Category Archives: Automation

Ericssons intelligent innovation approach is very simple: use standardization where standardization gives optimal results and use vendor-specific where a vendor-specific approach optimizes results. Intelligent innovation is dynamic, agile and a problem solver. It is strongly aligned to Ericssons approach to RAN automation which recognizes the O-RAN Alliance service management and orchestration (SMO) platform, including the non-Real-Time RAN intelligent controller (Non-RT-RIC), is a brilliant platform for RAN automation. Ericsson extends this innovation to include todays existing, purpose-built 4G and 5G networks which make up 98 percent of deployed networks today.

Intelligent innovation is closely tied to Ericssons approach and commitment to openness and innovation in the telecommunications industry. So how does it work?

Ericssons Intelligent Automation Platform (EIAP) is a prime example of Intelligent Innovation in practice. The platform uses both [pre]-standardized interfaces to maximize openness to encourage multi-vendor inter-working and open development ecosystems, particularly in the northbound (OSS/BSS) and southbound (network) interfaces, and in closed, vendor-specific components areas like the software development kit (SDK) where speed, agility and control are important.

Ericsson is a strong supporter of the internal, R1 interface, between the Non-RT-RIC and the RAN automation rApps that run on it. The ability to specify, publish and eventually standardize the R1 interface are key to creating an open innovation ecosystem that will allow RAN vendors, communication service providers (CSPs) and other third-party software vendors to build and importantly monetize RAN automation rApps. The Ericsson Intelligent Automation Platform is highly innovative and uses a mix of [pre-] standardized[1] and customer specific approaches on the platform.

[1] The key O-RAN Alliance interfaces have been proposed and are in the process of being specified. Once specified the expectation is that the interfaces will become standards. Today these interfaces can be said to be pre-standardized.

Ericsson has a very strong track record of leading 3GPP to define the specifications for our 2G, 3G, 4G/LTE and 5G mobile network technology. The utran-UE (Uu) interface, which operates between the user-equipment (UE) also known as the end-user device or smartphone, and the radio base station or eNodeB, is a prime example of the importance of interface standardization. The standardized Uu interface means any phone manufacturer can be confident that the mobile phone its produced will work on all 4G or 5G networks, anywhere in the world. As always there is always a requirement to carry out a level of interoperability testing between the device and various RAN vendor equipment because standards can be interpreted or implemented in slightly different manners, but this testing in minimal. Standardization has driven a broad ecosystem of phone manufacturers with access to global markets. For end users, it means they can travel anywhere in the world and use their phone; assuming there is network coverage and their service provider has the requisite roaming agreement. This is not how things were twenty-plus years ago. Its important to remember that until the introduction of 4G/LTE there wasnt any global mobile telephony standard. The world was roughly divided into incompatible systems based on 3GPP (WCDMA) and 3GPP2 (cmda2000), which were further broken down into a number of variations as well as country specific standards across the globe. Latin America in particular was interesting because there was a mix of WCDMA and CDMA networks.

In this example there were clear benefits to the industry of standardization to support multiple vendor ecosystems.

A key component of the Ericsson Intelligent Automation Platform is the platform software development kit, or SDK. The SDK is designed to enable Ericsson, CSPs and third-party independent software vendors (ISVs) to rapidly build automation rApps. This is because the SDK offers: low technical barriers to market entry, low costs to development and, based on the eventual specification or even standardization of the R1 interface, enables monetization across multiple SMO vendor platforms. When deciding its SDK approach, Ericsson made two important decisions:

This is an example of good openness', with Ericsson having chosen to share a very valuable asset with the industry but also to benefit from the speed and agility that single-entity ownership conveys. Because the rApps developed with the SDK will utilize the open R1 interface to connect to the non-RT-RIC and the O-RAN Alliance A1, O1 and O2 interfaces to connect to Cloud RAN and Open RAN networks the fact that the toolkit used to build those rApps is effectively proprietary doesnt affect the application.

Unfortunately, in todays deployed 4G and 5G purpose-built or physical RAN networks the network management function tends to be highly proprietary or vendor specific. There have been some good interworking initiatives, such as the Operational Support System interworking initiative, or OSSii, but unlike Ericsson not all RAN vendors have adopted the spirit or the letter of the OSSii approach. This means that for the EIAP to support non-Ericsson network management systems (NMS) or equipment management systems (EMS) often requires a level of systems integration to support the FCAPS - fault, configuration, accounting, performance and security of non-Ericsson networks.

However, because the EIAP is designed to maximize openness the platform is capable of supporting standardized and proprietary northbound and southbound interfaces with the intent of providing a single, multi-vendor, multi-technology service management and orchestration platform.

Sometimes, all you can do is make your platforms as open as possible and hope that other vendors take the opportunity to leverage that capability to provide what CSPs expect: truly multi-vendor and multi-technology platforms.

