internet of Things and analytics technologies. As Bill Ruh, GE VP of global software services, told Computing: “It’s about getting better outcomes out of the machines we produce … the most profitable thing we can get to is zero unscheduled downtime.

“If you can make sure your power generation doesn’t go down, you don’t have brownouts, you can change the world and substantially improve industry.”

GE Aviation, the world’s second largest engine manufacturer, is using Internet of Things (IoT) technology to manage and repair jet engines pre-emptively, detecting tiny faults before they have a chance to grow into big ones.

“We’re finding that we can drive huge productivity increases in our teams because we can look at historical data across the fleet and begin to identify problems before they really happen,” Ruh explained

“We’ve had huge productivity increases because we’re automating how we think about maintaining an aircraft engine,” he continued. “We’re using big data analytics to help drive the maintenance schedule.”

By using sensors to collect engine data, GE is able to perform short bursts of maintenance much earlier on, meaning that over an entire lifecycle the engine spends less time in repairs.

Ruh likened it to getting a car repaired, but then discovering something hadn’t been spotted and having to return it to the garage shortly afterwards.

“The thing you hate when taking your car in is when in two months you have to take it back in. If they’d fixed it the first time, then they’d save you money and time,” he said.

“We can do that now. This is going to drive satisfaction rates and time on wing.”

But jet engine maintenance isn’t the only area where GE has harnessed the power of the IoT and big data analytics. Another is what the company calls its “Brilliant Factories Initiative”, which, according to Ruh, is “rethinking what a factory is”.

“Analytics in a factory has probably been underutilised, the data is mostly thrown away,” he explained.

“But we’re not doing that. We’re keeping every piece of data about how the machines operate and we’re using that to continue to identify types of analytics that could drive efficiency in our factory.”

Ruh added that GE is aiming for a “huge” 40 per cent improvement in factory efficiency.

‘If I could do analytics without IoT, I would’

But while connected devices and the Internet of Things are helping to drive improvements, for Ruh, they’re not the most interesting part of factory set-up; that would be the data and what can be mined from it.

“If I could do the analytics without IoT, I would, but I can’t because I need the machine data and machines are chatty. So for us, the IoT is necessary but it’s not the most interesting part. The analytics, the insight you gain: that’s where the value is. It’s just that you need the data in order to gain the insight,” he said.

For a company the size of GE, there’s a lot of data to gain insight from.

“Our current jet aircraft engines produce one terabyte of data per flight,” Ruh said, to illustrate the scale of GE’s data trove. “On average an airline is doing anywhere from five to 10 flights a day, so that’s five to 10 terabytes per plane, so when you’re talking about 20,000 planes in the air you’re talking about an enormous amount of data per day.”

Apart from the sheer volume of data, Ruh estimated that the firm analyses 50 million variables from 10 million sensors. These are the sorts of numbers that most industries could not conceive of managing. So when is IoT going to become useful to the mainstream?

Ruh believes that IoT going mainstream may be three to five years away. However, he warned that “if you’re not starting today you won’t be mainstream”. It is especially challenging, he argued, because operations teams rather than IT teams are the ones leading the change.

“The people who run power plants? They’re working with IT, don’t get me wrong, but they’re putting their own operations structure in place that is parallel to the IT structure,” he said.

“They’re already putting sensors in power plants, airlines and oil rigs. The number of sensors, the amount of data and the collection of that is already there,” Ruh continued. The trouble is, he added, the operations teams tend not to link this to analytics, which is where IT needs to get involved.

“The magic has to occur when the IT and the operations teams come together and that’s really where in five years the mainstream will be driven, when these guys are working in tandem,” he said. “GE does that today, but it took us four years to get there and it’s going to take other organisations that long.”

Despite being relatively advanced in its use of IoT and big data processing, GE isn’t resting on its laurels. Rather, it is exploring new areas to deploy the technology, including power generation.

