Category Archives: Automation

Taking a page out of the software development low-code/no-code movement, testing automation provider LogiGear Corp. has developed a "code-free" automated testing platform designed to make it easy for nearly anyone to achieve scriptless test automation.

At a time when companies of all sizes are moving to a DevOps approach from software development, the need to automate testing has never been greater. A Forrester Wave report in 2016 on functional testing automation tools said companies need to automate 80% of testing, leaving only 20% manual. But the research showed just between 42% and 45% of Agile companies are automated.

To look at it a bit differently, a 2016 research paper written by Divya Kumar and K.K. Mishra, titled "The Impacts of Test Automation on Software's Cost, Quality and Time to Market," indicated testing is the most expensive part of the development process. According to an email interview with Kumar, nearly 60% of the money spent on developing software is used for different types of software testing. So, despite the initial costs of setting up test automation, it pays for itself very quickly, he said.

LogiGear's new product, TestArchitect Team, is designed to achieve scriptless test automation for small businesses and will be free for two users, said Hung Nguyen, CEO of LogiGear, based in Foster City, Calif. "We think it's good to get more people to have access to automation options, even though they often look at ways of finding tools that can be free," Nguyen said. "Now, we offer a free solution that is beyond open source. Our 'freemium' version offers full features, and we also gain the advantage of having more engineers using the product, so it's beneficial to everyone."

Though the company's core user base is large companies, Nguyen said small companies need scriptless test automation, too. "In many situations, you have a developer who's also a product manager and a project manager and a tester and a customer support person. That's the real world, and giving this tool to this person gives him or her the automation ability to keep up."

To make TestArchitect Team work in a low-code/no-code or scriptless test automation way, Nguyen said the company took two approaches. The first step was to identify which are the most common command functions and translate those in to a businesslike language in English. Using natural language was key. "It's the old-school way of thinking that you write tests and run them. Today, it's you write the test and somebody else may run them, and if it fails, they have to have the ability to understand what your test was doing and how to analyze the results," Nguyen explained.

The second part of the process was to ensure a tester could create brand-new testing scenarios by choosing among prescripted actions. "It's like taking different blocks of Legos and slapping them together to create something new," Nguyen said.

The goal for TestArchitect Team is to open the world of testing to anyone on the development team. "This is very different from any approach we're seeing out there," he said. "By using action-based language, we're making the potential staff writing the tests huge. Now, companies are going to have a larger pool of resources."

What is a citizen developer, and why should you care?

A primer on software testing automation

It's a low-code world, but you need to learn to code -- here's why

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LogiGear's new scriptless test automation tool targets small businesses - TechTarget

Reason writer Ronald Bailey outlines a strong case that fears about technological unemployment are overblown. For instance: He adds needed context to the recent finding by MIT economist Daron Acemoglu and Boston University economist Pascual Restrepo that each additional industrial robot in the United Statesresults in 5.6 American workers losing their jobs.

But even taking the high-end estimate, job loss due to robots was has been just 670,000 since 1990 while last year some 62.5 million Americans were hired in new jobs, while 60.1 million either quit or were laid off from old ones, according the Bureau of Labor Statistics. I would add that total nonfarm employment over that span has increased by nearly 40 million.

A passenger stands in front of a row of Cathay Pacific Airways self check-in machines in Hong Kong Airport March 10, 2010. REUTERS/Tyrone Siu.

And Bailey on the basic economics that shock stories often miss:

When businesses automate to boost productivity, they can cut their prices, thus increasing the demand for their products, which in turn requires more workers. Furthermore, the lower prices allow consumers to take the money they save and spend it on other goods or services, and this increased demand creates more jobs in those other industries. New products and services create new markets and new demands, and the result is more new jobs.

Pessimists also fail to appreciate our inability to imagine what future jobs look like, a failing that stems from our inability to imagine future technology and its uses. Bailey cites research from economist Michael Mandel that in the decade since the advent of the smartphone, the app economy now supports nearly two million jobs.

