Category Archives: Automation

Japantends to be less wary of automation, even in nursing homes.

Japan's next boom may be at hand, driven by the very thing that is supposed to be bad for its economy.

Japan's aging and shrinking populationhas been partly blamed for the on-again, off-again nature of growth and deflation the past three decades. Lately, it's been drivingadifferent and just as powerful idea: In the absence of large-scale immigration, the only viable solution for many domestic industries is toplow money into robots and information technology more generally.

Humans will still be needed, of course, and that's behind a separate by-product of Japan's demographic challenges that I wrote about during a visit there last month. With unemployment down to 2.8 percent, companies are increasingly realizing they need to pay up to attract and keep qualified personnel.The other option -- increased immigration -- is politically difficult.

Japanese tech innovation in yesteryear was about gadgets and games designed to give pleasure. Think Sony's iconic Walkman and Nintendo games. Now the demand in Japan comes from an older demographic. A nursing home may well be the place to look for the next wave.

As my colleagues Henry Hoenig and Keiko Ujikane wrote this week, an owner of nursing homes in the Tokyo area plans to spend 300 million yen ($2.7 million) on software to make life easier for employees and residents.

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Hoenig, Toru Fujioka and I heard anecdotes like that numerous times during a December trip to Kadoma, a city near Osaka. The area was once an industrial powerhouse that rode Japan's post-1945 industrial surge with local employers like Panasonic Corp. Now, Mayor Kazutaka Miyamoto frets openly about whether there will simply be enough wage earners to pay the taxes to maintain hospitals, public transport and schools (for those few children who are born and actually stay).

Miyamoto does not share the worries that dominate conversations about robots and AI in the West. He almost laughed when pressed on the issue in a conversation in his office. What if robots eliminate jobs? He said that would be a good thing. He told us to look around: There aren't many people on the streets in the middle of a weekday.

He doesn't see any real appetite for immigration on a scale that would substitute for more robots and AI. Few businesses we spoke to that day did. One small manufacturer insisted that immigration would dilute Japan's homogeneous society. He would happily get a few robots if he could afford them. Wait until the price comes down.

Bank of America Merrill Lynch forecast IT investment in Japan to rise as much as 9 percent annually in coming years, with the difference in software investment per worker versus the U.S. falling to 5 to 1 by 2020 from about 10 to 1 now.

The budding surge isn't limited to manufacturers. Non-manufacturing companies planned 2.4 trillion yen in software investment in the fiscal year ending in March 2018, according to the Bank of Japans Tankan survey, released in July. That would be the most since 2009. Retailers plan to spend 146.4 billion yen on software this fiscal year, the most on record for data going back to 1999.

Another reason Japanese people don't share American angst about robotics: Astro Boy. Cultural affection for the anime character has made it easier for people to feel more relaxed about robots and technology in their lives.

Just as well. That nurse assisting you in retirement may soon be a robot, along with the dog that keeps you company.

This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.

To contact the author of this story: Daniel Moss at dmoss@bloomberg.net

To contact the editor responsible for this story: Philip Gray at philipgray@bloomberg.net

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Aging Japan Wants Automation, Not Immigration - Bloomberg

By Kumar Saurabh, Contributor, CSO | Aug 22, 2017 7:01 AM PT

Opinions expressed by ICN authors are their own.

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When I speak with CISOs about automation in cybersecurity, it can conjure up parallels to self-driving cars. After all, if machine learning can create cars that drive themselves, why cant we have self-driving security?

Its a bit early and optimistic, however, to say machine learning and automation will immediately solve all cybersecurity challenges, if ever. Given the threat landscapes inevitable evolution, it will most likely remain an arms race between the defenders and the attackers for the near and long term.

Alternatively, the promise of a machine doing what we thought only humans could do is quickly approaching reality. Theres a lot of early results, hype and even more potential. In fact, this is also true for self-driving cars. The Washington Post highlighted the different levels of development in regards to autonomy in self-driving cars established by the Society of Automotive Engineers (SAE).

Specifically, the evolutionary path to the much-hyped fully autonomous car with each stage providing exponential value.

Similarly in cybersecurity, increasing levels of intelligent automation will also provide exponential benefits. If we compare the levels in the auto industry and apply them to the world of cybersecurity, level zero has very little automation while level five is most autonomous.

