Category Archives: Automation

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Thanks to automation a life of potential leisure beckons whether we like it or not.

Once one combines the advances in computing, big data mining, artificial intelligence, speech recognition, driverless vehicles and robotics it's not too hard to foresee that the impacts of the digital technology revolution may have, to date, been simply a clearing of the throat.

Don't just take my word for it, A 2016 report titledTechnology at Work v2.0: The Future Is Not What It Used To Be, prepared for global finance giant Citi, stated that "a job is considered to be 'exposed to automation'or 'automatable'if the tasks it entails allows the work to be performed by a computer, even if a job is not actually automated". On that basis, the researchersfound 47 per centof current US jobs at risk.

According to Futurist.com, Organisation for Economic Co-operation and Development(OECD) data shows that, averaged across the world, 57 per centof jobs are susceptible to automation. This rises to 69 per centin India and 77 per centin China.

The low-risk jobs tend to be those which emphasise social orcreative skills. Which puts me in mind of the cuts to funding for the humanities subjects over the last few decades. Can you spell"irony"?

Commenting on the Citi report, one expert said: "Focus less on pure academics, and more on creativity and presentation skills. The enormous likelihood is that however good you are at STEM subjects there are likely to be people in the world who are infinitely better than you this is to say nothing of the computers that will eventually take over all STEM related roles. Communication skills, creativity and the ability to adapt to change are hugely more valuable and a much better differentiator medium term."

In other words, an emphasis on levels of education and a shift in the educational areas of importance are going to be needed to prepare people for employment in a highly automated future.

This is usually the point where one starts to hear some variation on the words "strong leadership will be required to help us meet these challenges". Feeling confident anyone?

In his book, The Collapse of Complex Societies(1988) historian Joseph Tainter examines the collapse of three complex, sophisticated societies, the Western Roman Empire, the Chacoan and Mayan civilisations. Heposits, broadly speaking thatpast a certain point of complexitysocieties do not collapse despite their levels of sophistication but because of them.

While "collapse" is perhaps an overly dramatic term, we have already seen the struggles that numerous industries media in particular have faced when confronted with digital disruption. If the impacts of automation hit harder and faster than what we have already seen, will there be the ability or the will or the consensus to pivot with the necessary speed?

How will the transitions be managed? Even if the idea of a universal wage gains traction, how will governments generate revenue to supply it if their taxable base starts to dramatically dilute?

Drawing on Keynsian parallels, Andy Haldane, Chief Economist for the Bank of England said in 2015 that a longer-term solution to countering the impact of automationwould be to embrace "a world of progressively shorter working weeks, where mini-breaks become maxi-breaks".

Mind you, he also pointed out that the lowest paid jobs would be at the most risk so, a life of potential leisure beckons, assuming you don't starve.

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Will the robots ruin us? - The Sydney Morning Herald

Forbes

How To Apply The Right Automation And Reporting Tools To Your Business Forbes Automation, or the act of utilizing technology to oversee and simplify repeatable tasks, may seem most common in the manufacturing industry. The truth, however, is that automation can be employed in all fieldsand across many departmentsto provide ...

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How To Apply The Right Automation And Reporting Tools To Your Business - Forbes

Enterprise Irregulars (blog)

Japan: The Land of Rising Automation Enterprise Irregulars (blog) And back to our emerging coverage of Asia/Pacific where people tend to focus on China, India and Australia. However, the Japanese IT services market is larger than these three markets combined and is growing. So, let's have our Asia/Pacific ...

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Japan: The Land of Rising Automation - Enterprise Irregulars (blog)

These days, theres no shortage of news about 3D printing and innovations in advanced manufacturing. From design enhancements to a hybrid approach to automated composite part production to changing business modelslike, UPS adding 3D print services to its package delivery services. All of this indicates that the industry is on the fast track to move 3D printing from prototyping to production.

The latest announcement from SAP reinforces the role of 3D printing in the future of manufacturing. This week at Hannover Messe, the software company unveiled SAP Distributed Manufacturing, a new application that provides a cloud-based scalable process for manufacturers of all sizes. It is a collaborative business network that enables manufacturers to collaborate with 3D printing companies, service and material providers and OEMs.