Let me end with this bit from Bailey that quotes economist David Autor:

Imagine a time-traveling economist from our day meeting with Thomas Edison, Henry Ford, and John D. Rockefeller at the turn of the 20th century. She informs these titans that in 2017, only 14 percent of American workers will be employed in agriculture, mining, construction, and manufacturing, down from around 70 percent in 1900. Then the economist asks the trio, What do you think the other 56 percent of workers are going to do?

They wouldnt know the answer. And as we look ahead now to the end of the 21st century, we cant predict what jobs workers will be doing then either. But thats no reason to assume those jobs wont exist.

I cant tell you what people are going to do for work 100 years from now, Autor said last year, but the future doesnt hinge on my imagination.

(For more on the issues surrounding automation, a relatively recentpiece from the Richmond Fedis worth reading. Itlooks at things through the lens of how driverless vehicles might affect truck drivers.)

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A techno-optimist take on automation and jobs - American Enterprise Institute

Smaller Canadian regions that specialize in mining, manufacturing, and other natural resources jobs are most vulnerable to automation, according to a new report from Brookfield Institute for Innovation and Entrepreneurship (BII+E).

For the report, Automation Across the Nation: Understanding the potential impacts of technological trends across Canada, the Brookfield Institute applied findings from a recent report by McKinsey & Company on automation to employment figures from the 2011 Statistics Canada census, the most recent account of local labour statistics. Specifically, the Brookfield Institutes report aims to identify the Canadian cities and towns, as well as specific industries, that are most likely to be impacted by automation.

We expect that the impact of automation will vary considerably across Canadas towns and cities, said Sean Mullin, executive director of BII+E. By better understanding the geographic distribution of this trend, we believe the country will be much better prepared to weather the risks and reap the potential benefits of automation.

Industries most likely to be impacted by automation include accommodation and food services.

The report revealed that overall, 46 percent of work activities in Canada have the potential to be automated, across all industries, a figure that is equivalent to 7.7 million jobs. When it comes to specific industries, however, the report found that small regional economies that specialize in manufacturing or mining, quarrying, and oil and gas extraction are most susceptible to automation.

Some of these regions included Woodstock, Ontario, where 49.5 percent of work activities have the potential to be automated; Ingersoll, Ontario, where 50 percent of the work has the potential to be automated; and Quesnel, BC, where 49.64 percent of work activities have the potential to be automated.

On the contrary, the cities and towns that are less susceptible to automation are areas with a large hospital, post-secondary institution, or public sector presence such as Petawawa, Ontario, Ottawa-Gatineau, Ontario, and Fredericton, New Brunswick.

Diving further into specific industries, the report found that industries most likely to be impacted by automation also include accommodation and food services; transportation and warehousing; and agriculture, forestry, fishing and hunting. According to the Institute, the proportion of work activities in industries with the potential to be automated is equal to 2.5 million jobs.

Large cities like Toronto, Montreal, and Vancouver lie in the middle of the pack. The report suggested that while about 46 percent of work activities in these regions have the potential of being automated, workers displaced by automation may have an easier time finding new jobs as these cities tend to specialize in professional, scientific, and technical services.

Overall, the report suggests that while automation will bring certain benefits, it will also bring significant risks for individual Canadians and communities, particularly for Canadas smaller cities and towns.

While the rate and extent of adoption of different technologies across industries is unknown, the benefits, as well as the job displacement risks resulting from automation, are likely to be more concentrated in certain industries, and in certain cities and towns, the report reads. This suggests a need to more deeply understand the areas and people that are most at risk, and to design policy and program responses, including in the areas of training, upskilling, education, and social safety nets, that take this uneven distribution of risk into account.

The Brookfield Institute plans to continue examining the differentiated impacts of automation on various regions and individuals across Canada in the coming months.