On one hand, you have solutions such as User Behavior Analytics and Network Traffic Analysis that profess to automatically analyze normal behavior and alert anything abnormal. The drawback is the inability to understand the full context of an environment or situation, which results in a tendency to generate too many false positives and requires significant analyst involvement to triage.

On the other hand, you have early orchestration solutions that can partially automate some of the easier and repeatable actions during an incident response process. While this solution is adequate to collect relevant information for an investigation process, the actual decision making is delegated to the analyst.

In essence, Level 2 automates actions and repeatable tasks, but not the decision making and judgments that require intelligence.

The first is full, end-to-end alert triage automation. This is where the system has the intelligence, based on context and awareness of an alerts severity, to make decisions and accept feedback from human analysts. Though more advanced systems are able to provide a full explanation of their scoring, analysts still need to review the systems results. However, 95 percent of the overhead work they used to have to do is effectively eliminated.

Second is automated threat hunting that is possible after expert analysts map out the logic they would use in an investigation. The system applies cognitive automation to intelligently hunt for threats 24/7, but at a scale with which human analysts cant keep up. This approach can be made more manageable with prescriptive logic flows for specific use cases, such as Threat Hunter for CloudTrail or Threat Hunter for Office 365.

Such a solution does not exist today, but is often what CISOs hope for when they hear security automation. Achieving this nirvana will require significant advancements in machine learning and computing power.

Security operations technologies have greatly evolved in the past decade. The first big wave was driven by log aggregation and analytics, followed by predictive technologies. The next generation of solutions will be Prescriptive Security Intelligence, offering specific solutions to typical security use cases. The industry will take time to enter a fully autonomous state. If security automation is your end goal, start by looking for Level 3 security solutions that can drive 80 percent of the way to your destination.

This article is published as part of the IDG Contributor Network. Want to Join?

Kumar Saurabh is the CEO and co-founder of security intelligence automation platform LogicHub. Kumar has 15 years of experience in the enterprise security and log management space leading product development efforts at ArcSight and SumoLogic, which he left to co-found LogicHub.

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The self-driving car of security automation - CSO Online

I am often asked to opine about whether automation will destroy all the jobs. Yes, we talk about tractors, which brought farm employment from something like 70 percent in the United States at the beginning of the 20th century to about 3 percent today. And about cars, which put the horse drivers out of business. And about trains, which put the canal boats out of business.

A more recent case has occurred to me, however. Its the one represented by the photo at the top of this page. It may look unfamiliar to some today, but this is what offices looked like in the 1950s and 1960s. Specifically, the photo shows a typing pool, and there used to be basketball-court-sized rooms that looked just like this, all over the place, staffed almost exclusively by women.

Then along came the copiermany of these women are copying documents by typing them over again with a few sheets of carbon paperthe fax machine, the word processor, the PC. And thats just typing. Accounting involved similar ranks of women with adding machines. Women by the roomful used to operate telephone switchboards, now all automated.

This memory lives on in the architecture of universities. All the old buildings have empty hutchesfor secretaries.

Business changes, and the workforce grows Women poured into the labor market despite automation destroying their old office jobs.

If you were prognosticating in or around 1970, and someone asked, What will happen now that women want to join the workforce, but office automation is going to destroy all their jobs? it would be a pretty gloomy forecast. But heres what actually happened: the female labor force increased from 20 million to 75 million. The female participation rate increased from below 35 percent to 60 percent. Womens wages relative to mens rose as female workers moved into activities with higher productivity than retyping the same memo a hundred times. Businesses expanded. And no, 55 million men were not out on the streets begging for spare change.

It is true that the male labor-force-participation rate did decline, from 87.5 percent to 70 percent. Thats a big, worrisome decline. But its 15 percentage points, while the womens increase was 25 percentage points. Also, the male labor force expanded from 45 million to 82 million.

Whos in, whos out As womens participation in the workforce has increased over the decades, the proportion of men working has declined.

US labor-force-participation rate Percentage of civilian population age 16 and older

US Bureau of Labor Statistics

But even if women were moving in and men moving out of employment, it would just show that you cant make predictions simply by looking at who has what jobs now that are threatened by automation. The typing pool got better jobs.