We believe that there are four key principles that create the conditions for good openness and that Ericssons approach to Open RAN service management and orchestration uses all four:

So, to answer our own question, the use of open interfaces is fundamental for driving RAN automation. In terms of the debate between standardization or proprietary, vendor-specific approaches we believe this is driven by weighing up the pros and cons of each approach. Certainly, in the SMO domain good openness means a mix of standardization and vendor-specific interfaces to create optimal outcomes and enable rapid innovation.

Excerpt from:

Intelligent Innovation openness and RAN automation - Ericsson

NEW YORK--(BUSINESS WIRE)--UiPath (NYSE: PATH), a leading enterprise automation software company, today announced it has integrated its automation platform with digital document generation and e-signature capabilities from Adobe (NASDAQ: ADBE). By integrating with Adobe Document Services and Adobe Acrobat Sign to help customers automate end-to-end document processes, UiPath can boost employee productivity, enhance digital customer experiences, and lower costs through seamless, uninterrupted digital document workflows.

According to a Forrester Consulting study commissioned by Adobe, 97% of organizations with minimal digital document processes are seeing a negative impact on productivity. Automation and artificial intelligence (AI) technologies have triggered a paradigm shift in existing ways of managing processes and repetitive tasks creating the productivity and efficiency gains that these fast-moving organizations demand.

Whether its onboarding new hires, creating NDAs, or ordering standard equipment, employees and customers spend a lot of time repeating manual, paper-based processes. These tasks not only take too much time, but they also introduce inefficiency and risk into every step of the process, said Deepak Bharadwaj, Vice President of Product Management, Adobe Document Cloud. In todays hybrid world, every department across an organization needs modern tools that accelerate document and e-signature workflows. And with UiPath and Adobes integration, organizations will have easy access to the best digital document experiences that drive productivity and scale in a secure manner.

By transforming manual processes into all-digital experiences, UiPath and Adobe are enabling organizations to accelerate and modernize their work with employees and customers alike. More specifically, these integrations:

For example, when onboarding a new vendor that vendor is required to complete an NDA. With the Adobe Acrobat Sign connector for UiPath, customers can automate the process through a web form by indicating the recipient and selecting the type of document that is needed. The connector triggers an automated process to find the most recent version of the NDA that automatically descends to requesting the vendors e-signature. Meanwhile, customers can view the progress at any time what documents were reviewed, who signed them, and more.

Customers want a simple, affordable, and resilient solution without complex infrastructure and application changes. They also know that Adobe has been in the business of providing the best document tools and services for decades. Were here to help, said Param Kahlon, UiPath Chief Product Officer. As interest in accelerated document processes amongst organizations continues to grow, the UiPath integration with Adobe enables enterprise organizations to easily begin or continue their enterprise automation journey, successfully mature and scale their automation initiatives, and refocus their workforce on business transformation.

For more information on the integration and to get started, visit the UiPath Marketplace:https://marketplace.uipath.com/listings/adobe-pdf-services.

About UiPath

UiPath has a vision to deliver the Fully Automated Enterprise, one where companies use automation to unlock their greatest potential. UiPath offers an end-to-end platform for automation, combining the leading Robotic Process Automation (RPA) solution with a full suite of capabilities that enable every organization to rapidly scale digital business operations.

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UiPath Partners with Adobe to Automate End-to-End Digital Document Processes and Workflows - Business Wire

As Industry 4.0 and IIoT (Industrial Internet ofThings) concepts become real applications,an exciting conversation has developed centeredon the integration of information technology(IT) with operations technology (OT). Large IT companieshave actively promoted ideas like workloadconsolidation for businesses to optimize processes andbe more competitive. Some of the largest players inautomation technology (AT) are jumping on board.Greater system openness, real-time deterministiccontrol with many-core processors, the incorporationof web technologies and machine learning, amongother advances, are all possible through applyingpopular technologies to industrial applications.

IT and OT convergence offers incredible benefitsto machine control architectures todayjust as it hasfor more than 30 years. While many suppliers arejust beginning to integrate PC-based technology intoindustrial automation, it is nothing new. The history ofIT-OT convergence in automation technology datesback to the early 1980s with the advent of the modernPC and those who saw its potential for industrialuse. The adaptation of these ideas follows the diffusionof innovations theory, which describes how newtechnologies are adopted in order by the innovators(2.5%), early adopters (13.5%), early majority (34%),late majority (34%) and, finally, the laggards (16%).

PC-focused innovationin the 1980sDuring this era, the larger technology world beganto develop the personal computer (PC) and relatedtechnologies for widespread business and consumeruse far beyond 1970s levels. This led to transformationsin standard chip sets, board designs, and sophisticatedoperating systems. At that time, most industrialtechnology companies stayed away from the PCpath. The PLC platforms of the time used proprietarychip sets, board designs and, in most cases, programmingsoftware. Traditional PLC technology formachine control evolved much slower than it shouldhave due to an industry-wide aversion to change. Asa result, the paths of hardware PLCs and consumerPCs would not begin to converge for decades.

While the majority of industrial vendors andmanufacturers initially shunned IT technology on theplant floor, smaller start-up companies recognizedthat both technologies could coexist. Using provenindustrial standards and computer science innovations,smaller AT companies began the convergenceof IT and OT in manufacturing.