This offering is part of the recently launched SAP Leonardo portfolio for the Internet of Things and works through integration with the SAP S/4HANA cloud that delivers business process automation as a service. SAP has partnered with 12 printing service providers, including UPS, which it has been working with for a year now.

For a fee, customers log on, upload a design, and have their approved vendors collaborate to set quality requirements. This offering may seem strange coming from SAP, an enterprise software company, but the company views 3D printing as a disruptive technology that impacts both manufacturing and the supply chain.

We want to be an enabler for bringing this technology to our customers, said Mike Lackey, SAPs global vice president of solutions management for IoT and digital manufacturing.

Now, manufacturers are not inhibited by how many 3D printers they own because they have multiple service providers available to them that can accommodate many different materials. This opens the door to creativity and flexibility.

Beyond the prototype it brings 3D printing into repair, spare parts and production, Lackey said. Customers want lot sizes of one. They want to buy products that are made for them and with 3D printing you dont have to have things in inventory. You can make it on-demand.

Looking at UPS as an example, they have local stores with 3D printers, including a 3D printer factory in their distribution hub in Louisville, KY. They can have something printed at 4:00 a.m. and have it delivered to your door, Lackey said.

As part of this weeks announcement, SAP also expanded its partnerships with HP and Jabil. HP plans to collaborate on eliminating friction in the process of evaluating and sourcing 3D print technology through integration with SAPs enterprise systems and network of partners. And Jabil is co-innovating as both customer and partner with SAP to create end-to-end industrial digital manufacturing with real-time visibility to the machine level on the production floor. Combining Jabils manufacturing expertise with SAP Leonardo and manufacturing solutions, Jabil can create a digital twin to effectively manage the entire lifecycle of a part from design to production and recycling.

Among the first to collaborate with SAP in auditing and certifying the processes of 3D printing service providers in the network is TV NORD, a Hannover-based technical services provider with operations in more than 70 countries, which plans to offer ISO 9001 certification adapted for distributed manufacturing.

For customers its enormously important that the manufactured components should be of consistently high quality so that they can be safely and reliably used, said Ulf Theike, general manager of TV NORD Systems. To this end, demonstrably reliable processes and certification from trusted providers provide assurance that customers require.

SAP has been conducting pilot tests with 45 customers for the last six months. As of this week the SAP Distributed Manufacturing service has officially launched.

Originally posted here:

The New Distributed Manufacturing Model - Automation World

Written by Johnson T A | Bengaluru | Published:April 25, 2017 2:02 am

Last week following a presentation at the Bengaluru office of a multinational US software services company on robotics and automation, a few software engineers asked a vice president of their group whether it would be possible to delay implementation of automation in their areas of work. They were sure that their jobs would be in danger if the automation processes that were proposed were implemented, says the senior company official.

While issues like regulation of H-1B visas for Indian software professionals to work in the United States tends to dominate the discourse on job concerns in the information technology world thousands of tech jobs have been rendered redundant in India over the last couple of years with machines taking over the responsibilities of human workers.

If eight people were needed to insert a correction into the software code for a client on the cloud at the peak of the cost arbitrage model, a machine can do it now. The jobs of eight people have become redundant. That is what automation is doing and this is challenging the business models of traditional IT companies, says Ravi Prathap a software engineer and founder of a tech start up.

Last year Infosys Ltd is reported to have automated as many as 9,000 jobs with the company reporting the release of as many as 2,700 workers from automated jobs in the third quarter alone. The software business at Wipro Ltd is reported to have seen as many 4,500 jobs automated last year. The CEO of Wipro Ltds software business Abidali Z Neemuchwala and the CFO Jatin Dalal have in recent times stated that the firm is investing aggressively in its automation suite Wipro HOLMES. The firm is estimated to have asked as many as 350 people to leave on performance considerations in the last quarter.

Infosys Ltd which at the end of March 2017 had 1,88,665 employees added only 6,336 employees last fiscal compared to 16,283 in 2015-16 and 14987 in 2014-15

My personal view and all of us share this view is that automation and AI are perhaps larger forces to catch on to, more than any other specific disruption that will take place either industry specific or US visa regime or any Brexit or anything like that, Sandeep Dadlani, Head Infosys Americas, said recently.