This is not the first time the Brookfield Institute has examined the relationship between automation and jobs. In March, the Brookfield Institute and RBC released a report that found that people aged 15 to 24 are one of the population segments most likely to experience changes in job roles and skills demand due to automation. They reportedly make up nearly 20 percent of employees that have a high risk of being impacted by automation.

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Report: Smaller Canadian towns most likely to be impacted by automation - BetaKit

When people think of future technologies that will change our lives, robotics and the general trend towards more automation is usually at the top of the list. And while some of the more sci-fi aspects of this technology still appears to be in the future, robotics and automation is already an important industry, and one that could surge in status in the years ahead as well.

The space is probably a lot bigger than you think too. Sure, most are familiar with companies like iRobot (IRBT - Free Report) , but the industry goes beyond vacuuming and pool cleaning robots at this point. In fact, many big-name players are getting into the robotics world, and it looks to be a high growth area for quite some time.

To learn more about this growing trend, I spoke with Bill Studebaker, the CIO and President of Robo Global. This company was the first to create a benchmark index to track the global robotics and automation market, acting as a barometer for companies across the space, and making Robo Global a firm in the know about the world of robotics and automation.

Investing in Robotics

Bill and I discuss the key growth areas of the robotics and automation world, as well as some of the top reasons for the greater push towards robotics as of late, including the prospect of rising wages. We also talk about how this industry may have reached a critical mass in recent years, and what this means for investors too.

We also look at what the hot areas of the robotics world are, and I get Studebakers take on Bill Gates recent commentary that we may have to consider taxing robots in the near future. We then investigate what is ahead for this industry, and why an index-based approach might make sense in this high-growth and higher-risk corner of the market.

Index in Focus

The index is also the basis for the Robo Global Robotics & Automation Index ETF (ROBO - Free Report) , the most popular fundby assetsto track the space in the ETF world. We dive into the underlying benchmark in this podcast and I investigate how securities are chosen and weighted for the index.

This is especially important when you take a first glance at the index components for the benchmark, as some companies that make their way into the benchmark include large and well-known firms like Deere (DE - Free Report) and Northrop Grumman (NOC - Free Report) to name a few. We go over why these are in the index, as well as the wisdom behind including a number of semiconductor stocks such as Nvidia (NVDA - Free Report) , Qualcomm (QCOM - Free Report) , and Ambarella (AMBA - Free Report) too.

We also talk about the significant foreign exposure in this index, and why Japanese companies account for such a large portion of the benchmark as well. Finally, we talk about the market cap breakdown for companies in this space, and what could be ahead for this growing area.

If youve been interested in the world of robotics and how to invest in this space, definitely check out this podcast for a great guide to the industry!

Bottom Line

But what do you think about the world of robotics? Is this something youve considered for your portfolio? Make sure to write us in at podcast @ zacks.com or find me on Twitter@EricDutramto give us your thoughts on this, or anything else in the fund market.

But for more news and discussion regarding the world of investing, make sure to be on the lookout forthe next edition of the Dutram Report(each and every Thursday!) and check out themany other great Zacks podcasts as well!

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Zacks free Fund Newsletter will brief you on top news and analysis, as well as top-performing ETFs, each week.Get it free >>

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Guide to Investing in Robotics Stocks: What's the Future in Automation? - Zacks.com

Nearly half of Canadas work activities could be automated, and the communities most susceptible tend to have smaller populations with an outsize share of manufacturing or natural resources jobs, according to a newreport.

On the other hand, the Canadian areas best insulated from tech disruption include those where hospitals, postsecondary institutions and the public sector are major employers, the Brookfield Institute for Innovation + Entrepreneurshipfinds.

The Toronto-based think tank applied McKinsey & Company data on automation to employment figures from the 2011 census, the most recent account of local labour statistics. (Labour figures from the 2016 census will be released inNovember.)

Census metropolitan areas with a higher share of non-routine work activities were less likely to be disrupted, the reportsays.

