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Category Archives: Automation

Festo Bridges Pneumatics and Servo Motion – Automation World

Posted: September 27, 2021 at 5:39 pm

At PACK EXPO Las Vegas, Festo is showcasing its new Simplified Motion Series (SMS) all-in-one integrated-drive axes. The company says SMS represents an engineering breakthrough in that it combines pneumatics with electric automation. This breakthrough is based on how Festos SMS integrates ball screw axes, toothed belt axes, mini slides, electric cylinders, piston rod, and rotary actuators with an onboard servo drive.

SMS actuators are designed for use in positioning, indexing, clamping, feeding, and cut-to-length tasks. Because all SMS components are integrated into a single unit with a unique part number, this simplifies the ordering, inventory, and replacement of SMS units, which is especially important for OEMs. Units in the series include: ELGS-BS ball screw, ELGS-TB toothed belt axis, EGSS mini slide, EPCS electric cylinder, EPCE compact electric cylinder, ERMS rotary drive, and ELGE toothed belt axis.

Simple electrical connection is accomplished via a M12 plug design with 4-pin power and 8-pin logic.

Festo points out that no additional software is required to operate SMS, as commissioning is accomplished via onboard push buttons for two-position functionality. Key commissioning parameters include:

Digital I/O (DIO) and IO-Link control come standard with each SMS unit. With DIO control, two positions are availablehome and a configurable end point. Festo says that, when controlling SMS with IO-Link, positioning along the axis length is infinitely variable, which enables SMS axes to be used as a cost-effective alternative to traditionally higher cost servo motion. Using IO-Link, technicians can remotely adjust movement parameters as well as copy and backup functions for parameter transfer and read functions of essential process parameters.

This level of capability opens up more applications to electric motion, including conveyor material handling and mobile applications, according to Festo.

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Automation of the Data Lifecycle Data Consumption – RTInsights

Posted: at 5:39 pm

Data consumption is a critical part of the data lifecycle, and with the introduction of new tools, it increasingly benefits from automation.

In May of this year, we published an article entitled Improve Data Lifecycle Efficiency with Automation, where we opened the discussion around how the identification, collection, integration, and utilization of information in its various forms has accelerated in recent years. We covered the broad strokes of the data lifecycle and then went deeper into each aspect of the lifecycle in subsequent articles (Automation of the Data Lifecycle: Focus on Data Creation and Automation of the Data Lifecycle: Focus on Data Storage that also covered aspects of Data Quality.) This piece will focus on an area that has seen some of the most dramatic changes and one that is of critical importance to the primary business users of data Data Consumption.

The data consumption layer is the area of the data lifecycle that sits between the sources of ones data and the users of that data. This is an area that has seen some significant advances in recent years with the release of commercially available tools that help todays data-centric leaders run their organizations in a more proactive way. Not too long ago, data professionals leveraged reporting tools and early-stage business intelligence solutions that offered visibility into what had and (in some cases) what was happening within the organization. This offered tremendous value and allowed us to make sense of the growing volumes of data (largely) within the confines of the organizational firewalls (e.g., Microsoft Excel typically used to organize data and perform financial analysis.) As technology advanced and the thirst for more proactive analysis grew, new tools and solutions allowed the data consumer to be more proactive and gave birth to predictive and prescriptive solutions turning data into information and information into actionable intelligence.

Below we will focus primarily on some of the more recent advances in data consumption and how automation of this aspect of the data lifecycle provides significant value to the business. Traditional analytics and business intelligence, while still of value, are being supplemented and even replaced by tools and solutions that augment (and even replace) the human in the equation. Augmented analytics and self-service solutions driven by AI-enabled bots have become more widely leveraged and in demand given the distributed workforce and our hunger for information. First, we will look back and explore some of the more widely used legacy tools and solutions from the early days of reporting and business intelligence and then showcase some of the fantastic and game-changing offerings available today.