Early adoptersof the 1990sIn the 1990s, both technologies continued toadvance, with IT pioneers running laps around traditionalOT. The popularity of Windows exploded, andit became ubiquitous in nearly every area of technology.By launching Visual Studio in 1997, Microsoftcombined a number of programming languages ina single environment, which continues to evolve tothis day. Industrial vendors that began implementingPC-based automation technologies in the previousdecade saw significant gains in hardware and softwareperformance that far outpaced traditional PLCs. Thesuccessful companies created new tools for deterministic,real-time control that could run on industrialPCs with standardized operating systems.

More automation vendors saw this opportunityand launched computer-based controls. However,these early adopters realized that developing theirown software from scratch was quite costly. Theystarted using off-the-shelf real-time operatingsystems, but often didnt widely promote thesolutions. Some notable crash-and-burns gavePC-based platforms a bad reputation during thistime. However, many platforms were providingincredible results in the field, extending their leadin performance over traditional PLCs.

Early majority from2000 onwardThe turn of the millennium brought further developmentsin software and multi-core processors. MajorIT players like Intel, IBM, and Microsoft activelyexpanded into OT. Likewise, a determined subsetof the automation space kept integrating IT withincreased real-time capabilities.

Along with these automation and controladvances, another major development involved networking.Industrial Ethernet protocols, such as Ether-CAT, created significant performance improvementsand a path forward from legacy fieldbuses. This isanother example of IT and OT convergence, withEthernet merging with fieldbus technology. Ether-CAT eliminated the complexity and cost of switchesand additional hardware while providing deterministiccontrol with up to 65,535 devices per network. Thisresulted from the same PC-based control innovatorswho carefully considered the potential of industrialEthernetcombining its openness and acceptancewith the functionality of a fieldbus.

Todays late majorityFrom automation software apps on smartphonesto many-core Intel Xeon processors in controllers,IT-OT convergence continues to acceleratetoday. For example, contemporary HMIs nowcommonly rely on web technologies, and standardssuch as MQTT and JSON are being implementedin IIoT contexts.

Gigabit Ethernet technologies such as Ether-CAT G are also becoming key as machines becomemore complex. The industry is also beginning toapply machine learning and other artificial intelligencetechnologies.

Fortunately, the reluctance of manufacturersto implement PC-based technologies continues toevaporate as they see the benefits of IT technologiesin industry. The decades of IT-OT advances haveshown that any IT principle carried over to OT productsmust be deterministic, reliable, available for manyyears and implemented efficiently. Done correctly,IT-OT integration produces results far better thanwhat traditional platforms can accomplish.

For more information:www.beckhoff.com/IoT

Link:

IT-OT Convergence Has Always Been The Path Forward - Automation World

Back to Basics is a weekly feature that highlights important but possibly overlooked information that any EHS professional should know. This week, we examine automation, the use of automation in EHS reporting, and how it can increase the productivity of the workforce.

New technologies are constantly being invented and distributed to consumers, including versions of artificial intelligence that are used in various ways to make peoples lives simpler. In the EHS industry, there has been a surge of individuals and organizations who are advocating for the automation of EHS processes, especially when it comes to reporting and data collection.

Many companies have come up with their own algorithms and data input resources to help EHS professionals with their jobs, and as this continues to happen, its becoming increasingly important to understand what automated EHS means and how it can impact the workforce. Jake Freivald, the Vice President of Fulcrum, spoke in a recent webinar about the benefits of automation in EHS and what the implementation of artificial intelligence would look like, specifically in the case of safety inspections.

In order to increase productivity and efficiency, EHS leaders should first consider the processes that their employees go through while doing their jobs. Freivald said there are two levels of processes, the workers process, and the enterprises process. The worker, an EHS professional in Freivalds example, may send out a team to do an inspection on-site with checklists, then someone has to return to transcribe that data into a spreadsheet, which is then used as a part of a master spreadsheet that is turned into a report for stakeholders.

This workflow fits into the larger enterprise process, which can involve using the spreadsheets to bill clients and making sure the work being done is remaining in compliance. Freivald stated that in this framework, the data is only useful depending on the quality, which is why it is important to consider the workflow to see if there are any gaps or errors in reporting that can be potentially addressed by automation.

There are many different ways to introduce automation into a workflow or process, and its important to have realistic expectations of what automation can do. Freivald said that rather than artificial intelligence (AI) making every process magically easier, the reality is that AI will likely have a specific set of capabilities that are a solution for a single problem, and it will be able to solve that problem faster than a human.

There are multiple pathways that employ automation and technology that Freivald outlined that are specific to the EHS industry.

In terms of digitizing inspection processes, Freivald recommended finding methods that make it easier for users to input data. When picking between fill-in-the-blank or a pick list with options, choose the pick list. If the worker needs to type in their observations, add in an audio feature so they can use their voice to record what they need to. Break up text and questions into appropriate chunks, and only display certain information or questions when the circumstances make it necessary. Lastly, include diagrams and any other data the user needs in the inspection checklists, and generally simplify more than what might seem necessary. The goal is to streamline processes to increase efficiency.