For example, one-third of Ottawa-Gatineau employees were working in health care, education services and professional scientific and technical services three industries that rely on human interaction and management. As a result, 44 per cent of the work activities in Ottawa-Gatineau had the potential to be automated, according to the study, making it the second-least susceptible area out of147.

In contrast, one-quarter of Ingersoll, Ont., employees were working in manufacturing and one-fifth in retail, restaurants and accommodation industries with highly repetitive tasks. The study found that 50 per cent of the work in Ingersoll had the potential to be automated, making it the area most at risk in thecountry.

Where does your city rank? Use the searchable table below to find out, or tap the column headings to order thefigures.

Source: BII + E

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Automation nation: Which Canadian communities are most at risk? - The Globe and Mail

This Axios headline is problematic: Summers: Automation is the middle class worst enemy.

The accompanying piece doesnt actually quote economist Larry Summers making that declaration. Rather it summarizes an interview in which Summers indeed points out the challenge automation poses for workers. Hes right. Of course thats been the case for the past 200 years and will likely be the case for the next 200. But in exchange for a degree of instability and disruption, technological progress has dramatically raised living standards for workers.

Automation is kind of like alcohol, which, as Homer Simpson putsit,is the cause of, and solution to, all of lifes problems. Its the job of policymakers to make sure workers are ready to climb to the next footholdor ledge as the waters of automation continue to rise. Its also their job to make sure policy is as supportive as possible of innovation. Indeed, we need more tech progress, not less. The U.S. economy currently suffers not from too much automation, but rather from too little investment in the sort of technology that would raise the countrys lackluster productivity, writesDerek Thompson in an excellent new piece at the Atlantic.

Technology will erase jobs but also create them. Unfortunately, as Kevin Kelly writes, we cant see those jobs from here because we cant yet see the machines and technologies that will make them.

The piece also includes this chart, which shows lower US labor force participation than other advanced economies:

But I doubt whether Summers blames automation vs. the lack of USpolicies that center-left economists see as supporting workers, such as paid leave, and high USincarceration rates. And here is economist David Autor on the net impact of automation on jobs this century:

A final observation is that while much contemporary economic pessimism attributes the labor market woes of the past decade to the adverse impacts of computerization, I remain skeptical of this inference. Clearly, computerization has shaped the structure of occupational change and the evolution of skill demands. But it is harder to see the channel through which computerization could have dramatically reduced labor demand after 1999. My suspicion is that the deceleration of the U.S. labor market after 2000, and further after 2007, is more closely associated with two other macroeconomic events. A first is the bursting of the dot-com bubble, followed by the collapse of the housing market and the ensuing financial crisis, both of which curtailed investment and innovative activity. A second is the employment dislocations in the U.S. labor market brought about by rapid globalization, particularly the sharp rise of import penetration from China following its accession to the World Trade Organization in 2001.

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Is Automation Really the Worst Enemy of the Middle Class? - Ricochet.com

BERKELEY Advances in artificial intelligence and robotics are powering a new wave of automation, with machines matching or outperforming humans in a fast-growing range of tasks, including some that require complex cognitive capabilities and advanced degrees. This process has outpaced the expectations of experts; not surprisingly, its possible adverse effects on both the quantity and quality of employment have raised serious concerns.

To listen to President Donald Trumps administration, one might think that trade remains the primary reason for the loss of manufacturing jobs in the United States. Trumps treasury secretary, Steven Mnuchin, has declared that the possible technological displacement of workers is not even on [the administrations] radar screen.

Among economists, however, the consensus is that about 80% of the loss in US manufacturing jobs over the last three decades was a result of labor-saving and productivity-enhancing technological change, with trade coming a distant second. The question, then, is whether we are headed toward a jobless future, in which technology leaves many unemployed, or a good-jobless future, in which a growing number of workers can no longer earn a middle-class income, regardless of their education and skills.