One cannot really talk about reporting and analytics without mentioning Microsoft Excel. Excel is the most widely used data analytics software in the world and is the tool of choice for many business professionals. It is the most common tool used for manipulating spreadsheets and building analyses and has been for decades. Excel is installed on most business and personal computers, is easy to learn, easy to use, and provides fantastic visualization capabilities for reporting and analytics. While Excel offers powerful reporting and (descriptive) analytics capabilities, an organization looking for deeper insights that span multiple sources and types of data might have looked to solutions offered from some of the large enterprise solution giants like SAP, Oracle, or IBM. For example, BusinessObjects (BOBJ), which was acquired by SAP in 2007, offered/offers clients an enterprise-ready solution for reporting and analytical business intelligence (BI) that aided users to find data, generate canned or custom reports, and conduct deep analytics across multiple data sources. These (now) legacy solutions have matured over time, and many have morphed into next-generation offerings leveraging Artificial Intelligence (AI) to automate the acquisition and analysis of data aiding the data professional seeking more real-time, forward-looking insights.

Todays data-centric leaders are no longer satisfied having to rely on others to feed their hunger for insights and require more immediate gratification from their data. Traditional/legacy analytics offerings have, therefore, seen significant disruption recently by platforms that leverage AI to augment the human interaction and automate much of the data discovery, acquisition, and analysis many leveraging bots and virtual assistants that are conversational in nature (such as Tableau and Microsoft Power BI.) This provides the (business) data professional with more of a self-service type offering and reduces some of the reliance on IT. In Q4 2019, Microsoft released Automated ML in Power BI. According to documentation from Microsoft, with Automated ML, business analysts can build machine learning models to solve business problems that once required data scientist skill sets. Power BI automates most of the data science workflow to create the ML models, all while providing full visibility into the process. Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights. Your data may be an Excel spreadsheet or a collection of cloud-based and on-premises hybrid data warehouses. Power BI lets you easily connect to your data sources, visualize, and discover whats important, and share that with anyone or everyone you want. As organizational leaders thirst for deeper, more real-time, forward-looking insights has increased, so has the demand for these types of solution offerings.

Regardless of the type of technology you are using or the stack that you currently have in place, automation is playing a larger role in the ability to get to the information one needs to make an informed business decision. Take reporting as an example. At one point, it was necessary to run an extract on the data to get what one wanted in a usable format. One, then, needed to understand the structure of the data to ensure you were accessing the correct fields. Todays automation allows you to scroll through a list of needed fields, select the ones that are necessary for your report, move them around on the page and select run. The application then accesses the necessary information and provides you with the results. The act of automation has reduced the time necessary to run the report (allowing you to run it as many times as necessary to see the information you are looking for in the format you desire) as well as eliminating the need for you to contact IT in order to either extract the data or create the report for you.

Previously, when running statistical analysis, it was necessary to understand the structure of the information and run countless point-to-point analyses to determine if there was a correlation between data points that could then be used from a predictive perspective. Algorithms were built by hand using specific coding instructions in order to get results. While there are several programming languages today that allow data scientists to continue to delve into deep analysis and run ML programs dependent on that analysis to make specific decisions on a shop floor (for example), it is also now possible for the average user to drag and drop any number of fields into an application to see what the correlation between the fields is with no support from either a statistician or IT. What is important to understand here is that the automation that is included within all these tools (reporting, analytics, AI/ML, etc.) becomes transparent to the end user. All of the work that needed to be coded or done by hand is now done in the background through the interface with automation.

And, while we did mention the idea of incorporating Data Governance and the cleansing of data as part of our previous article, we would be remiss if we did not mention it again here as the use of automation in this area (verification on consumption) also decreases the data rejection rate and increases the overall quality, and value of the data. The implementation of data standards and governance provide the business rules that are used to cleanse the data and increase its validity to the business itself. Automation and the use of AI decrease human intervention in the cleansing process, increasing the velocity at which the data can be used.

In summary, organizations should embrace change and watch for opportunities to harness and leverage data to improve profitability, reduce costs and increase revenue. Advances in automation of the data lifecycle enhance our ability to acquire, store, cleanse, integrate and deliver data in real time thus improving the overall value and reliability of the massive amount of information and do so at the speed of thought.

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Bigeye, providing data quality automation, closes second round this year with $45M – TechCrunch

Posted: at 5:39 pm

Bigeye on Thursday announced a $45 million in Series B funding, just six months after securing a $17 million Series A round.

Coatue led the new investment that included existing investors Sequoia Capital and Costanoa Ventures. Together, the San Francisco-based company has brought in a total of $66 million, which also includes a $4 million seed raised last May.