With automation, the number of people we are hiring will not be the same. It will slow down a little bit, says Krishnamurthy Shankar the Group Head, Human Resource Development at Infosys Ltd.

One of the things that people in the IT world are advising young graduates coming out of engineering colleges to join the IT service industry is to develop skills in cloud computing security and network security which will continue to be in demand despite automation.

We must embrace automation. We must stay in automation. We must become masters of it. We can only do that through skilling and through education We have to become entrepreneurial, says Infosys Ltd CEO Vishal Sikka.

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IT automation: Taking toll on jobs and fresh hiring - The Indian Express

For Utah to stay competitive in an age of automation, the state needs thousands of more educated workers, rather than protectionist policies.

Shentong Express, a Chinese delivery company, recently released a video showing an army of small, round, orange robots sorting packages. The robots are capable of sorting 200,000 packages in a single day, and they are self-charging, so they never stop working. The video is an amazing demonstration of technological innovation, but it should also serve as a visceral reminder that Utah and the nation are not adequately prepared to adapt to a changing global economy.

In the first decade of the 21st century, the United States lost more than 5.6 million manufacturing jobs. Its not surprising, then, that President Donald Trumps campaign was uniquely appealing to blue-collar workers who were encouraged by promises of trade deals that would restore the glory days of American manufacturing.

But according to a study conducted by Ball State University s Center for Business and Economic Research, roughly 85 percent of those jobs were lost to automation, not foreign workers. Thats why manufacturing productivity has increased at a much steeper rate than jobs have declined.

This trend is likely to accelerate in the years to come. At last years World Economic Forum in Davos, Switzerland, experts predicted that technology and automation would eliminate as many as 7.1 million more jobs by the end of the decade. Given that robots are much cheaper and less demanding than human beings, that means that, regardless of any trade agreements, most of those jobs simply arent coming back.

Its worth remembering, however, that America has been through this kind of economic shift before. General Motors started using robots to make cars back in 1961, and increased assembly line automation has been ongoing ever since. Yet human beings are still a vital part of that process, although their contributions require more skill and training than they did before robots were put on the assembly line. The same will undoubtedly be true in the economy going forward.

It is simply not possible to freeze an economy to preserve jobs that have become technologically obsolete. The best response to changing economic conditions is training to help displaced workers find new jobs that robots cant do. The government will be more successful in helping citizens find meaningful work if they increase both the availability and quality of education rather than trying to isolate the American economy through protectionist trade deals. In addition, universities and trade schools would do well to tailor their curricula to meet the modern job market.

Firing all those robot workers sorting packages may save some unskilled jobs in the short term, but its a long-term recipe for disaster. In an economy with increasing automation, adaptation through education is the best solution.

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In our opinion: Utah must plan for a new era of automation | Deseret ... - Deseret News

For business people, AI presents a variety of challenges. On a technology level, artificial intelligence and machine learning is complicated to develop and demands rich data sets to produce meaningful results. From a business perspective, many business leaders have difficulty figuring out where to apply AI and even how to start the machine intelligence journey.

Making matters worse, the constant drumbeat of AI hype from every technology vendor has created a continual barrage of noise confuses the market about the real possibilities of AI.

To cut through this noise, I have invited many world-leading practitioners to share their expertise as part of the CXOTALK series of conversations with innovators.

For episode 219 of CXOTALK, I spoke with Michael Chui, a Principal at the McKinsey Global Institute (MGI), and David Bray, an Eisenhower Fellow who is also CIO at the Federal Communications Commission.

The McKinsey Global Institute has released a variety of research reports on topics related to Ai, automation, and jobs. For example, see this article on the fundamentals of workplace automation.

As you can see in the graphic below, Chui and his team examined a variety of industries looking at the impact of automation, including AI, on the workforce.

Image from McKinsey Global Institute

Another fascinating graphic showing automation potential and wages for US jobs:

Image from McKinsey Global Institute

The conversation between Michael Chui and David Bray covered key points about the relationship of business and the workforce to automation and AI including investment, planning, and even ethical considerations.

You can watch our entire conversation in the video embedded above. An edited partial transcript is available below and you can read the complete transcript at the CXOTALK site.