“We’re changing the way we do remote monitoring and diagnostics. GE generates over 30 per cent of electricity in the world on our machines. So we monitor those machines remotely, then we try to proactively understand their behaviour and how to fix them,” Ruh said.

Ultimately, as with the jet engines, use of this technology will allow predictive maintenance, “telling our customers what they should be doing as opposed to what has happened”. This approach represents “the cornerstone of modernisation”, for GE.

‘An R2-D2 for every field worker’

But sensors are just the start. Ruh described how GE is looking to exploit the power of internet-connected robots to carry out “dirty, dull and dangerous tasks”. The firm has already experimented with this in the railway industry.

“We’re testing robotic rail inspectors that will go along and look for problems in rail yards, looking to see if there’s anything broken,” said Ruh. “The nice thing about that is they work 24 hours a day and they can work in the dark as well.”

GE called its first robotic inspector “The Guardian”, because as Ruh pointed out, it’s there to help people, not replace them.

“It’s something which actually works with a human,” he said, adding that GE got inspiration for this model from the film Star Wars.

“Most people think robotics is separate from humans but I look at something like Star Wars, where the robots weren’t there to replace humans, but to help them. So the question is: how do you create an R2-D2 for every field worker?”

Ruh went on to describe how this could raise some interesting questions in the future: as robots get more intelligent people could potentially start treating them on a more equal level.

“People are treating their robots like pets or members of the family. People are giving robot vacuum cleaners names, but not only that – and I think this is strange – but people take them on vacation,” he said.

“The fact is that we’re now seeing the Turing Test being passed every day, with people having no idea that they’re talking to a computer,” Ruh said. By extension, if the trend continues, robots will become widely accepted in homes and workplaces.

“Once robots take on human qualities – and I think that’s what’s going to happen -we’re going to find these things are playing a role in our lives as part of the family,” he concluded.

Jobs and the Clever Robot

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Experts rethink belief that tech always lifts employment as machines take on skills once thought uniquely human.

Feb. 24, 2015

CAMBRIDGE, Mass.—Economist Erik Brynjolfsson had long dismissed fears that automation would soon devour jobs that required the uniquely human skills of judgment and dexterity.

Many of his colleagues at the Massachusetts Institute of Technology, where a big chunk of tomorrow’s technology is conceived and built, have spent their careers trying to prove such machines are within reach.

When Google Inc. announced in 2010 that a specially equipped fleet of driverless Toyota Prius cars had safely traveled more than 1,000 miles of U.S. roads, Mr. Brynjolfsson realized he might be wrong.

“Something had changed,” Mr. Brynjolfsson said, recalling his astonishment at machines navigating the many unpredictable moments that face drivers.

From steam engines to robotic welders and ATMs, technology has long displaced humans—always creating new, often higher-skill jobs in its wake.

But recent advances—everything from driverless cars to computers that can read human facial expressions—have pushed experts like Mr. Brynjolfsson to look anew at the changes automation will bring to the labor force as robots wiggle their way into higher reaches of the workplace.

They wonder if automation technology is near a tipping point, when machines finally master traits that have kept human workers irreplaceable.

“It’s gotten easier to substitute machines for many kinds of labor. We should be able to have a lot more wealth with less labor,” Mr. Brynjolfsson said. “But it could happen that there are people who want to work but can’t.”

In the Australian Outback, for example, mining giant Rio Tinto uses self-driving trucks and drills that need no human operators at iron ore mines. Automated trains will soon carry the ore to a port 300 miles away.

The Port of Los Angeles is installing equipment that could cut in half the number of longshoremen needed in a workplace already highly automated.

Computers do legal research, write stock reports and news stories, as well as translate conversations; at car dealers, they generate online advertising; and, at banks, they churn out government-required documents to flag potential money laundering—all jobs done by human workers a short time ago.