The companys technology automatically recommends and monitors data quality, for example telling customers what kind of data metrics to collect and alerting customers if there is an issue like when one of their ordering systems is down before it becomes a bigger problem.

Usage of the platform has doubled in each of the last four quarters, and the company also brought on new customers, like Clubhouse, Recharge and Udacity, prompting co-founders Kyle Kirwan and Egor Gryaznov to consider another round of funding. The co-founders met while at Uber and worked on similar data quality issues.

We really started out wanting to fix the problem for people in our shoes, but we didnt anticipate the quiet demand, CEO Kirwan told TechCrunch. Even in the Series A, there was demand, and to go after it, we needed to grow our engineering team even faster. There is so much to do on the product we have the nugget of the product today, but we want to go further like explore when we detect data outages, how to prevent them the next time and how better to communicate them to the right person.

In addition to engineering, the new investment will fund growth in product and go-to-market teams as well. Bigeye has 25 employees currently and Kirwan would like to see that be 40 by the end of the year.

Having started with automating a way to pay attention to the right signal coming from data, Bigeye is now shifting its attention to helping data teams communicate to the rest of their company when something isnt working or broken.

Kirwan plans to invest in how to make it faster to get to the root cause so that data outages can be prevented in the future. In addition, the company is also examining repetitive tasks within a customers workflow to see if there is an opportunity for machine learning to automate it.

As part of the investment, Caryn Marooney, general partner at Coatue, is joining the companys board. Coatue is one of Bigeyes early customers; she was able to see firsthand what the platform could do.

Marooney said she was attracted to the teams experience building data-quality monitoring to scale at Uber, its approach to helping data teams measure and improve their data quality and the high-level customers the company is serving.

Looking toward the future, she sees data monitoring and observability as a key component of the modern data stack. Rather than examine data once a quarter, companies are using it every day to make business decisions, and therefore, need a reliable method for collecting and utilizing the data.

Before, if you had bad data, your dashboards would break, Marooney added. Today, bad data can disrupt your business. Bigeye was made by data teams for data teams, and we believe theyve solved this reliability problem for the most data-centric businesses.

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What is intelligent automation and how might it help us? – World Economic Forum

Posted: at 5:39 pm

Pascal Bornet is a pioneer and expert in the field of intelligent automation - also known as cognitive or hyperautomation. He spoke to the World Economic Forum about the technology and his passion for making our world more human using intelligent automation.

An edited transcript of that conversation follows below.

Intelligent automation is a combination of methods involving people, organizations and also technologies involving machine learning. Intelligent automation is aimed at automating end-to-end business processes on computers. It delivers business outcomes on behalf of the employees working hand-in-hand with them to deliver faster, better, cheaper services. This improves not only the employee experience, but also the customer experience.

When I explain what intelligent automation is, I like to share an example. All companies around the world are performing an end-to-end process, which we call 'procure-to-pay' (PTP), which is about procuring goods and services from vendors. Intelligent automation will help, first of all, to select the vendors using machine learning. And then it's about sending orders to those vendors and how we will leverage workflow platforms, for example.

And then it's about receiving and processing invoices after the services or goods have been received - and this can be done using natural language processing. And finally, the payment to those vendors. It's quite systematic and can be done using robotic process automation.

It helps employees to do work faster, better, but also to have more time to focus on what really matters. For example, insights, comments, relationships, managing their teams because intelligent automation is working for them on the most transactional and repetitive activities. We always say, 'I don't have the time to do that because I need to do all this'. Now, we have more time for qualitative work.

The employee experience is critical, but so is the customer experience. Waiting in a queue to get a train ticket, waiting to see a bank agent, all of this can be solved by intelligent automation. More than 90% of customers don't even bother to complain, and 90% of them will never return. So it's really a black box here to understand what makes a client satisfied and how to get their loyalty - and intelligent automation is in the middle of this.

According to our estimation, intelligent automation has the potential to save 10 million lives per year. It can do this by helping to support clinical trials, disease diagnoses and avoiding medical errors.