This is all a simplification, of course. There were surely some people with specific skillsshorthand, for examplewho could not retrain and didnt do as well as others. There are real problems with the labor market and real concerns for American workers, whatever the color of their collars.

But will automation mean that all the jobs vanish? In the case of the office-technology revolution, even combined with a large expansion in the number of people wanting to work, it did not.

John H. Cochrane is a seniorfellow of the Hoover Institution at Stanford University and distinguished senior fellow at Chicago Booth. This essay is adapted from a post on his blog, The Grumpy Economist.

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History offers a reassuring message on automation - Chicago Booth Review (blog)

The global terminal automation market in the oil and gas industry to grow at a CAGR of 6.72% during the period 2017-2021.

Global Terminal Automation Market in the Oil and Gas Industry 2017-2021, has been prepared based on an in-depth market analysis with inputs from industry experts. The report also includes a discussion of the Key vendors operating in this market. To calculate the market size, the report considers new installations, value, and aftermarket services market.

Terminal automation is a system that eases the product handling at the terminal and enables integration of these operations with the business software. It is used to measure, control, automate, and report all the exchanges and transfers. It offers complete management from receipt of the product to inventory control to dispatch recording. Terminal automation systems are deployed in various applications in the oil and gas terminals. Oil terminals include truck and pipeline terminals, whereas gas terminals include liquefaction liquid natural gas (LNG) and regasification LNG terminals.

One trend in the market is emergence of IoT and cloud integration. IoT is the next generation technology for all the applications due to its superior advantages in connectivity.

According to the report, one driver in the market is global expansion in oil terminals. Oil terminals are required to store the crude oil and petroleum products. The tank terminal industry is one of the spurring industries since last decade. The oil terminal owners made profits owing to the increased trade of oil and gas and increasing demand for storing the product in the high oil and gas prices scenario.

However, in low oil prices scenario, the industry is propelled by the trading and marketing activities by the countries. With low crude oil prices, oil and gas supply chain market structure is contango (a situation in which future value of the commodity is higher compared to spot pricing).

Further, the report states that one challenge in the market is huge capital investment and business downtime. Terminal automation provides several benefits ranging from increased operational efficiency to lowering the manual interference.

Key vendors

Other prominent vendors

Key Topics Covered:

Part 01:Executive summary

Part 02: Scope of the report

Part 03: Research Methodology

Part 04: Introduction

Part 05: Market landscape

Part 06: Market segmentation by product

Part 07: Market segmentation by application

Part 08: Geographical segmentation

Part 09: Decision framework

Part 10: Drivers and challenges

Part 11: Market trends

Part 12: Vendor landscape

Part 13: Key vendor analysis

Part 14: Appendix

For more information about this report visit https://www.researchandmarkets.com/research/ccf8nt/global_terminal

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Global Terminal Automation Market in the Oil and Gas Industry 2017-2021 - Key Vendors are ABB, Emerson, Implico ... - PR Newswire (press release)

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Home automation systems from Lutron and Somfy let you set collections of settings for your home.

For example, in the morning you can have your motorized window treatments automatically rise, your lights turn on. At the same time, your thermostat turned to a comfortable temperature. To clarify, you can program your lighting to completely switch off at night or when you leave your house to conserve energy. Formore you can set a couple of lights to turn on at night for security purposes. To put it another way, you can access your home automation system through your mobile device or laptop.

Home automation should make your life easier, not more complex thats where we come in. At Distinctive Home Automation, we work with you at your pace to set everything up. We provide expert consultation to help you figure out and get what you need. Of course, your input is essential for specific decisions and configurations, but we do the rest.

Our expert technicians will install and program your home automation system seamlessly. Most importantly we hold our products and customer service to very high standards to keep you happy.

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In the intense and ongoing debate over federal healthcarepolicy, the cost of prescription drugs has been a central and constant issue. Lawmakers from both parties have put forward dizzyingly diverse range of plans that aim to reducecostsand respond to constituent's demands.

But theres one straightforward technical tool for reducing drugcoststhat hasnt appeared in the high-profile debate.

Its no secret:automationcan be a dirty word in U.S. politics. Its often synonymous with computers or robots taking jobs and shuttering factories. Theres some truth to this. The U.S. lost at least 5 million domestic manufacturing jobs over the past two decades,in large part due toautomation.