The answer may be some of both. The most recent major study on the topic found that, from 1990 to 2007, the penetration of industrial robots defined as autonomous, automatically controlled, reprogrammable, and multipurpose machines undermined both employment and wages.

Based on the studys simulations, robots probably cost about 400,000 US jobs each year, many of them middle-income manufacturing jobs, especially in industries like automobiles, plastics, and pharmaceuticals. Of course, as a recent Economic Policy Institute report points out, these are not large numbers, relative to the overall size of the US labor market. But local job losses have had an impact: many of the most affected communities were in the Midwestern and southern states that voted for Trump, largely because of his protectionist, anti-trade promises.

As automation substitutes for labor in a growing number of occupations, the impact on the quantity and quality of jobs will intensify. And, as a recent McKinsey Global Institute study shows, there is plenty more room for such substitution. The study, which encompassed 46 countries and 80% of the global labor force, found that relatively few occupations less than 5% could be fully automated. But some 60% of all occupations could have at least 30% of their constitutive tasks or activities automated, based on current demonstrated technologies.

The activities most susceptible to automation in the near term are routine cognitive tasks like data collection and data processing, as well as routine manual and physical activities in structured, predictable environments. Such activities now account for 51% of US wages, and are most prevalent in sectors that employ large numbers of workers, including hotel and food services, manufacturing, and retail trade.

The McKinsey report also found a negative correlation between tasks wages and required skill levels on the one hand, and the potential for their automation on the other. On balance, automation reduces demand for low- and middle-skill labor in lower-paying routine tasks, while increasing demand for high-skill, high-earning labor performing abstract tasks that require technical and problem-solving skills. Simply put, technological change is skill-biased.

Over the last 30 years or so, skill-biased technological change has fueled the polarization of both employment and wages, with median workers facing real wage stagnation and non-college-educated workers suffering a significant decline in their real earnings. Such polarization fuels rising inequality in the distribution of labor income, which in turn drives growth in overall income inequality a dynamic that many economists, from David Autor to Thomas Piketty, have emphasized.

As Michael Spence and I argue in a recent paper, skill-biased and labor-displacing intelligent machines and automation drive income inequality in several other ways, including winner-take-all effects that bring massive benefits to superstars and the luckiest few, as well as rents from imperfect competition and first-mover advantages in networked systems. Returns to digital capital tend to exceed the returns to physical capital and reflect power-law distributions, with an outsize share of returns again accruing to relatively few actors.

Technological change, Spence and I point out, has also had another inequality-enhancing consequence: it has turbo-charged globalization by enabling companies to source, monitor, and coordinate production processes at far-flung locations quickly and cheaply, in order to take advantage of lower labor costs. Given this, it is difficult to distinguish between the effects of technology and the effects of globalization on employment, wages, and income inequality in developed countries.

Our analysis concludes that the two forces reinforce each other, and have helped to fuel the rise in capitals share of national income a key variable in Pikettys theory of wealth inequality. The April 2017 IMF World Economic Outlook reaches a similar conclusion, attributing about 50% of the 30-year decline in labors share of national income in the developed economies to the impact of technology. Globalization, the IMF estimates, contributed about half that much to the decline.

Mounting anxiety about the potential effects of increasingly intelligent tools on employment, wages, and income inequality has led to calls for policies to slow the pace of automation, such as a tax on robots. Such policies, however, would undermine innovation and productivity growth, the primary force behind rising living standards.

Rather than cage the golden goose of technological progress, policymakers should focus on measures that help those who are displaced, such as education and training programs, and income support and social safety nets, including wage insurance, lifetime retraining loans, and portable health and pension benefits. More progressive tax and transfer policies will also be needed, in order to ensure that the income and wealth gains from automation are more equitably shared.

Three years ago, I argued that whether the benefits of smart machines are distributed broadly will depend not on their design, but on the design of the policies surrounding them. Since then, I have not been alone. Unfortunately, Trumps team hasnt gotten the message.