The first step to increasing productivity with automation is to find parts of the workflow or process where there is a significant amount of data passing between people. Freivald recommended looking for areas where poor data quality has caused significant issues, because automating those data handoffs will reduce transcription errors which makes reporting more efficient and accurate. However, it is important to find a balance when determining which problem to tackle with automation. If the problem or process is too simple, the outcome will not be significant enough for the results to matter, but avoid trying to take on too much at once.

Freivald used remediation as an example, which is a process that basically consists of identifying the problem, communicating it, fixing it, and then communicating the fix. Typically, inspectors will perform inspections, identify issues, and then transcribe the data they found in a report which gets sent to the superintendent. The superintendent will identify issues in the report and contact the remediation crew. Remediators will fix what they need to and make another report, which goes back to the superintendent, who then confirms the remediation and closes out the case. Freivald stated that this process would be easier if automation was used during the first inspection step with data collection, since it would reduce transcription errors and streamline the reporting process.

In terms of measuring success, Freivald said to leverage data flow to create and publish metrics, and he suggested using two different types safety performance and inspection performance. Safety performance metrics can include remediation time and cost, fines, calendar days lost, and person-days lost. Inspection performance metrics can include inspection time and cost, the time workers wait for inspection completion, and safety problems found post-inspection. Freivald also warned against being punitive, and emphasized that punishing hazard reports teaches people not to report hazards, which is not the ideal outcome.

Finally, in order to convince upper management to invest more in automation, AI, and technology in general, EHS leaders should emphasize the end result of more productivity and the downstream effects of that productivity. Freivald said the number one thing to do is focus on specific problems that upper management sees, not just the niche issues. Frame the conversation around how automating inspections or other processes with reduce the number of billing days and the days it takes to send the bill to clients, which will increase the speed at which the company gets paid.

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Back to Basics: Increasing Productivity with EHS Automation - EHS Daily Advisor - EHS Daily Advisor

Summary

Star Cutter and Garr Tool are developing innovative multi-process CNC machine tools for complete end mill manufacturing.

May 17, 2022 -US manufacturers Star Cutter Company and Garr Tool have jointly developed an innovative 5-axis CNC machine tool that completely automates the production of complex profile end millsfrom blank to finished tool.Star Cutter Company specializes in carbide and preform manufacturing, cutting tools and CNC machines for tool/cutter grinding and hob sharpening. Founded in Detroit back in 1927, the company nowadays operates six manufacturing facilities at strategic locations throughout Michigan. Its Elk Rapids Engineering division is responsible for the renowned Star brand of CNC tool and cutter grinders.Garr Tool is the USAs leading manufacturer of high-performance solid carbide cutting tools. From humble beginnings with Fred Leppien in his garage in 1944, it now operates a state-of-the-art 200,000 square foot manufacturing facility in central Michigan with over 150 CNC grinders. Garr Tool specializes in solid carbide cutting tools, including end mills, drills, reamers and routers.Garr Tool makes extensive use of CNC automation, including tool grinding machines from Ulmer Werkzeugschleiftechnik (UWS) and Star-Cutter. All of these machines are based on control technology supplied by the specialist CNC company NUM. Star Cutter, for example, has partnered with NUM for cooperative development of application-specific CNC hardware and software since 1998, and nowadays bases nearly all its machine tools on NUMs open-architecture Flexium+ CNC platform.According to John Leppien II, vice president of Garr Tool, We use NUMs NUMROTO software for tool production and reconditioning on all of our Star and UWS machines. Our operators regard it as very flexible and user-friendly, and we find that it encourages interdepartmental knowledge sharing and also helps to reduce our training overheads.A few years back, Garr Tool began producing a series of large diameter tools for use on high torque machines employed in the aerospace industry; however, manufacturing the tools involved multiple machines and multiple processes. The company therefore embarked on a collaborative project with Star Cutters Elk Rapids Engineering team, to develop a multi-process machine capable of handling the entire production task. The result was a 2018 development of a Star CNC Tool grinder which included NUMROTO end mill software, cylindrical grind, along with linear motors and drives, with all 5 axes on a closed loop chiller/coolant system. This thermally stable machine allows Garr Tool to maintain .001 in diameter on the OD of these tools during lights out for 48 hour unattended runs.Star's latest machine, the NXT tool and cutter grinder, now also incorporates these same features that were introduced to Garr Tool. Based on NUMs Flexium+ CNC system and NUMROTO software, this new 5-axis machine tool features linear motors instead of ball screws on the X, Y and Z axes, direct drive torque motors on the B and C rotary axes, and a liquid-cooled spindle motor. There is a choice of three different types of spindle motor, to best suit application needs; these include a very high speed unit capable of 24,000rpm, and a very high power unit rated at 28kW.The NXT has an exceptionally small footprint (including the spindle/axis chiller) of just 7 6 x 6 6 (2300 x 2032mm), and an installed height of only 75 (2284mm). These dimensions mean that the machine can easily be accommodated on the shop floor, where space is often at a premium. The base of the machine is cast in ZanitePlus polymer composite to ensure mechanical rigidity and thermal stability.Despite its diminutive size, the NXT offers a substantial grind zone, with maximum X, Y and Z travels of 19.7, 25.6 and 29.5 (500mm, 650mm and 750mm) respectively. The machine can accommodate up to 15 (381mm) end work and up to 10 (254mm) diameter parts. Automated wheel changing and probing is standard with up to 8 (203mm) diameter wheels, and the NXT can also run up to 10 (254mm) diameter wheels with coolant manifolds and up to 12 (305mm) diameter wheels without.The ability to use large diameter grinding wheels for profiling applications or small, sub 1 (25mm) diameter wheels for PCD pocket grinding on the same machine introduces a remarkable level of production flexibility.Star Cutters new NXT tool and cutter grinder features a fully integrated Fanuc 200iD compact 6-axis short arm robot to facilitate fully automated processing of round and flat tool blanks; the standard gripper can handle from 5mm to 32mm blanks, with other options available. In-process measurement data is fed directly to the CNC systems NUMROTO software, to provide adaptive real-time control of the entire grinding process.Based on a modular architecture, the NXT is designed for ease of integration with other forms of industrial automation and handling robots. An extensive range of factory-build and retrofit options include a traveling W-axis and a 12,000rpm wheel dresser.Aaron Remsing, Jr. Sales Manager for Star Cutters Elk Rapids Engineering Division, pointedout: We believe that the NXT is the smallest and most capable CNC tool and cutter grinder on the market. Even though it is an evolutionary design, its performance is nothing short of revolutionary.