Still, a great deal ofautomationis inevitable. And, if we make the right investments ahead of our global competitors,automationcan work to our advantage including in terms job creation and reductions in consumer prices.

Consider howautomationis poised to change pharma manufacturing. The standard analog method of making drugs,batch manufacturing, is now more than 100 years old. This process requires numerousstops and starts, takes a lot of time, and involves serious risks of contamination or error.

In contrast, the newautomatedmanufacturing method calledcontinuousmanufacturing makes it possible to producemedicines more quickly and efficiently,without interruption and with a great deal more real-time control.Continuous manufacturing can lower the cost of drugs significantly, by decreasing the unit cost, by accelerating product development, and by improving quality.

This kind ofautomationisunquestionablythe future of pharmaceutical manufacturing.But, in this future,it'squestionable whether the United States will lead and, in turn, reap the rewards of new high-skilled jobs and reduced consumer prices.

While U.S. researchers including those at Rutgers University'sCenter for Structured Organic Particulate Systems(C-SOPS),which I direct have led the development of Continuous Manufacturing technologies, U.S.-based firms face challenges in making the transitionto commercial practice.

In particular, small and medium sized manufacturers struggle with the upfront technologicalcostsrequired to incorporate these new technologies into operations. And, yes, some stakeholders mayfearthe loss of old jobsassociated withatransition fromthe previous system of pharmaceutical manufacturing.

Drug making is a microcosm of the broader manufacturing economy asautomationand digitization take hold.

If we areserious aboutsucceeding in manufacturing and taking advantage of digitization andautomation, wewillneed to ensure that new transformativeinnovationsare anchored in America and that we do more informed cost-benefit assessments when thinking about employment.

While automationeliminatesthe need for some operator positions, itsimultaneouslymeans the creation ofbetteropportunities at multiple levels of skill from engineering and programming to design, assembly,optimization,maintenance, and monitoring.

Government, industry, and universities should work together tostandardize the technology processes and product development methods that can ensure the new methodstakehold herefirst.Different sectors should also cooperate to incentivize and invest in education, workforce training, and technology adoption.

Automationisnt the enemy. It simply means thatmanufacturing jobs follow real knowhow, not cheap labor.

This is a reality that we can turn to our advantage.

In todays political arena, we should see proactive investments in advanced manufacturing not only as a tool to create high-value, high-skill jobs but also to address other overarching challenges including the cost and quality ofhealthcare.

In a competitive world of constant innovation, these investments aren't optional.

Fernando J. Muzzio is Director, NSF ERC on Structured Organic Particulate Systems, and Distinguished Professor, Chemical and Biochemical Engineering, Rutgers University.

The views expressed by contributors are their own and are not the views of The Hill.

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Want to cut healthcare costs? Try automation - The Hill (blog)

Writing in the Guardian, heres Larry Elliott on automation.The whole article is well worth a read, even if its too simplistic to argue (as he does) that the Luddites were wrong. Over the longish term they most certainly were. The industrial revolution paved the way for an immense improvement in living standards. But what that happy history omits is the fact that it took a while to do so, a phenomenon known as the Engels pause:

In the first half of the nineteenth century, the real wage [in Britain] stagnated while output per worker expanded. The profit rate doubled and the share of profits in national income expanded at the expense of labour and land. After the middle of the nineteenth century, real wages began to grow in line with productivity, and the profit rate and factor shares stabilized.

Put another way, the Luddites were (broadly) right about what the new technology could do totheir prospects and those of their children, but hugely wrong about what it would mean for their grandchildren.

Its worth noting that the Engels Pause was also a time of growing popular political discontent in Britain,

Convinced by the logic that the hit to demand from mass unemployment will (to oversimplify) constrain the extent to which tasks are handed over to the robots, Elliott argues that the robots will create more jobs. More jobs? Im not convinced, but hes on stronger ground when he asks this:

[W]hat if these jobs are less good and less well paid than the jobs that automation kills off? Perhaps the weak wage growth of recent years is telling us something, namely that technology is hollowing out the middle class.

Robots are likely to result in a further hollowing out of middle-class jobs, and the reason is something known as Moravecs paradox. This was a discovery by AI experts in the 1980s that robots find the difficult things easy and the easy things difficult. Hans Moravec, one of the researchers, said: It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility. Put another way, if you wanted to beat Magnus Carlsen, the world chess champion, you would choose a computer. If you wanted to clean the chess pieces after the game, you would choose a human being.