In developing countries, it can help to reduce deaths from preventable causes as well. More than 1.6 million people die every year from diseases related to diarrhoea, for example. But it's crazy because we know how to solve it. The issue is those people don't have access to physicians. Globally, we have a shortage of more than four million physicians. And by enabling remote diagnosis, using smartphones, tablets, those people can have access to the services. And again, here, it's millions of lives that can be saved every year.

Another example I like to give is an intelligent automation application, like tissue analytics, which helps instantly to diagnose chronic wounds, burns or skin conditions just by taking a picture on a smartphone.

It's a good use case in transportation. This includes the identification of and the prediction of where transportation is needed so that you can allocate the right assets and the right trucks in the right place in advance of the need being expressed. And this can be done using machine learning based on past and historical data and then the optimization of the routes that the trucks will take.

In Melbourne, they've also sent some drones to capture the traffic at roundabouts on video, to understand the patterns there and help them to design better traffic rules and a better flow of cars and so on, using machine learning.

It's really about a synergy, I would say, between what the people do and will do and what the machines do and will do. Machines today, supported by technologies such as machine learning robotics, are able to perform any transactional, repetitive tasks very well. But, they need to be trained on huge amounts of data, so it means those tasks need to have been repeated in time in the past many, many, many times.

But machines are not good and will not be good at all for at least the next few decades in tasks such as creativity, relationship building, critical thinking or anything with social skills. So it's really about us humans focussing on those capabilities that make us different from technology.

Let's take the example of a physician that is helping review X-rays. Of course, the machine will be much better at doing the job of identifying tumours on X-rays very quickly with high accuracy - better than a doctor. Nevertheless, the doctor will be the best at managing the patient relationship, helping the patient to understand what's happening, what will happen in the future, managing change and communicating. So that's really how people and machine work together.

We use intelligent automation to manage small, transactional, repetitive activities. It helps to refocus people on more exciting activities and activities that are also delivering more value for their companies.

The adoption of intelligent automation is quite high. The term was officially coined in 2017, but more than 50% of the companies around the world have already implemented it. That's going to rise to 70%, according to Deloitte, in the coming two years.

Nevertheless, only 15% have been able to scale these transformations. So today, the key challenge for all companies is about scaling, implementing such technologies across divisions, and across companies within the same group.

We've done our research on the critical success factors to get to scale. The first one is always put people in the centre of those transformations: they are performed by people for people. The second is about management support. The third is about combining the different technologies to be able to automate the most complex use cases. Number four is about using new technologies, which are commonly called low-code technologies, that help people with no coding skills, no programming skills, to implement intelligent automation in their daily work and improve their daily work by themselves.

Finally, the fifth critical success factor is it's about using a new breed of technologies that help to implement intelligent automation. Ironically digital transformations are actually extremely human-intensive, extremely manual. But by using technologies such as process, discovery, data discovery, auto-machine learning and others, we are capable of automating a large part of the implementation of intelligent automation so that those transformations can go faster and be broader.

The views expressed in this article are those of the author alone and not the World Economic Forum.

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China’s Mindray takes cell morphology analysis to next level with automation – BSA bureau

Posted: at 5:39 pm

Mindray, China-based medical solution provider, has launched the new MC-80 Automated Digital Cell Morphology Analyser, a revolutionary cell morphology system that provides more clarity, more intelligence and more productivity for morphological analysis.

Combining MC-80, Mindray's hematology solution will revolutionize the high-end hematology segment.

Morphological review of blood cells is a crucial procedure following hematology analysis. Most laboratories need to re-examine more than 30% of their blood samples, but find traditional microscopic review labor-intensive and time-consuming.

Automated digital cell morphology analyzers are now available on the market, but providing clear and accurate cell images comparable to the microscope remains a fundamental challenge.

Mindray's new MC-80 is taking digital morphology analysis to the next level, delivering clearer images which are able to capture abnormalities in more detail.

With advanced algorithms, the analyzer enables better identification of different cells with high throughput, resulting in greater productivity.

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Are the robots coming for white-collar jobs? – Raconteur

Posted: at 5:38 pm

Automation has long been seen as a threat to blue-collar jobs. However, as the technology becomes increasingly sophisticated, white-collar careers could also feel the impact, affecting everyone from lawyers toCEOs.