Microsoft co-founder Bill Gates , speaking in Washington last year, said automation threatens all manner of workers, from drivers to waiters to nurses. “I don’t think people have that in their mental model,” he said.

Robot employment:
Gartner Inc., the technology research firm, has predicted a third of all jobs will be lost to automation within a decade. And within two decades, economists at Oxford University forecast nearly half of the current jobs will be performed with machine technology.

“When I was in grad school, you knew if you worried about technology, you were viewed as a dummy—because it always helps people,” MIT economist David Autor said. But rather than killing jobs indiscriminately, Mr. Autor’s research found automation commandeering such middle-class work as clerk and bookkeeper, while creating jobs at the high- and low-end of the market.

This is one reason the labor market has polarized and wages have stagnated over the past 15 years, Mr. Autor said. The concern among economists shouldn’t be machines soon replacing humans, he said: “The real problem I see with automation is that it’s contributed to growing inequality.”

Mr. Autor and other experts say much of the new technology are tools to make workers more productive, not replace them. Markets will yield new, yet-to-be-imagined work, they said, and, according to modern economic history, plenty of jobs.

The short- and long-term impact of technology is debated at MIT, where research labs hatch much of the hardware and software reshaping markets.

Landmark breakthroughs by MIT scientists include Marc Raibert ’s development of robots with “dynamic” balance, without which the machines would tip over constantly. Another colleague, Rodney Brooks, made “Genghis” in the late 1980s, a six-legged clambering robot inspired by spiders and now in the Smithsonian.

MIT campus scientists and economists meet regularly to discuss the implications of their work. The talks started after Mr. Brynjolfsson co-wrote a 2011 book that spelled out his epiphany about automation’s new era. The book noted that only six years before Google’s startling driverless car announcement, fellow MIT economist and automation expert Frank Levy had published a well-regarded book that said driverless cars were impossible.

Mr. Levy wasn’t happy to be singled out that way, he said, and was hardly a Luddite. The subtitle of his book is: “How Computers Are Creating the Next Job Market.” Mr. Levy stands by the idea that automation’s advance to uniquely human tasks, including driving, won’t happen as fast as many predict.

The debate inspired him to get economists and scientists talking. MIT robotics professor John Leonard helped set up the meetings, which are held about once a month. Topics span the prosaic—warehouse robots—to the philosophical—What happens if there is no meaningful work for humans?

A recent session featured Henrik Christensen, head of the Georgia Institute of Technology’s robotics program and a specialist in industrial robots. Automation is spreading to factories world-wide, and China recently overtook the U.S. as the world’s largest market for robots, he told the group, packed into a room in MIT’s Frank Gehry-designed computer-science center.

“Most truck drivers won’t have those jobs 10 years from now,” said Mr. Christensen, who is especially bullish on self-driving cars. He predicted children born today won’t need to learn to drive but will find plenty of jobs.

Automation may move slower than many expect. Bank ATMs spread quickly throughout the U.S. over the past three decades, but the number of tellers has only recently declined. In 1985, the U.S. employed 484,000 bank tellers, compared with 472,000 in 2007—reflecting the growth in banking. Since the recession, the number has fallen to 361,000.

Scott Stern, an MIT economist who spoke to the group last year, is among those who believe that technology may have reached a tipping point. He had once thought the latest wave of automation would crest gradually, he said, “playing out along the lines of prior technological transitions.”

But technological advances are moving at a faster speed, Mr. Stern said, with unpredictable results.

The large question under debate by scientists here is how close are breakthroughs that will allow robots to interact with humans in complex tasks.

One group at MIT says computing capacity is the only barrier. The world is building vast pools of data and computing muscle that, this view holds, will soon enable machines to do jobs that previously required skilled people.

Others say scientists are far from translating common sense, sight and dexterity into a string of code. Absent that, computing power won’t help.

Automation skeptics:
Mr. Leonard, the robotics professor who helped initiate the talks with economists, is skeptical such breakthroughs will come soon. “There’s something about robots that makes people think we’re close to Arnold Schwarzenegger and the Terminator movies,” he said.