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Labor Markets in the Age of Automation by Laura Tyson - Project ... - Project Syndicate

The Digital Twin concept is steadily gaining groundin the product development worlda means of creating a virtual representation of physical assets, including modeling behaviorfor validation and test purposes. This process, which promises to reduce reliance on costly prototypes while accelerating time to market, is now starting to take root in the plant floor environment as a way to garner efficiencies for production and, in some cases, set the stage for predictive maintenance.

Unlike the product development space, where the definition is more universal, the concept of a digital twin varies among automation providers, depending on where their offerings fit in the automation stack. Some companies with deep roots in 3D CAD modeling like Dassault Systmes and Siemens see the digital twin as a way to define and optimize factory floor layout and production processes in a virtual world prior to putting physical assets in place and flipping the switch on production.

Other companies like Emerson Automation and Beckhoff consider the digital twin as a tool for validating and optimizing control systems and automation processes in the virtual worlda tactic that lends itself to a variety of use cases, including operator training and virtual commissioning. Other companies, like GE Digital, have a broad and ambitious game plan for the digital twin, leveraging it for everything from asset performance management to predictive and prescriptive maintenance, the latter combining a digital model with Industrial Internet of Things (IIoT) connectivity, real-time operational and historical data, as well as machine learning and analytics.

In an entirely different interpretation, some players conflate the concept of a digital twin with virtualization, the now mainstream IT technology that abstracts operating systems, applications, networks and storage from the underlying hardware or software so the process is no longer dependent on a specific physical platform, allowing for greater flexibility and scale. For example, Wind River Titanium Control is an open standards-based, on-premise cloud infrastructure that creates a digital twin of a plants legacy equipment, allowing it to become a full participant in IIoT by creating a real-time data channel between the traditional physical controllers and automation systems and its virtual representation.

Despite the murkiness of the digital twin concept, one thing is clear: It doesnt constitute any one idea, any single set of simulations or analytics or even a specific product category. A digital twin is a whole set of analytics that look at different aspects of how an asset performs, says Matt Wells, general manager of automation software at GE Digital. What we found is not one analytics model has all the answers.

Twinning thesmart factory Currently, one of the more prominent use cases for the digital twin is validating plant floor layouts and simulating logistic processes as part of a digital manufacturing portfolio. At Dassault, the concept of a connected production digital twin is a virtual 3D replica of an actual physical structurerobots, conveyors, CNC machines and other plant floor assetsalong with a simulation of the actual production processes of a smart factory, according to Prashanth Mysore, portfolio technical director of digital manufacturing at Dassault.

Under pressure to improve quality and responsiveness, reduce costs and strive for continuous improvements, manufacturers have an opportunity with the production digital twin to react more responsively to various internal and external disruptive events driven by mass customization needs. Specifically, Mysore says, manufacturers embracing a digital twin strategy can increase productivity and manufacturing efficiency by reducing variability and synchronizing material. They can also improve quality and compliance by validating processes virtually to ensure they are right the first time in addition to running multiple what-if scenarios to analyze production options and ensure worker safety and productivity.

A 3D replica of the actual physical plant is not the end of the road for the digital twin, Mysore says. The digital twin is also used to connect production with materials management, quality processes, and labor and maintenance processes.

As part of its 3DExperience platform for global industrial operations, Dassault makes its version of the digital twin come to life through its Delmia digital manufacturing portfolio, which includes numerous simulation tools as well as manufacturing operations management (MOM) capabilities resulting from its Apriso acquisition and operations planning and optimization functionality from its buyout of Quintiq.

A digital twin or dynamic software representation of an entire plant or an offshore oil rig, for example, can serve a variety of use cases across an entire automation and process control project lifecycle, according to Ronnie Bains, business manager for dynamic simulation and process optimization at Emerson Automation Solutions. Emerson customers are leveraging digital twins to support the initial design of a facility, to build actual processes and control systems, and to understand whether what is being built can function at the proper throughput.