One of the common worries around digital transformation is that many peoples jobs will be automated or replaced by technology in a quest for greater efficiency. According to PwCs Upskilling Hopes and Fears 2021 survey, 60% of respondents are worried that automation is putting many jobs at risk, and 39% think its likely that their job will be obsolete within five years. Last October, a World Economic Forum report said 85 million jobs may be replaced with AI by 2025.

In the past, the jobs seen as at-risk were those that involve a high number of routine or repetitive tasks, often in areas termed low-skilled. According to PwC, most jobs that will be lost to automation are routine (such as underwriting), repetitive (like data entry) or dangerous (for example, factory line production).

However, the reality now is that many high-skilled jobs will be affected to varying degrees if technology continues on the current trajectory, says Alexa Greaves, CEO of AAG IT Services. These include nurses, lawyers, legal secretaries, accountants, translators, marketing managers and real estate agents, shesays.

Professions and skills that are based on accrued knowledge and data-led decisions are all at risk from different levels of automation, Greavesadds.

With US law firms investing $1.5 billion in robotic process automation (RPA) in legal sector offices between 2017 and 2019, the legal profession appears to be embracing the technology - but does this threaten lawyers livelihoods? A robot may be able to produce better legal documents than a human can, says Greaves, but a lawyer who has experience in dealing with the subtle, social elements of a case is still a valuableasset.

Thanks to automation, lawyers at all stages of their careers will take on less project management, leaving more of their time free for actual legal work. Matt Abbott, president at recruitment firm The Sourcery, says that legal professionals should staypositive.

You might not need as many people for those jobs, but someone has to manage the whole process. The RPA software cannot analyse its own possible flaws or fix itself, so once theres an issue with the system or automation, someone has to unravel it completely.

Even the CEO position isnt totally immune to automation. Earlier this year the business editor of the New Statesman, Will Dunn, asked: CEOs are hugely expensive why not automate them? As Dunn notes in the piece, the High Pay Centres most recent annual survey of FTSE 100 pay packages points out that there is actually quite significant potential for companies to safeguard jobs and incomes by asking higher-paid staff to make sacrifices.

Professions and skills that are based on accrued knowledge and data-led decisions are all at risk from different levels of automation

So what is the future of the CEO? Victorian McLean, founder and CEO of City CV, suggests they will continue to be in demand, because the role is a complex combination of learned wisdom, intuition and human connection.

Highly skilled, highly paid employees are more likely to perform roles that require creative thinking, the ability to develop complex strategies and decision-making, even if they use AI to help them solve problems, she says. AI simply cant handle these functions or mirror the workings of the human brain - right now, atleast.

Innovations in automation might help us reimagine what a CEO is, but there will always be a need for a leadership position. We may get rid of the CEO title, Abbott says, but that being said, there has to be someone who makes decisions. There is still a need for the human element that has to make the calls. I dont see too many high-level careers going away with digital transformations.

So how should these high-powered workers prepare for an automated future in which their jobs remain, but are altered by automation?

These types of jobs tend to emphasise the skills where humans always excel over the technology we have today or are likely to have in the near future. As Greaves says, diversifying skillsets and focusing on so-called soft skills that are harder to automate, like communication and teamwork, are likely to be goodbets.

While robots may be intelligent enough to perform routine tasks, they are not generally intelligent in the way that humans are, says McLean. Any creative job - musicians, marketers, inventors - wont be replaced. It also means jobs like therapists, counsellors, carers - anything that requires a human connection - wont bereplaced.

The reality is that the workplace and the workforce are continually evolving to incorporate new technology and new ways of thinking. Its a challenge as old as our concepts of white-collar work.

We know that 65% of children in primary school right now will work in jobs that dont currently exist, says McLean. We also know that since the Industrial Revolution, new technologies have changed the working landscape. Weve lived through 150 years of change. Should we look at AI any differently?

Probably not. The workplace will always feel the impact of developing technology, but human beings are endlessly adaptable. Bringing automation into the office will make our working lives better, invent new jobs that fit the future workplace and save all of us some precioustime.

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ABB’s New, Higher Payload Collaborative Robot – Automation World

Posted: at 5:38 pm

Originally introduced to handle highly repetitive, low-weight tasks such as machine tending, assembly, and smaller packaging operations alongside humans, collaborative robots (cobots) have been increasing in capability over the past few years. These new capabilities enable cobots to perform a wider variety of tasks.