To make his point, Mr. Leonard mounted a camera on his car’s dashboard to record his daily commute. The idea was to collect an inventory of the sort of unexpected events a computer would face while driving.

Snapping open his laptop, Mr. Leonard showed a series of images from his dash-cam that would confound a machine, he said, including a left-hand turn in traffic. The 49-year-old professor said driverless cars won’t be able to navigate busy city streets in his lifetime.

Bill Freeman, a professor of engineering and computer science at MIT, joins colleagues from the campus during a meeting last month about new frontiers in automation.

Google recently gave Mr. Leonard a ride in a driverless car, and he compared the experience to the Wright brothers’ flight at Kitty Hawk. “It was a remarkable event,” he said of the first flight. “But look how long it took” to reach commercial air travel, he said, aviation’s lasting economic transformation.

The first time automation spawned fears of a jobless future might have been in the 19th century, when English textile workers attacked the first mechanical knitting machines. They were right to fear the contraptions, which eventually replaced them. Another wave of fear hit in the 1960s, when industrial robots began to eat into U.S. manufacturing for the first time.

Yet a recent survey of top economists by the University of Chicago found 88% either agreed or strongly agreed that automation has never historically led to reduced U.S. employment.

Economists in the minority are often said to embrace the so-called lump of labor fallacy: that the amount of work is finite. To date, the job market hasn’t worked that way. Some new machines are so efficient they push down prices and create more demand—which in many cases spawns more jobs, not fewer.

The invention of the automobile threw blacksmiths out of work, but created far more jobs building and selling cars. Displaced workers with obsolete skills are always hurt. but the total number of jobs has never declined over time.

That seems to be the case at Rio Tinto’s Australian mines. John McGagh, the company’s head of technology and innovation, said the surge of automation began about a decade ago, made possible by “more powerful computer chips and highly accurate GPS.”

The new equipment cut many driving jobs, of course. But the reductions will be partly offset by new types of work. The company now needs more network technicians, Mr. McGagh said, and “mechatronics engineers,” a hybrid of electrical and mechanical engineering that hardly existed five years ago.

The robot at Aloft hotel in Cupertino, Calif., covers errands. It trundles items to guests from the front desk, weaving pilotless through hotel corridors. The machine has a compartment kept locked until it reaches the guest’s door. Instead of knocking, it calls the room phone and waits.

No tipping is required. But a built-in screen asks guests for a rating. The robot chirps “Wheee” for a good rating, jiggling back and forth on its wheels.

“We considered having them talk,” said Steve Cousins, chief executive of Savioke, the robot’s creator. “But the issue is, if it talks to you—you’ll assume it understands you.” That remains a skill monopolized by hotel employees.

Small Businesses Embrace Technology to Boost Efficiency—with Robots.

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Dec. 26, 2014



ZURICH—A German brewer established in the 1790s has found a 21st-century answer to increasing profitability: robots

Nine years ago, Badische Staatsbrauerei Rothaus AG was struggling with production bottlenecks that weighed on its profits. Workers couldn’t package and crate the company’s beer quickly enough to stock bars and supermarkets, prompting customers to buy other brands.
Since introducing an ABB Ltd. IRB7600 robot in 2005, however, the company has sped up its delivery times, particularly at peak holiday periods. The robot does the heavy lifting, sorting through 30,000 bottles an hour, allowing the company to reassign its human employees to its bottling and packaging operations.

“We wanted to increase production and efficiency” across the company, Chief Executive Christian Rasch said on a recent Wednesday as a robot painted in the company’s signature traffic-light red stacked cases of beer behind him. The brewery, which hasn’t changed its recipe in more than two centuries, was so impressed it bought four more ABB robots.