If youre doing something incorrectly and you dont have such simulation, you dont find out about the potential impact until much later in a projects process, Bains explains. With a digital twin, you can identify areas of concern and design flaws early on and fix them as opposed to when things are built out and its more expensive.

As part of its Multi-Purpose Dynamic Simulator systems, Emersons DeltaV Simulate capabilities allow companies to test control logic and operator graphics in a virtual commissioning scenario, minimizing potential errors and streamlining the startup process. The same technology can also be leveraged to assist in training operators in unique processes. The level to which the digital twin is applied varies from customer to customer, Bains says. For some, its just for training; for others, its the full lifecycle.

For its part, Beckhoff has assembled a set of tools for its TwinCAT automation suite that extends into the realm of digital twin, specifically for upfront virtual testing and commissioning. Via support for the vendor-neutral Functional Mock-up Interface (FMI), Beckhoff has created interfaces between its platform and popular model-based design and simulation tools like MathWorks Matlab and Simulink and Maplesofts MapleSim to allow for acquisition and visualization of real-time parameters while creating a closer connection between physical and digital models. The ability to import simulated code and run it directly on a physical system enables machine builders to test before setup, aiding in reliability and shortening time to market, according to Daymon Thompson, an automation specialist at Beckhoff.

At Rockwell Automation, the whole premise of the digital twin is to remove the need for the physical asset, whether its to test the actual hardware or control systems, notes Andy Stump, business manager for the companys design software portfolio. Rockwells Studio 5000 Logix Emulate software enables users to validate, test and optimize application code independent of physical hardware while also allowing connectivity to third-party simulation and operator training systems to help teams simulate processes and train operators in a virtual environment.

In this context, a digital twin can be employed to provide a safer, more contextualized training environment that focuses on situational experience. It helps with emergency situations, starting up and shutting downthings you dont encounter ever day, Stump explains.

A digital twin of a control system created in the Logix Emulate tool could also be tapped for throughput analysis, Stump adds, ensuring, for example, that a packaging machine could handle a new form factor without having to actually bring down the machine to test the new design. Any time you take a machine out of production, its expensive, he says. If you can estimate that a machine is going to be down 60 percent of the time running what-if scenarios in a digital twin, theres a lot of money to be saved.

Moving forward, Rockwell will leverage new technologies such as virtual reality (VR) and augmented reality (AR) to enhance its vision for a digital twin. At the Hannover Fair in April, the company demonstrated a next-generation, mixed-reality virtual design experience using its Studio 5000 development environment with the Microsoft HoloLens VR headset.

For Siemens, the concept of a digital twin straddles both product design and production. In a production capacity, the digital twin exists as a common database of everything in a physical plantinstrument data, logic diagrams, piping, among other sourcesalong with simulation capabilities that can support use cases like virtual commissioning and operator training. Comos, Siemens platform for mapping out a plant lifecycle on a single data platform, and Simit, simulation software used for system validation and operator training, now have tighter integration to support more efficient plant engineering and shorter commissioning phases, says Doug Ortiz, process automation simulation expert for Siemens. In addition, Comos Walkinside 3D Virtual Reality Viewer, now with connectivity to the Oculus Rift Virtual Reality 3D glasses, enables a more immersive experience, allowing plant personnel to engage in realistic training and virtual commissioning exercises, he says.

Customers want to get plants from the design stage to up and running in the shortest period of time and these tools are paramount for that, Ortiz says. The digital twin is great to use for any plant for the lifecycle of that unique plant.

Improvedmaintenanceopportunities While most companies in the automation space are settling in with the digital twin for roles in operator training, virtual commissioning and optimization, there is still not a lot of activity leveraging the concept for predictive and preventive maintenance opportunities. The exception might be GE Digital, which is clearly pushing this use case as its long-term vision.