Michael Chiu: More organizations have started to understand the potential of data analytics. Executives are starting to understand that data and analytics are either becoming a basis of competition or a basis for offering the services and products that your customers, citizens, and stakeholders need.

While there are often real technology challenges, we often find the real barrier is the people stuff. How do you get from an interesting experiment to business-relevant insight? We could increase the conversion rate by X percentage if we used this next product to buy an algorithm and this data; we could reduce the maintenance costs, or increase the uptime of this whole good. We could, in fact, bring more people into this public service because we can find them better.

Getting from that insight to capture value at scale is where organizations are either stuck or falling. How do you bag that interesting insight, that thing that you capture, whether in its in the form of a machine learning algorithm, or other types of analytics, into the practices and processes of an organization, so it changes the way things operate at scale? To use a military metaphor: How do you steer that aircraft carrier? Its as true for freight ships as it is for military ships. They are hard things to turn.

Its the organizational challenge of understanding the mindsets, having the right talent in place, and then changing the practices at scale. Thats where we see a big difference between organizations who have just reached awareness and maybe done something interesting and ones who have radically changed their performance in a positive way through data, analytics, and AI.

David Bray: The real secret to success is changing what people do in an organization, that you cant just roll out technology and say, Weve gone digital, but we didnt change any of our business processes, and expect to have any great outcomes. I have seen experiments that are isolated from the rest of public service; and they say, Well look, were doing these experiments over here! but theyre never translating to changing how you do the business of public service at scale.

Doing that requires not just technology, but understanding the narrative of how the current processes work, why theyre being done that way in an organization, and then what is the to-be state, and how are you going to be that leader that shepherds the change from the as-is to the to-be state? For public service, we probably lack conversations right now about how to deliver results differently and dramatically better to the public.

Artificial intelligence, in some respects, is just a continuation of predictive analytics, a continuation of big data, it is nothing new because technology always changes the art of the possible; this is just a new art of the possible.

I do think theres an interesting thing in which it could offer a reflection of our biases through artificial intelligence. If were not careful, well roll out artificial intelligence, populating it with data from humans, [and] we know humans have biases, and well find out that the artificial intelligence itself, the machine learning itself, is biased. I think thats a little bit more unique than just a predictive analytics bias or big data.

Michael Chiu: When we surveyed about 600 different industry experts, every single one of those problems we identified, at least one expert suggested it was one of the top three problems that machine learning could help improve. And so, what that says is potential is just absolutely huge. Theres almost no problem where AI and machine learning potentially couldnt change and improve performance.

A few things that come to mind: One is a lot of the most interesting and recent research has been in this field called deep learning, and thats particularly suited for certain types of problems with pattern recognition, often images, etc. And so those problems that are like image recognition, pattern recognition, etc. are some of those that are quite amenable and interesting.

So again, regarding very specific types of problems, predictive maintenance is huge. The ability to keep something from breaking; rather than waiting until it breaks and then fixing it, the ability to predict when somethings going to break. Not only because it reduces the cost. More important, is the thing doesnt go down. If you bring down a part of an assembly line, you bring down the entire factory or often the entire line.

To a certain extent, that is an example of pattern matching. Sensors are the signals that reflect that somethings going to break, informing you to do predictive maintenance. We find that across a huge number of specific industries that have these capital assets, whether its a generator, a building, an HDC system, or a vehicle, where if youre able to predict ahead of time before somethings going to break, you should conduct some maintenance. That is one of the areas in which machine learning can be quite powerful.

Health care is another case of predictive maintenance but on the human capital asset. Then you can start to think, Well gosh! I have the internet of things. I have sensors on a patients body. Can I tell before theyre going to have a cardiac incident? Can I tell before someones going to have a diabetic incident? That they should take some actions which could be less expensive, and less invasive, than having it turn into an emergent case where they must go through a very expensive, painful, and urgent care type of situation?

Again, can you use machine learning make predictions? Those are some of the problems things that can potentially be solved better by using AI and machine learning.

David Bray: There are opportunities for artificial intelligence and machine learning to help the public. I think a lot is going to happen first in cities.