In the modern economy, the jobs that are prized tend to be the ones that involve skills such as logic. Those that are less well-rewarded tend to involve mobility and perception. Robots find logic easy but mobility and perception difficult.

It follows, says Joshi [an economist at BCA Research], that the jobs that AI can easily replicate and replace are those that require recently evolved skills like logic and algebra. They tend to be middle-income jobs. Conversely, the jobs that AI cannot easily replicate are those that rely on the deeply evolved skills like mobility and perception. They tend to be lower-income jobs. Hence, the current wave of technological progress is hollowing out middle-income jobs and creating lots of lower-income jobs.

Recent developments in the labour market suggest this process is already well under way. In both Britain and the US, economists have been trying to explain why it has been possible for jobs to be created without wage inflation picking up. The relationship between unemployment and pay the Phillips curve appears to have broken down.

But things become a bit easier to understand if the former analysts and machine operators are now being employed as dog walkers and waiting staff. Employment in total might be going up, but with higher-paid jobs being replaced by lower-paid jobs. Is there any hard evidence for this?

Well, Joshi says it is worth looking at the employment data for the US, which tends to be more granular than in Europe. For many years in America, the fastest-growing employment subsector has been food services and drinking places: bar tenders and waiters, in other words.

AI is still in its infancy, so the assumption has to be that this process has a lot further to run. Wage inflation is going to remain weak by historic standards, leading to debt-fuelled consumption with all its attendant risks. Interest rates will remain low. Inequality, without a sustained attempt at the redistribution of income, wealth and opportunity, will increase. And so will social tension and political discontent.

The Guardian is what it is, thus the call for sustained redistribution, but the risk of social tension and political discontent cannot be wished away. Andthe risk of that will rise significantly asautomation gnaws its way higher up the food chain.

And gnawing away is what its doing. Here (for example) is a recent story from CNBC on radiologists:

Arterys, a medical imaging startup, reads MRIs of the heart and measures blood flow through its ventricles. The process usually takes a human 45 minutes. Arterys can do it in 15 seconds.The remarkable power of todays computers has raised the question of whether humans should even act as radiologists. Geoffrey Hinton, a legend in the field of artificial intelligence, went so far as to suggest that schools should stop training radiologists. Those on the front lines are less dramatic.

Theres a misunderstanding that someone can program a bot that will take over everything the radiologist does, said Carla Leibowitz, head of strategy and marketing at Arterys. Radiologists still use the product and still make judgment calls. [We're] trying to make products to make their lives easier.

According to Dreyer, a radiologist spends about half the day examining images. The rest is spent communicating with patients and other physicians. Theres only so much that automated systems can take over.

Our desire to have somebody in control, I dont think that will go away anytime soon, said General Leung, cofounder of MIMOSA Diagnostics, which is testing a smartphone device that uses AI to aid diabetics. Someones always going to want a person to have made the decision.

True, but what will they be paid to make that decision?

Meanwhile, at the lower end of the scale, the traditional retail sector is taking a battering from the impact of e-commerce, but so far as retail workers are concerned, the hit from the switch to online shopping will be both direct (store closings) and, in a sense, indirect, as those stores that survive turn to automation to defend their profitability:

A recent analysis by Cornerstone Capital Group suggests that 7.5m retail jobs the most common type of job in the country are at high risk of computerization, with the 3.5m cashiers likely to be particularly hard hit. Another report, by McKinsey, suggests that a new generation of high tech grocery stores that automatically charge customers for the goods they take no check-out required and use robots for inventory and stocking could reduce the number of labor hours needed by nearly two-thirds. It all translates into millions of Americans jobs under threat.

None of this will happen overnight, and there will still be room for employees to work alongside them, but there will be fewer of them and what will they be paid?

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Automation, Unemployment and Moravec's Paradox - National Review

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The concept of robotics has been in existence for a long time, with Egyptians using automated water clocks to strike the hour bell and hydraulically operated statues that could gesture and speak in 400 BC. Subsequently, there have been many such instances of robotics in the history of mankind. The first modern-day Industrial Revolution dates back to 1800s and had manufacturing processes for metals, chemicals, textiles and mining; leading to an increase in productivity and output. Robots have evolved tremendously over the years and are now being widely used in various sectors such as defence, disaster management, search and rescue operations, and the entertainment industry in the form of electronically operated toys.