ABBs new 6-axis GoFa CRB 15000 is one of these new cobots and is on display at PACK EXPO Las Vegas. It is designed to support the growing demand for cobots capable of handling heavier payloads. According to ABB, the GoFa CRB 15000 features a class-leading reach of 950mm and speeds up to 2.2 meters per second for a variety of packaging applications, including pick, pack-and-place, kitting, and product handling.

GoFas collaborative robot features include intelligent torque and position sensors in each of its six joints/axes. ABB says these specially designed joints eliminate the risk of injury to human workers by sensing any unexpected contact between the cobots arm and a human to bring the robot arm to a stop within milliseconds.

Programming GoFa is done via ABBs new Wizard programming software, which employs simple graphical blocks to ease the programming process for personnel who are not robot specialists. The blocks represent actions such as move to location, pick up an object, and repeat task to make the programming process more intuitive.

ABB points out that every ABB cobot installation includes a start-up package that provides ABB Ability condition monitoring and diagnostics as well as a support hotline free for the first six months to access ABBs expert technical assistance.

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DHL harnesses the benefits of automation – SHD Logistics

Posted: at 5:38 pm

Over the last eighteen months the eCommerce space has seen significant growth, catalysed by the Covid-19 pandemic and global lockdowns which shifted even more consumer spend online. We have seen this across the board, with pure play etailers growing, bricks and mortar operations able to solidify their online operations, and even new market entrants able to launch with different business models such as subscription services. This acceleration in the market has been great for consumers, and a lifeline for businesses needing to find their way through challenging times, but has posed some challenges from a fulfilment perspective. A surge in the number and type of orders that need to be picked, packed and shipped can put pressure on businesses as they try to keep to their customer promises and brand ambitions, while maintaining employee satisfaction. At DHL Supply Chain we have been working closely with technology providers as part of our accelerated digitisation strategy to ensure were able to harness the benefits of innovations in automation to help our customers, delivering efficiency and service improvements to their operations as well as improve the working environment for our colleagues.

In the fashion eCommerce space we have seen our customers experience significant growth as we stayed at home but continued to shop online. Often the challenge in both mid- and high-end fashion is getting the cost-to-serve price point right, something that can be improved by making the order picking process more efficient and where automation can really help. For example, for some of our fashion customers globally we have been able to deploy the Geek+ goods-to-person solution, which eliminates the need for our colleagues to travel around the warehouse picking manually, helping to improve picking accuracy and drive efficiencies. This technology also allows us to improve the density of product storage, reducing the warehouse footprint needed and lowering the costs of the logistics operation even further. As with all the robotics partners selected by DHL, the rich data behind the Geek+ solution can also be used by our customers to gain an in-depth understanding of their consumer and their fulfilment operation, producing sophisticated heatmaps of how their stock is performing in real-time.

Looking to the future, shared user sites are becoming increasingly common and these goods-to-person robots have a real place in these environments, as sophisticated algorithms will allow them to work accurately in multi-user sites, and even simultaneously across different businesses.

Another area were working with customers on is in the beauty and pet care space, where high throughput and a requirement for personalisation and customisation is driving the need for an increasingly light-touch, end-to-end pick process. For pure play retailers, peak volumes can typically be four times the non-peak volumes, placing strain on the fulfilment operations as it adapts. At the same time, the shipping and unboxing experience is particularly important, as it may be the only real opportunity for the brand to interact with the consumer and so needs to be an opportunity to build brand loyalty. Across our global eCommerce business, working with 6 River Systems we have been able to deploy the mobile robot chuck to help our customers manage the challenges of fluctuating demand, while maintaining high quality control and delivering a great end-consumer experience. Using the chuck means that each order is able to be quickly and efficiently picked and packed across a high number of SKUs, and only needs one touch before it is shipped. Reducing the number of touchpoints is really beneficial to the protection and presentation of fragile beauty products.