Weve heard about smart cities. You can easily see better preventive maintenance on roads or power generation and then monitoring to avoid brownouts. I think the real practical, initial, early adoption of AI and machine learning is going to happen first at the city level. Then weve got to figure out how to best use it at the federal level.

CXOTALK brings together the most innovative leaders in the world for in-depth conversations about leadership and innovation. See the complete list of episodes.

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(Cross-posted @ ZDNet | Beyond IT Failure)

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McKinsey: AI, jobs, and workforce automation - Enterprise Irregulars (blog)

Rapid advancements in robotics and artificial intelligence technologies over the past decade have stoked concern that machines could eventually take over most, if not virtually all, human jobs.

But there is another, more optimistic view of how the advance of A.I. and automation will impact the economyone articulated by people like Mark Gorenberg (pictured right). Hes a managing director of Zetta Venture Partners, a San Francisco-based firm that invests in intelligent enterprise software startups.

He argues that as A.I.-related technologies advance, itll be increasingly common for machines to work side by side with humans and empower them to perform at a higher level. Technology advances will likely result in fewer jobs in some areas and more jobs in others, he says. Our take is, net, its going to be positive for society and positive for the human condition, he says.

I dont think we should fear these technologies, Gorenberg continues. I dont think A.I. is going to be the chief threat that people fear that just eliminates jobs.

A.I. has become one of the most active technology sectors in the past few years, with venture capitalists and large companies investing heavily in the field. Amid the hype, Gorenbergs comments are worth highlighting because they provide a window into how some investors view A.I. and its potential impact on businesses and society.

Of course, no one can predict with certainty how things will play out. As a Zetta spokesman points out, there are wildly differing estimates for how A.I. technologies might affect human jobs. A paper published last year by the Organisation for Economic Cooperation and Development estimated that an average of 9 percent of jobs across 21 countries could be susceptible to automation. Meanwhile, a University of Oxford study from 2013 estimated that 47 percent of U.S. jobs are at risk of being taken over by computers.

Erik Brynjolfsson, the director of the MIT Initiative on the Digital Economy, thinks that machines could eventually render human workers obsolete in virtually every industry, but that shift will take at least 30 to 50 years to play out. James Bessen, an economist and lecturer at Boston Universitys law school, has written that computers automating tasks doesnt necessarily imply significant job losses. The bigger and more immediate challenge, he has argued, is making sure humans learn the skills necessary to use new technologies.

Gorenberg, a member of MITs board of trustees, says he doesnt know if A.I. technologies will lead to more or fewer jobs overall. But I dont subscribe to the camp that says it is inevitable that it will lead to more, or much more, net unemployment, he says.

Some manufacturing and warehouse work will continue to be automated; self-driving cars and trucks could eliminate the need for many human drivers; and cashiers will likely continue to be replaced by self-service kiosks, Gorenberg says.

But in other occupations, Gorenberg thinks intelligent software and machines will augment the capabilities of human workers and, in some cases, actually help create jobs for people.

In healthcare, more sophisticated technology could enable a larger pool of candidates to attain a job in the industry because the machines will be able to handle tasks that fill in gaps in peoples skills or experience level. One example might be enabling more people to operate ultrasound equipment, he says. He acknowledges that it may be possible that such machines might eventually become sophisticated enough to run themselves without human oversight, but that isnt going to happen any time soon.

Gorenberg gives another example in sales software. His firm has invested in InsideSales.com, a Utah-based company whose software crunches data and helps guide sales employees. The software tries to predict which leads are likely to result in a deal, and it makes suggestions for the wording of sales pitches. The software gets into granular details like assessing whether it makes more sense to call or e-mail a particular target customer, and trying to predict the optimal time of day to contact people, Gorenberg says.

The product has shown the ability to increase customers revenue by as much as 30 percent, InsideSales claims.

Its allowing people who maybe werent as skilled in sales before, now to do better, Gorenberg says. I dont think its going to destroy sales jobs; I think just the opposite.

Gorenberg also sees opportunities for A.I. to lead to new jobs in construction, as cities remake themselves in an era of sensor-enabled infrastructure and self-driving cars. In manufacturing, data scientists and sensor implementation workers are being hired to help factory operations become more efficient and smarter, he says. And as education moves online and becomes more data-driven and personalized, the need for content creators and teaching assistants will increase, he says.

