Daily Archives: September 27, 2021

At its 2021 virtual Ignition Community Conference, Inductive Automation highlighted the steps it has been taking over the past year to position the Ignition industrial automation software platform for its next steps, indicating that several new updates will be forthcoming in the next few months.

Carl Gould, director of software engineering at Inductive Automation.Carl Gould, director of software engineering at Inductive Automation, said, Our primary area of focus for the software development team is on quality and process improvements. He said the company has been staffing up the quality team to achieve a nearly one-to-one staffing ratio of software engineers to test engineers. We're also building up our QA (quality assurance) infrastructure with automated test infrastructure and automated benchmarking so that every release we put out has undergone a rigorous set of testing to ensure that Ignition can be as stable and defect free as possible.

Two industrial automation technology trends having a big impact on Ignition are mobility and data access, said Travis Cox, co-director of sales engineering at Inductive Automation. With a greater focus on mobility, developers are extending automation systems to smartphones and tablets to take advantage of mobile device capabilities such as GPS, the built-in camera, NFC (near-field communication) and Bluetooth, and leverage those features to build the bigger solution, he said. Inductive Automations Ignition Perspective module allows users to build industrial applications to monitor and control production processes from a mobile device, desktop, or touch panel.

Travis Cox, co-director of sales engineering at Inductive Automation.As for the data access trend Cox noted, he said industrys increasing interest in leveraging edge computing and MQTT communications is targeted at bringing [production floor] data into a modern infrastructure and the cloud for additional applications, such as analytics and machine learning. We're seeing a lot of customers leveraging AWS and Azure and their asset modeling tools to go a lot further with the data they collect, he said.

A fixture of the Ignition Community Conference is its Discover Gallery, where key Ignition implementations are spotlighted to show off the softwares capabilities as an automation platform. In part of his keynote presentation at the conference, Cox noted several applications in this years Discover Gallery, including:

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Inductive Automation Explains What's Next for Ignition - Automation World

As we emerge from the pandemic and look to recovery, it is important for finance leaders to keep two points on automation in mind to drive resiliency and growth. The first is the ability to react quickly to changing requirements and demands, and the second, the many processes that can now be done remotely and in much less time.

There is no doubt that automation not only drives efficiency, control and visibility to spend, but can also maximize resiliency and minimize risk. Here are four ways through which automation does just that, and ultimately, future-proofs businesses for unpredicted events.

1. Enabling a remote workforce and automating manual processes will allow companies to be better prepared for future disruptions.

At the onset of the pandemic, businesses struggled to go remote or be automated overnight, as some tools, applications and networks needed to be created or implemented. While many executives scrambled to find the right investments and create a resilient infrastructure, they were looking for solutions that could help convert paper invoices to e-invoices and easily approve and process for automatic payment, which resulted in a new interest in how the accounts payable (AP) process was viewed, including how it interfaces with the purchasing process. For example, capturing invoices in an online portal provides businesses with complete visibility of what has been spent and planned expenditure along with reducing manually intensive and error-prone aspects of invoice processing.

The future is looking a bit different. A newly released survey from JP Morgan Chase shows that more than 50% of business leaders are planning for a flexible work environment post-pandemic and are doing some form of remote work model as a result of COVID-19. There is so much that is cloud-based and employees can have access anywhere, through any software and in a secure way. Now companies have the visibility and control that many lost at the onset of the pandemic. Today, providing the right software-as-a-service (SaaS) solutions for remote workers will future-proof businesses.

2. Speed in automation adoption matters in todays complex environment.

The manual process to receive, process and pay invoices was one of the last things that executives looked to automate. As companies have been slow to adopt digital innovations towards automating AP and accounts receivable (AR) processes, it is putting the spotlight on the back office forcing it to change. Whether it was budget constraints or implementation concerns, many had avoided this process until the pandemic exposed the vulnerabilities that laid within it. Processing payments and handling invoices in an automated fashion better enables resiliency. For example, since suppliers wont change how they submit invoices overnight, a flexible AP model one that can efficiently handle paper, data-layer and image-based pdfs, XML and portal invoices, regardless of how the team is set up is the most reliable approach to take. By implementing both AP automation and a modern P2P system, finance leaders benefit significantly as it relates to the financial close, reporting and ongoing audits.

Forward-thinking companies, e.g., big Fortune 500 companies, have already traveled part of the road to automation and seen the efficiency and have the capital to do it. What is interesting is the mid-tier and small-to-medium enterprises. These are the ones who can benefit from automation. Automation not only saves money and time, but also it could be doors to a greater opportunity for strategic projects.

3. Now is the time to prioritize risk management.

Risk management is something relatively new from a supplier and payments standpoint. People have experienced and realized that a disruption to revenue can disrupt the resiliency in supply chain and are investing in systems and processes to manage suppliers from anywhere and more efficiently.

Suppliers who could not shift, find a product or operate were in a bad position. Businesses looked for resiliency and redundancy within suppliers, along with the need to communicate and react quickly. Minimizing supplier risk is and will continue to define success for many businesses. With consistent, consolidated, and on-going management of supplier information throughout the supplier relationship lifecycle, a true visibility of supplier risk can be maintained.