Aside from the efficiency gains that innovations in the order-picking space can bring, its important for us to consider how we can improve the employee experience for our colleagues in these roles. At DHL we are focused on introducing technology that improves the working life of colleagues across the business, and in the warehouse it is no different. Adding automation into the environment means that our colleagues are able to move away from repetitive and manual tasks into a more technology-based role. In a competitive labour market we know that giving the opportunity to work with cutting edge innovation can be incredibly rewarding, and creates the sort of working environment where people want to stay. Likewise, while the strict requirements for social distancing may have passed, there are still ongoing challenges and the use of technology allows us to keep staff welfare front of mind by reducing the number of pack benches we need.

Working with a business like DHL is a great way for businesses to take advantage of the opportunities presented by the technology, without taking on the investment themselves. In these challenging times retailers dont want to stifle the growth opportunities, so tapping into our portfolio of solutions allows them to explore the possibilities without any of the risk. Its an exciting time to be in this space, as there is no doubt that order picking and fulfilment stands to benefit greatly from innovations in automation and robotics now, and into the future. We have already seen just how transformational it can be, and were still at the beginning of the journey.

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Automation puts one in 10 Aussie jobs at risk, report warns – 9News

Posted: at 5:38 pm

One in 10 jobs in Australia are at risk of being automated as the economy recovers from the COVID-19 pandemic, a new reports says.

In comparison, wealthier and affluent urban areas face the least risk of jobs being automated.

Jobs most at risk from automation

The OECD estimates 36 per cent of Australian jobs are at risk of being automated, compared with the OECD average of 46 per cent. About 11 per cent of jobs face a high risk of being automated. A further 25 per cent face major changes.

Plant and machinery operators and food preparation workers are among the employment sectors most at risk.

Young people, men and Indigenous people were also more likely to have declining job opportunities.

Where will it be felt hardest?

Regional towns and cities will be among the most affected by automation. Many of these have traditional industries such as coal mining.

About 40 per cent of jobs in the New South Wales Hunter Region face some disruption while in Queensland's Mackay region it was about 41 per cent.

In comparison, Canberra and Sydney's eastern suburbs face the lowest risk of jobs lost through automation.

Which jobs have the best prospects?

The COVID-19 crisis accelerated the shift from traditional industries to teaching and health, the OECD says.

One in seven Australians today work in health or social services, a 100,000 rise over the past 12 months.

In Australia, health or social services now account for more than 14 per cent of all jobs.

What about protecting jobs?

The OECD says some workers will have their duties upskilled to replace their routines duties. This would ensure they could carry out non-routine tasks that could not be achieved through automation.

This trend is increasingly common in the mining and resource industries.

Federal and state governments needed to continue this to encourage a shift away from sectors that have traditional jobs.

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PMMI’s Top to Top addresses automation, workforce woes and sustainability – Packaging World

Posted: at 5:38 pm

Major consumer brands like Barilla, Kraft Heinz, Pepsico and General Mills collaborated with PMMI member OEMs such as Spee Dee, Garvey, Delkor, and Poly Pack to prioritize challenges facing the industry today as well as in the next three to six years.

The biggest ask from CPGs is machinery that is more intuitive for easier operations, especially with continued workforce shortages. Two-thirds of the audience voted this the most challenging issue facing the industry today. One CPG called for machinery that is Amazon-easy to operate.

Forty-two percent of participants called for earlier collaboration between stakeholders including contract packagers/manufacturers.

Better partnerships with deeper communication are keys to success. Dont wait to tell us about a problem or shortage, said one CPG. Often, we can help source steel or components because of our global connections.

About a third of participants point to workforce issues as an opportunity to help boost ROI for automation projects, especially connectivity to aid in remote monitoring, diagnostics, etc. Although everyone agrees that when you talk machine connectivity, you are introducing cyber security issues.

The discussion turned more passionate when moderator Jorge Izquierdo, VP of Market Development for PMMI, asked about projecting problem issues three to six years in the future. Many issues garnered the same amount of interest, with no one issue emerging above others.

The number-one issue in the future will be sustainability and recycling initiatives, including education for industry and consumers. The industry needs to address our role in waste and climate change, said one participant.

Another crisis tied to workforce is making the packaging industry attractive to young workers. Working with schools to create a curriculum that will prepare students for specific jobs was suggested. A clear way to attract young gamers is the application of virtual and augmented reality, said one participant.

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PMMI's Top to Top addresses automation, workforce woes and sustainability - Packaging World

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