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Star Cutter and Garr Tool Create Next-generation Production Automation - Automation.com

Mentions of industrial automation within the filings of companies in the medical devices industry were 12% lower during 2021 than in 2016, according to the latest analysis of data from GlobalData.

When companies in the medical devices industry publish annual and quarterly reports, ESG reports and other filings, GlobalData analyses the text and identifies individual sentences that relate to disruptive forces facing companies in the coming years. Industrial automation is one of these topics - companies that excel and invest in these areas are thought to be better prepared for the future business landscape and better equipped to survive unforeseen challenges.

To assess whether industrial automation is featuring more in the summaries and strategies of companies in the medical devices industry, two measures were calculated. Firstly, we looked at the percentage of companies which have mentioned industrial automation at least once in filings during the past twelve months - this was 62% compared to 55% in 2016. Secondly, we calculated the percentage of total analysed sentences that referred to industrial automation.

Of the 10 biggest employers in the medical devices industry, BD was the company which referred to industrial automation the most during 2021. GlobalData identified 20 industrial automation-related sentences in the United States-based company's filings - 0.2% of all sentences. Danaher mentioned industrial automation the second most - the issue was referred to in 0.14% of sentences in the company's filings. Other top employers with high industrial automation mentions included Roche, Fresenius and IQVIA.

Across all companies in the medical devices industry the filing published in the fourth quarter of 2021 which exhibited the greatest focus on industrial automation came from Agilent. Of the document's 1,720 sentences, nine (0.5%) referred to industrial automation.

This analysis provides an approximate indication of which companies are focusing on industrial automation and how important the issue is considered within the medical devices industry, but it also has limitations and should be interpreted carefully. For example, a company mentioning industrial automation more regularly is not necessarily proof that they are utilising new techniques or prioritising the issue, nor does it indicate whether the company's ventures into industrial automation have been successes or failures.

In the last quarter, companies in the medical devices industry based in Western Europe were most likely to mention industrial automation with 0.16% of sentences in company filings referring to the issue. In contrast, companies with their headquarters in the United States mentioned industrial automation in just 0.08% of sentences.

Development and Production of Medical Devices and Primary Packaging

High-Performance Machines for Medical Device Components

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Filings buzz: tracking industrial automation mentions in the medical devices industry - Medical Device Network

Global payment orchestration platform BlueSnap has announced the results of its 2022 Automating Accounts Receivable survey.

For this report, BlueSnap surveyed executives globally to examine the extent to which businesses are adopting automation in their accounts receivable (AR) processes and its benefits. One takeaway from the findings: organisations have only automated a fraction of their AR processes with plenty of gaps left to close to reap the full rewards of true end-to-end AR automation.

Supply chain issues and inflation put increased pressure on businesses to get paid on time. Now more than ever, businesses must find ways to increase efficiencies to keep a positive cash flow. BlueSnap's survey results found that 89% of businesses that have automated AR processes are getting paid within their agreed payment terms or faster.

The data shows that nearly half (49%) of global businesses are stuck using legacy AR processes. While many organisations have started to automate AR processes, they are often only automating one or two steps. When it comes to generating invoices, only 19% have completely automated the process and a mere 15% have completely automated sending the invoices.