Automation is an extension of robotics and can be termed as the next phase of industrial revolution. The present industrial revolution seeks to disrupt the existing processes and enhance them with programmable logic. While it is easy to identify a repetitive process or task, it is equally difficult to program such a code that can make a machine carry out this activity on a perpetual basis.

As technology has improved over time, robots and automated systems have made inroads into organizations where tasks may have been dangerous, impossible or just plain mundane for humans.

Since the dawn of computer programming, automation, also known as robotics, was available in the form of click-and-type macros. These would repeat keyboard and mouse operations, mimicking a human.

With the advent of advanced analytics and data sciences, as in artificial intelligence, it is now possible to automate complex tasks that can act intelligently like humans. Analytics are now being used to identify or avoid risks; for example, identifying a suspect fraudulent transaction on a credit card based on the customers regular spending pattern or studying a customers spending pattern on an online retail store and recommending products.

Use of sensors in everyday objects such as lights, air conditioners and televisionswhich operate based on inputs like human gesture, speech or commandsis another example. Sensors are also being used to identify speeding cars or count the number of parking slots available in large parking spaces.

The latest application of robotics and automation can be seen in technologies such as autonomous or driverless cars, 3D printing and chat bots.

Data analytics forms the backbone of robotics and automation. Any task that can be programmed into a computer-readable code requires extensive amount of input data to be analysed and processed in real-time basis to provide enhancements.

For instance, real-time data analytics plays a pivotal role in allowing a driverless vehicle to self-navigate from one point to another, without human intervention. Sensors and cameras provide real-time input of distance between vehicles, traffic conditions, and natural obstacles such as stones and dividers; which are then processed at high speeds to allow the vehicle to navigate at an optimum speed. Global Positioning System (GPS) provides navigation and route information for the destination. All these processes and sensors work simultaneously, processing large data sets to redefine the driving experience.

Chat bots too require complex understanding to simulate human behaviour for efficient customer service. Data analytics can provide significant value to chat bot technology by leveraging large data sets that form the basics to simulate human behaviour. With the help of artificial intelligence and machine learning, bots can be designed to continuously learn and evolve their responses to customer queries. Chat bots can also be used in help desk management systems where these are capable of resolving queries accurately and at a faster pace compared to their human counterparts.

While automation technologies like driverless cars and chat bots may disrupt our lives in the future, each one of these could potentially create avenues and opportunities for individuals and businesses. Here are some examples:

The mass adoption of driverless cars could potentially have an adverse short-term impact in the form of job losses, but may also allow low-cost entry for small scale investors. These investors can set up a unit of driverless cabs and earn their livelihood without relying on third parties. Programming and data analytics for driverless cars would result in job creation in software engineering.

Chat bots could possibly reduce the need for customer service representatives but on the other hand, complex programming requirements and artificial intelligence would lead to more job creation for data science analytics and service delivery to customers.

Every industrial revolution that has occurred in the past has opened a wide variety of prospects for individuals as well as organizations.

Market sentiments suggest that the job market does not stay static but changes constantly with innovation in technologies. Many tasks undertaken (manually) by humans about 20-30 years ago are no longer relevant. Gone are the days wherein one would need to feed a huge stack of chip cards to a large computer system. Data entry has become more sophisticated and less manual. Similarly, todays jobs may not be that relevant 20-30 years in the future but there would be more and different opportunities. With the increased use of remote connectivity, video conference and digital presence; the job scenario is expected to drive the future of work. Manual tasks would become increasingly automated for business efficiencies and scale. This will be key for organizations that want to stay ahead of the curve and outpace rivals in a highly competitive world.

Amit Jaju, partner, forensic technology and discovery services,EY India

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Robotics and automation: threats and opportunities - Livemint

The Automation Conference & Expo is seeking end user presentations about the use of automation technologies from across industry (discrete manufacturing, batch manufacturing and continuous processing). Past presenters have included representatives from Boeing, GM, BP, Stihl, ExxonMobil, Coca-Cola, Chevron, BASF, Nestle, Caterpillar, Sherwin Williams, Chobani and many others so you will be in good company at the event and have the opportunity to connect with your automation peers in industries of all types.