Gorenberg argues that in most cases, businesses are implementing A.I. technologies with the goal of improving their top linemeaning growing their revenuerather than as a way to trim their bottom line by reducing human labor.

I take the position that when a company is able to improve its top line, it gives it more money to spend, and [it] typically hires more people, he says.

Lots of robotics and A.I. software companies these days are touting ways their technologies can aid human workers, rather than put them out of work. New York-based B12, for example, has promoted itself as human-assisted A.I. software. Boston-based Lola is developing a personal travel service that combines human travel agents with sophisticated software. On the hardware side, Boston-area companies like NextShift Robotics and Veo Robotics are trying to make it easier for robots to collaborate with humans.

Robots and humans have really complementary strengths, says Clara Vu, a co-founder of Veo and a former senior software engineer at iRobot. Robots are strong, theyre fast, theyre precise. They can lift things that no human could ever lift. They can put them down with sub-millimeter precision. But dexterity, judgment, flexibilityhumans just way outclass robots in that way.

What that means, Vu continues, is Next Page

Jeff Engel is a senior editor at Xconomy. Email: jengel@xconomy.com

See more here:

Amid Automation Debate, AI Backers Tout Job Creation Potential - Xconomy

As new fiber networks are rolled out to meet the capacity and speeds required by access technologies and high-value services, ensuring quality installation is crucial. In challenging field testing environments, test process automation is one of the most valuable tools available to reduce human error and improve compliance with network operators standards.

Telecom providers know what performance and capacity they need to get out of their networks, whether the fiber use centers around fiber-to- the-antenna (FTTA) or distributed antenna systems (DAS) for wireless fronthaul or fiber-to- the-home (FTTH) residential or enterprise installations. Most operators have detailed documentation on how to construct and validate fiber links to their own specific requirements and network design strategies. These methods and procedures documents, or M&Ps, are often updated and changed to reflect evolving best practices, making it difficult to ensure that all technicians and project teams are working from the most current version. They are also lengthy: typically more than 50 pages. This makes them unwieldy to use on-site and difficult to reference in the field, and it is all too easy for required processes to be missed or only partially completed.

M&Ps also establish labeling regimes and testing thresholds that are unique to each operator and can differ across installation types. For FTTA deployments, fiber identification information often remain the same, but site ID and other parameters change from job to job. DAS and FTTH deployments, on the other hand, are highly variable and require technicians to accurately enter even more data. Technicians try to avoid mistakes, but repetitive data entry is a difficult task in the field: tests may need to be performed with multiple test sets that have multiple user interfaces, M&Ps cross-checked, and so on. A significant percentage of test results have data-entry errors, from results not being saved or being lost, to tests being skipped, performed to the wrong threshold or associated with the wrong fiber, cable or location.

EXFOs TestFlow turns an inefficient and highly manual field testing approach into one that is consistent and simplified, and makes the best use of valuable time with the following functionality:

1. Managers create M&P-based digitized job definitions with predefined test-point IDs (e.g. for fiber/bulkhead connectors), required tests (e.g. fiber-connector inspection) and applicable test configurations with design pass/fail thresholds for techs to successfully complete on-site work.

2. Managers distribute jobs to techs test units and mobile devices.

3. Technicians run consistent job-specific test sequences using an all-in- one intuitive test-unit / mobile-device application with a single user interface and support for multiple tests and measurements without the need of other applications or manuals automated step-by- step tasks and job closeout with dynamic test-sequence reporting and test/task-sensitive instructions.

4. Technicians automatically upload test results with predefined filenames to TestFlows centralized server for results-to- metrics processing and immediate closeout-package audit for completeness.

5. Managers analyze user-defined testing metrics from the centralized TestFlow database using web-based analytics dashboards to verify compliance and review work.

Field test process automation with TestFlow means more productive use of both techs and managers time, improved compliance with operator standards and more accurate and timely data from the frontline, leading to better, faster network deployments.

Learn more about TestFlow by visiting: http://www.exfo.com/testflow

Excerpt from:

TestFlow: Field test process automation for better, faster network deployments - RCR Wireless News