Todays complex world taught businesses risk management simply cannot be ignored. Executives are now asking for transparency, visibility, and diversity there. Procurement teams are able to make that happen when supplier management becomes exponentially more efficient and consolidated through automation.

4. Use automation to increase efficiency, maximize control and drive visibility in their spend.

The big trend now is how to get automated and how to do it efficiently to drive resiliency. A problem we have seen is that if all the knowledge for a supplier contract or how they get is with one person or one small group, there is a lot to lose. What happens when that person or group is not available? That is an exposure, and it has manifested acutely this past year. Businesses will benefit greatly from transparency by including an online system.

Theres a lot of talk about maximizing working capital and minimizing your risk. Many finance leaders think of working capital in a broad sense and may not look at it through the lens of supply chain financing, which has many benefits. Working capital is known as the fuel behind any successful mid-market company. While working capital maximization is an interesting angle that does not always translate into this growing trend of supply chain financing, there are many ways to go about this such as giving suppliers the opportunity to take early payment discounts or by offering them different payment terms. If a business needs more cash, which we saw in the pandemic, many looked to offer supplier discounts. Those that had automation in place were able to work with their suppliers quickly to give them the ability to see their invoices or move through the approval process quickly.

The events of the past year have accelerated automation and created a new wave of transformative changes for many businesses to enhance customer experiences. Businesses need to assess where they are today and take action in their approach to their automation journey, especially when they look at how they can enhance and future-proof their businesses for unforeseeable events.

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4 Ways Automation Future-Proofs Businesses for Unpredicted Events - Supply and Demand Chain Executive

In our latest Innovation Spotlight, digital technology expertABBintroducesa dedicated virtual summit exploring the exciting future for robotic automation in the packaging and logistics industry.During the summit,ABB experts and industry leaders will discuss key issues and how they are being addressed by developments in robotic and automation technology.

ABB is holding its first summit for the packaging and logistics industry, looking at how robotic automation can be used to address the growing challenges presented by changing consumer trends. Taking place on Thursday 7th October, PackLog.Now will see ABB experts and representatives from the world of consumer goods manufacturing, retail, and logistics discussing how robotics and automation can help businesses to transform their operations into highly efficient, flexible, and productive factories and warehouses.

The manufacturing, retail, and logistics sectors are currently facing several disruptive megatrends that are demanding a new approach in the way that goods are produced and distributed.

Foremost among these is the increased expectation of consumers for goods produced, packaged, and delivered to their personal requirements, demanding new flexible technologies capable of handling low volume, high mix, and batch size one processes. With additional factors also including labor shortages and the ongoing impact of COVID-19 on worker availability, the growth of omnichannel distribution, and the continued rise of e-commerce, companies are increasingly looking to robots and automation for a solution.

The summit will open with a plenary session, where Sami Atiya, president of ABB robotics & discrete automation, will look at the impact of the megatrends affecting the packaging and logistics sectors.

Marc Segura, group senior vice president and managing director of consumer segments & service robotics, will follow this up with an introduction to ABBs Consumer Segments and Service Robotics (CSSR) and a look at some of the new robotic technologies capable of providing new levels of flexibility, speed and consistency in consumer manufacturing, packaging and logistics applications.

There will also be a Voice of the Customer roundtable session, where representatives from industry leaders companies like Procter & Gamble or Schwarz Gruppe, among others, will give their insights into their current production challenges and pain points and the solutions they are deploying to help tackle them.

Pieter Abbeel, co-founder and chief scientist for robotic AI specialist Covariant, will provide an additional look into the role of artificial intelligence in the factories and warehouses of the future.

Attendees will then be able to join one of three breakout sessions.

Each chaired by an ABB expert, these sessions will look at the various ways that robotics and automation can be used throughout the manufacturing and logistics supply chain, including creating integrated end-to-end lines; enabling flexible processing, picking, packing and palletizing; and optimizing the performance of eCommerce, Fulfillment and Post, and parcel operations.

With the impact of COVID-19 accelerating changes in consumer behavior, the event is part of a move by ABB to help build awareness of the role that robotic automation can play in packaging and logistics applications, and the technologies available that can help companies to achieve new levels of performance, efficiency, and adaptability.

The event will run from 10:00 to 12:30 CET on the morning of 7th October, with a repeat session in the afternoon from 16:00 to 18:30 CET.

To find out more, and to register for the event, visithttps://packlognow.robotics.abb.com/home.

This content was sponsored by ABB.

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ABB PackLog.Now virtual summit to reveal how flexible automation is transforming the future of packaging and logistics - Packaging Europe

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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Automation of the Data Lifecycle Data Consumption - RTInsights

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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Festo Bridges Pneumatics and Servo Motion - Automation World

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

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

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.

Original post:

China's Mindray takes cell morphology analysis to next level with automation - BSA bureau

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

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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ABB's New, Higher Payload Collaborative Robot - Automation World