GE Digital sees four stages of analytics that will be impacted by digital twin and IoT:

GE Digital showed off a digital twin representation of a steam turbine to showcase what is possible in the areas of predictive and prescriptive maintenance at its Minds + Machines conference last November.

A digital twin is a living model that drives a business outcome, and this model gets real-time operational and environmental data and constantly updates itself, said Colin J. Parris, vice president of software research at GE Globals research center, during the presentation. It can predict failuresreduce maintenance costs and unplanned outages, andoptimize and provide mitigation of events when we have these types of failures.

Though the digital twin is certainly making headway in production, its still in its early days. Digital twin is definitely hot right now, but it really depends on what the customer is trying to achieve and what they are trying to model, says Bryan Siafakas, marketing manager in Rockwell Automations controller and visualization business, adding that its just a matter of time. There is a huge upside in terms of productivity savings and shortened development cycles.

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Digital Twin Spawns Automation Efficiencies - Automation World

Intelligence analysts are swimming in data pouring in from an array of vehicles and platforms a problem that isnt new, but for which government leaders still seek the right solutions.

To help stem the deluge and better position analysts and key mission-critical data, intelligence community officials are targeting automation as a high priority, with a futuristic vision for applications down the road as well.

A significant chunk of my analytic workforce today, I will send them to a dark room to look at TV monitors to do national security-essential work but boy, is it inefficient, Robert Cardillo, director of the National Geospatial-Intelligence Agency, told reporters at the annual GEOINT Symposium in San Antonio, Texas. The number of people needed to maintain awareness of, if not exploitation of, one sensor is really daunting. I suspect were going to get more of those sensors. I cant double my human population in those dark rooms.

The near-term goal particularly centers on analysis of full-motion video that streams in from unmanned aerial systemsthe wolf really close to the door, as Cardillo put it.But he and other officials also are looking toward future uses for different types of automation, including artificial intelligence. And Cardillo, among others, are looking to partner up for help.

As the commercial industry and academic think tanks and advanced science and engineering schools move to artificial intelligence and machine learning, theyre all desperate to get a hold of some data with [which] to train their algorithms and teach their machines to learn, Cardillo said. He added that intelligence community leaders, including those at the NGA, are looking at how to safely expose data sets to accelerate development in automated tools.

But the NGA isnt just looking outside for solutions. Internally, the agency has launched a new Office of Ventures and Innovation aimed at guiding emerging technology from incubation through the entire life cycle.

To get to this automated, augmented future that were talking about, we need to coordinate across a lot of different parts of the agency, Anthony Vinci, NGA director of plans and programs, told C4ISRNET. Its not just a technology issue, its bringing technology and [research and development] into the operational units, into analysis or into the business services units, human development or finance for business analytics.

Vinci said the NGA is working closely with other government agencies, including the Defense Department, to further automation and AI and get to a new level of intelligence and military operations.

How can we use automation to take some of that pressure off of the analysts who are putting together those products? How do we buy back some of their time by automating some of these processes so they can focus on the higher-end analysis that they need to be focusing on? Thats a fundamental thing were trying to do using all the tools at the agencys disposal, Vinci said.

On the higher endthe exquisite analysishow can we bring in modeling and AI and some of those tools that are on the high end of technology to support analysis and do missions that werent even possible until now because we didnt have the tools to analyze that amount of data, or because we couldnt analyze some complex phenomenonologies? How can we bring them those tools and those models?

In a future operational landscape where autonomous vehicles dominate and interact with adversaries, its easy to see where intelligence missions cross over to operational military missions, Vinci noted.

These tools are not just intelligence tools; theyre operational as well. Were not just an intelligence agency, were a combat support agency, so we help across the spectrum, he said. Were a support function to someone who has to make a decision.

"We have to be able to act faster and get as far left of boom as possible.

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Intel officials pin high hopes on automation, artificial intelligence - C4ISR & Networks

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Automation Controllers With MQTT and Analytics Onboard Enable Lean IIoT Architectures - Automation World