Only 8% of the companies surveyed had completely automated the setup and management of customer payment plans, while more than half (51%) said they had the process mostly, but not completely, automated. These fragmented attempts are small steps in the right direction, but to see the full operational benefits like better cash flow, increased customer satisfaction, and improved employee productivity, it is essential for businesses to completely automate AR processes.

The factors preventing organisations from fully automating their AR processes include a lack of understanding of the technology available (71%), a fear that automation will take the human element out of the business (47%), lack of technical expertise to implement new systems (44%), and a concern that people will lose their jobs (23%).

To find out more about BlueSnap, please click here.

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Survey: businesses aren't reaping the benefits of accounts receivable automation - The Paypers

Pune, May 17, 2022 (GLOBE NEWSWIRE) -- Hyper Automation Market by type/solution, service, organization size, end-use verticals, and Region Global Hyper Automation Market Forecast to 2030, published by Market Data Centre, The Hyper Automation Market is projected to grow at a solid pace during the forecast period. The presence of key players in the ecosystem has led to a competitive and diverse market. The advancement of digital transformation initiatives across multiple industries is expected to drive the worldwide Hyper Automation Market during the study period.

This COVID-19 analysis of the report includes COVID-19 IMPACT on the production and, demand, supply chain. This report provides a detailed historical analysis of the global Hyper Automation Market from 2017-to 2021 and provides extensive market forecasts from 2022-to 2030 by region/country and subsectors. The report covers the revenue, sales volume, price, historical growth, and future perspectives in the Hyper Automation Market.

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Regional Analysis:

On the basis of Geography, the Global Hyper Automation Market is segmented into North America, Europe, Asia-Pacific, and the Rest of the World (RoW). North America is expected to hold a considerable share in the global Hyper Automation Market. Due to increasing investment for research and development process and adoption of solutions in the region whereas Asia-Pacific is expected to grow at a faster pace during the forecasted period.

The growing number of Hyper Automation Market players across regions is expected to drive market growth further. Moreover, increasing investments by prominent vendors in product capabilities and business expansion is expected to fuel the market during the study period. Many market players are finding lucrative opportunities in emerging economies like China and India, where the large populations are coupled with new innovations in numerous industries.

In deep ToC includes

233 Tables

45 Figures

300 Pages

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Table of Contents

1. INTRODUCTION1.1. Market Definition1.2. Market Segmentation1.3. Geographic Scope1.4. Years Considered: Historical Years 2017 & 2020; Base Year 2021; Forecast Years 2022 to 20301.5. Currency Used2. RESEARCH METHODOLOGY2.1. Research Framework2.2. Data Collection Technique2.3. Data Sources2.3.1. Secondary Sources2.3.2. Primary Sources2.4. Market Estimation Methodology2.4.1. Bottom-Up Approach2.4.2. Top-Down Approach2.5. Data Validation and Triangulation2.5.1. Market Forecast Model2.5.2. Limitations/Assumptions of the Study3. ABSTRACT OF THE STUDY4. MARKET DYNAMICS ASSESSMENT4.1. Overview4.2. Drivers4.3. Barriers/Challenges4.4. Opportunities5. VALUE CHAIN ANALYSIS6. PRICING ANALYSIS7. SUPPLY CHAIN ANALYSIS8. MARKET SIZING AND FORECASTING8.1. Global - Hyper Automation Market Analysis & Forecast, By Region8.2. Global - Hyper Automation Market Analysis & Forecast, By Segment8.2.1. North America Hyper Automation Market, By Segment8.2.2. North America Hyper Automation Market, By Country8.2.2.1. US8.2.2.2. Canada8.2.3. Europe Hyper Automation Market, By Segment8.2.4. Europe Hyper Automation Market, By Country8.2.4.1. Germany8.2.4.2. UK8.2.4.3. France8.2.4.4. Rest of Europe (ROE)8.2.5. Asia Pacific Hyper Automation Market, By Segment8.2.6. Asia Pacific Hyper Automation Market, By Country8.2.6.1. China8.2.6.2. Japan8.2.6.3. India8.2.6.4. Rest of Asia Pacific (RoAPAC)8.2.7. Rest of the World (ROW) Hyper Automation Market, By Segment8.2.8. Rest of the World (ROW) Hyper Automation Market, By Country8.2.8.1. Latin America8.2.8.2. Middle East & Africa

ToC can be modified as per clients' business requirements*

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Hyper Automation Market - Vendor Assessment (Company Profiles, Market Positioning, Strategies, Recent Developments, Capabilities & Product Offerings / Mapping), Technology Assessment (Developments & Economic Impact), Partner & Customer Ecosystem (Product Services, Proposition & Key Features) Competitive Index & Regional FootPrint by MDC Research

Key Questions Answered in This Report:

Vendor Assessment

Vendor assessment includes a deep analysis of how vendors are addressing the demand in the Hyper Automation Market. The MDC CompetetiveScape model was used to assess qualitative and quantitative insights in this assessment. MDC's CompetitiveScape is a structured method for identifying key players and outlining their strengths, relevant characteristics, and outreach strategy. MDC's CompetitiveScape allows organizations to analyze the environmental factors that influence their business, set goals, and identify new marketing strategies. MDC Research analysts conduct a thorough investigation of vendors' solutions, services, programs, marketing, organization size, geographic focus, type of organization and strategies.