Automation technologies covered by the conference include anything related to controllers, actuators, sensors, motors/drives, software, industrial networking/communications, robotics, etc.

The conference will be held May 22-23, 2018 in Chicago. Presentation sessions are 40 minutes in length (30-35 minutes for the presentation, allowing 5-10 minutes for Q&A with the audience) and should focus on specific aspects of your automation technology use to improve production, quality, maintenance, delivery times, etc.

You can learn more about the event at: http://www.theautomationconference.com

Please send a brief description of your proposed presentation, highlighting the automation technologies to be focused on and the application to which they apply, to: David Greenfield, director of content, dgreenfield@automationworld.com.

Deadline for submission: September 15, 2017.

Originally posted here:

The Automation Conference & Expo: Call for Presentations - Automation World

LONDON--(BUSINESS WIRE)--Technavios latest market research report on the global laboratory automation workcells market provides an analysis of the most important trends expected to impact the market outlook from 2017-2021. Technavio defines an emerging trend as a factor that has the potential to significantly impact the market and contribute to its growth or decline.

The global laboratory automation workcells market is expected to grow at a CAGR of close to 7% during the forecast period. At present, the stakeholders of laboratories are opting for automation for improved operations as well as well-directed experiments. This is expected to drive the growth of the market.

According to Bharath Kanniappan, a lead analyst at Technavio for automation research, The need for environmental controls in laboratories will drive the adoption of automated workcells. Adopting workstations will facilitate less manual contact with the specimen, leading to minimal cases of the lab technicians or personnel being infected. Workstations are entirely closed systems with one inlet for specimen entry and another exit point for proper collection of disposals.

This report is available at a USD 1,000 discount for a limited time only: View market snapshot before purchasing

Buy 1 Technavio report and get the second for 50% off. Buy 2 Technavio reports and get the third for free.

The top three emerging market trends driving the global laboratory automation workcells market according to Technavio research analysts are:

Looking for more information on this market? Request a free sample report

Technavios sample reports are free of charge and contain multiple sections of the report including the market size and forecast, drivers, challenges, trends, and more.

Emergence of laboratory automation control interface

Lab automation workcells requires an interface known as the Laboratory information management system (LIMS) to provide necessary information to the user. LIMS software stores, reports, and manages data of a batch of samples tested for drug trials and of other complex aspects of an experiment. This enables effective management of sample specimens and improves lab efficiency.

LIMS plays a major role in facilitating the real-time operation. The software can induce asynchronous functioning of all the devices and equipment. Automation control interface in laboratories drives hardware components. The interface helps in collecting patient information sources and achieving the goal of delivering optimum outcomes with maximum use of laboratory resources.

Increased use of cell-based assay

A cell-based assay is the phenomenon of several experiments taking place simultaneously based on the use of live cells. The experiments are primarily carried out to measure cell proliferation, motility, toxicity, production, and morphology of a specimen. At present, there is significant use of the cell-based assay for drug discovery.

Cell-based assays offer an accurate real-life representation of the behavior of live cells. Cell-based assays are required to analyze millions of samples per day. This calls for a need for laboratory automation workcells, which can support a high rate of productivity, says Bharath.

Rise in implementation of IoT in laboratories

The IoT has proliferated into many industries, and now, this technology is also being applied in laboratory automation. It has a major implication for creating a smarter healthcare infrastructure globally. Some of the wearable devices, connected with the IoT, can detect health problems and immediately refer drugs or send detailed information to emergency responders and family members of patients. The implementation of IoT is inducing the creation of smarter laboratories, leading to the creation of the Internet of Laboratory Things (IoLT).

The IoLT enables experts to operate automated workcells from anywhere and at any time. If a specimen needs to be in a freezer for 12 hours, a lab technician can give a command for the further progress of the experiment, in advance and the experiment will be executed after completion of 12 hours. In such a case, the technician can control the progress of the experiments through the information received on his or her tablet or mobile phone that is aligned with laboratory workcells. The technician can decide the status of the specimen from his or her own room and direct the progress. This type of remote monitoring has only been possible with the implementation of the IoT with automated workstations in laboratories.

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