ABB, Fanuc Corp. and other robot makers are counting on Rothaus and a variety of small and medium-size companies to fuel the next leg of their growth. Historically driven by automobile companies and electrical-and-electronics makers, robot companies are finding many smaller businesses want to automate dirty and repetitious tasks that were typically handled with good old-fashioned elbow grease.

In Murten, western Switzerland, a local bakery is using robots to bag pretzels, grabbing them off the production line while they’re still hot. In the U.K., a Yorkshire brickworks has robots removing fired blocks from the kiln. In a New York hotel, robots have begun serving as porters, delivering luggage to guest rooms.

Data on the use of robots at smaller companies is hard to come by, and automobile and electronics manufacturers remain the industry’s biggest customers. But the International Federation of Robotics, an industry association, said sales to all industries excluding the big buyers rose 10% in 2013, with growth coming from the metal, food-making and chemicals industries. By comparison, sales to the auto industry rose 4%. Sales of robots rose 12% to $9.5 billion, while sales of robot systems, which includes conveyor belts and other machinery, were $29 billion.

Robot makers are trying to encourage small companies by making their machines easier to use. Many are concentrating their research-and-development efforts on streamlining interfaces so that novices feel comfortable operating them.


‘The vision is for us to make robots as simple to use as a smartphone.’
—Per Vegard Nerseth, who runs ABB’s robot division

Zurich-based ABB is working on a robot that customers can program by moving the arms to perform a desired action, the same way a parent might guide a child assembling blocks. The company, which expects to bring the new robot to market in April 2015, wants to eventually build one that doesn’t require an instruction manual.

“The vision is for us to make robots as simple to use as a smartphone,” said Per Vegard Nerseth, who runs ABB’s robot division. “A lot of the smaller companies, such as bakeries,” he said, “may have qualified bakers, for example, but not lots of robot technicians.”

Japan’s Fanuc overcame skepticism at Marshalls , an Elland, England-based building-supply company, by offering the potential customer a trial robot for six months. Marshalls used the robot to perform a chore that was unpopular with its human employees: placing concrete slabs in an oven and removing the blocks after they’ve been baked.

After six weeks, Marshalls could see the Fanuc R2000iB robot was making a difference and placed an order for five. Since then, it has bought more and now has 63 robots toiling at its 11 plants.

Chris Sumner, who runs Fanuc in Europe, estimates roughly 80% of Fanuc’s European customers are small and midsize businesses, and the number is growing by 20% every year. Small businesses generally buy one or two robots at a time, but Fanuc is trying to encourage more automation: The company runs training classes for customers considering a robot and set up a dedicated hotline for its smaller customers.

“Small companies are concerned they will not get the service of the bigger customers,” Mr. Sumner said. He says Fanuc can devote more resources to servicing smaller enterprises because many bigger companies have in-house engineers.

Kuka AG , a German robot maker, has about 7,500 orders for robots in Germany, roughly a fifth of which are for smaller projects, according to Joerg Winter, who runs sales in the country. Many of those customers are small and midsize businesses, a customer segment that is growing, he says. Kuka robots range in price from €13,000 ($15,800) to €200,000.

At Rothaus, the German brewer, robots have helped the company speed up packaging and overcome staff shortages, a problem in the sparsely populated Black Forest region.

Before the robot—nicknamed Roger-Tor after the manager of the packaging line—was introduced, employees were unloading 24-bottle crates of beer and repackaging them into more-popular six-packs. Over the course of a day, workers would slow down and become more prone to dropping bottles.

Now, the output has climbed to 250 million bottles a year, four times its output 20 years ago. Sales reached €80 million and pretax profit hit €20 million in 2013.

The company has since installed robots at its filling plant. The robots lift kegs for cleaning and then fill them with beer. The robots then sort the full kegs, which weigh 139 pounds, for delivery.

“Nobody wants to do this boring, heavy work,” said Mr. Rasch, the chief executive. “We couldn’t imagine living without a robot.”