Technology Assessment

Technology dramatically impacts business productivity, growth and efficiency.Technologies can help companies develop competitive advantages, but choosing them can be one of the most demanding decisions for businesses. Technology assessment helps organizations to understand their current situation with respect to technology and offer a roadmap where they might want to go and scale their business. A well-defined process to assess and select technology solutions can help organizations reduce risk, achieve objectives, identify the problem, and solve it in the right way. Technology assessment can help businesses identify which technologies to invest in, meet industry standards, compete against competitors.

Business Ecosystem Analysis

Advancements in technology and digitalization have changed the way companies do business; the concept of a business ecosystem helps businesses understand how to thrive in this changing environment. Business ecosystems provide organizations with opportunities to integrate technology in their daily business operations and improve research and business competency. The business ecosystem includes a network of interlinked companies that compete and cooperate to increase sales, improve profitability, and succeed in their markets. An ecosystem analysis is a business network analysis that includes the relationships amongst suppliers, distributors, and end-users in delivering a product or service.

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Regions and Countries Covered

North America (US, Canada), Europe (Germany, UK, France, Spain, Italy, and Rest of Europe), Asia-Pacific (Japan, China, Australia, India, Rest of Asia-Pacific), and Rest of the World (RoW).

Report Coverage

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Nanoparticles and other nanomaterials are essential components of cutting-edge science and technology, including photochemistry, energy conversion, and medicine. New research suggests that automating nanomaterial synthesis can reduce the environmental footprint of these advanced materials while at the same time improving quality and scalability.

Image Credit:Ico Maker/Shutterstock.com

The groundbreaking paper, Towards automation of the polyol process for the synthesis of silver nanoparticles makes the argument for automated synthesis to enable the manufacturing of colloids with properties that are precisely tunable and crucially for industrial nanomaterial synthesis reproducible.

The study, which was published in the journal Scientific Reports in 2022, could have a significant impact in various fields of science, as the metal nanoparticles its authors synthesized are used at the forefront in photochemistry, energy conversion, and medicine.

The interdisciplinary team behind the paper materials researchers, nanotechnology specialists, and chemical engineers from Germanys Federal Institute for Materials Research and Testing (BAM), Max Planck Institute of Colloids and Interfaces, and Humboldt-Universitt zu Berlins Department of Chemistry focused their research on silver nanoparticle synthesis.

Silver was a suitable test candidate for the automated synthesis method because, while it is one of the more commonly used nanoparticles due to its antibacterial properties and sensing and catalysis applications, it is difficult to produce in well-defined products. The obstacles to this are silvers high polydispersity: it is difficult to precisely control or tune silver nanoparticles sizes.

Responding to this challenge, the German researchers developed an automatic approach for on-demand silver nanoparticle synthesis. The method enables fabricators to synthesize silver nanoparticles between 3 and 5 nm, employing a modified polyol process.

To test their results, the team employed small-angle X-ray scattering, dynamic light scattering, and a number of other investigations. All results showed that the new automated synthesis method is suitable for yielding reproducible and tunable properties in synthetic colloids.

Synthetic nanomaterials are made with shapes or structural components that measure between 0.1 and 100 nm or 0.1 to 100 billionths of a meter. The metal nanoparticles that the present research focuses on find numerous applications in research, medicine, and technology contexts.

Synthesis methods for nanoparticles have to provide a high degree of control over the nanoparticles size, shape, and polydispersity while limiting the effects of aggregation or agglomeration (ensuring an even distribution). They also need to take into account the rheological properties of nanoparticle dispersions and the long-term stability of the solution.

Challenges with synthesizing nanoparticles include reproducibility and colloidal stability. These challenges mean there are limited nanoparticle-based references available, despite calls for such materials from environmental, health, and safety concerns for a number of years.

For example, gold nanoparticles are ubiquitous in nanotechnology due to their straightforward synthesis requirements, distinct size regulation, and ability to realize predictable nanoparticle sizes and dispersion.

But, despite a high demand due to silvers well-known antibacterial properties and use in catalysis, photochemistry, sensing, and optoelectronics, silver nanoparticles remain difficult to synthesize with available methods.

One available method is based on a polyol process. Here, silver nanoparticles are formed by reducing silver ions in the presence of polyacrylic acid in hot ethylene glycol. The ethylene glycol acts as both a reducing agent and a solvent.

This method is considered important because it stabilizes nanoparticles in a water-based solution by adjusting the solutions pH balance to 10, creating a negatively charged shell that means particles can remain unchanged in the suspension for over six months.

As a result, the nanoparticles produced make good candidates for reference materials. Reference materials are used in nanomaterial synthesis to quantify the size, distribution, and concentration of nanoparticles in doped materials.

Reference materials need to be made in bulk and able to remain stable for a long period of time in storage to be useful. The adapted polyol process described above can achieve these requirements, although it is not best suited for the task.

To develop reference materials like silver nanoparticles faster, researchers focused on developing an automated platform for rapid on-demand synthesis.

An automated platform could avoid the need for bulk quantities and long-term stability by offering required reference materials to researchers at minimal cost and without excessive lead-in times.

It would also enable targeted testing of nanomaterials physicochemical properties and a shorter development cycle before arriving at the desired properties.

To achieve this, the German scientists developed an automated silver nanoparticle synthesis method with the polyol process producing a colloidally stable silver.

They deployed the so-called Chemputer for the first time in the field of inorganic chemistry. The Chemputer is an automated platform that was developed by the Cronin group to execute multi-step, solution-based organic synthesis and purification tasks.

The Chemputer works in a batch mode with common laboratory items like heaters and glassware connected to a backbone made out of HPLC selection valves and syringe pumps. Liquid solutions are transferred across the backbone and manipulated along its various modules in different ways.

Every operation is controlled with a software script, which ensures a high rate of reproducibility. The accompanying software also makes it easy to adjust the synthesis conditions as required and documents all changes in the reaction log file.

Caldern-Jimnez, B. et al. (2017). Silver nanoparticles: Technological advances, societal impacts, and metrological challenges. Frontiers in Chemistry. doi.org/10.3389/fchem.2017.00006.

Dong, H. et al. (2015). Polyol synthesis of nanoparticles: Status and options regarding metals, oxides, chalcogenides, and non-metal elements. Green Chemistry. doi.org/10.1039/C5GC00943J.

Kaabipour, S., and S. Hemmati (2021). A review on the green and sustainable synthesis of silver nanoparticles and one-dimensional silver nanostructures. Beilstein Journal of Nanotechnology. doi.org/10.3762/bjnano.12.9.

Wolf, J.B., et al. (2022). Towards automation of the polyol process for the synthesis of silver nanoparticles. Scientific Reports. doi.org/10.1038/s41598-022-09774-w.

You, H., and J. Fang (2016). Particle-mediated nucleation and growth of solution-synthesized metal nanocrystals: A new story beyond the LaMer curve. Nano Today. doi.org/10.1016/j.nantod.2016.04.003.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

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Should Nanomaterial Synthesis Rely on Automation? - AZoNano

The Covid-19 pandemic further complicated the ability of healthcare providers to collect on services rendered, a process that was already a challenge. A poll by MGMA in November 2021 poll found that 49% of medical practice leaders reported an increase in the aging of accounts receivable.

Healthcare Financial Management Associations (HFMA) 2021 Pulse Survey reveals that the pandemic has caused:

Many insurers are now taking more than 90 days to pay, despite most state and federal regulations mandating a 30- to 40-day remittance limit.

Another factor in lengthening the aging of accounts receivable is the current healthcare staffing shortage. Denied claims must be researched, reworked, and resubmitted to avoid write-offs, but overworked back-office staff doesnt have the time to be this tenacious.

This crisis has pushed an already dysfunctional healthcare revenue cycle to the breaking point, making it increasingly unviable to ignore the greater underlying inefficiencies. But this also creates an opportunity for providers to rethink and build an even better A/R strategy.

In this article, we go over how to build an intelligent, analytics-driven A/R strategy to significantly improve collections in todays healthcare environment. This article goes over the pillars of this approach as well as what metrics you should focus on in your implementation. First though, what are the limitations of providers current approaches?

Limited data and data analysis leads to revenue recovery deficits

Currently, providers generally rely on several, disconnected silos of data, leaving them with an incomplete and fragmented picture of their overall revenue cycle operations. The packaged reports their EMRs create from this disparate data fail to render sophisticated or often, even helpful, answers.

In addition, downloading the data index style and then analyzing it with simplistic, brute force manual techniques (think Excel spreadsheets) leaves providers with only a few dimensions on which to analyze it. Without a comprehensive view of the data, conclusions can be swayed by stakeholders subjective opinions.

This approach is extremely limiting. For example, when staff often only goes after high-dollar claims, they leave a whole slew of accounts untouched that could have been recovered. By the time staff determines that A/R has the potential for recovery, filing and field limits have passed and the debt must be written off. Decisions based on limited data lead to lower recovery and overall cash flow.

1. Analytics is the backbone of an intelligent A/R strategy

Robust, multidimensional analytics driven by artificial intelligence that can learn from itself, on the other hand, has the potential to deliver actionable information that translates into significant improvements in your collections.

2. Benchmark existing metrics and then effectively prioritize tasks

Your first task is to benchmark existing analytics and establish your metrics. Read about these metrics below. Good technology should be able to predict what A/R is recoverable, as well as prioritize tasks and realize revenue.

Machine learning is essential to do this as a simple set of rules will not be able to predict this alone.

Next, you need an effective way to prioritize recovery tasks that factors in your available resources. All A/R challenges arent equal. If you merely prioritize your outstanding accounts based on high-dollar claims, you arent factoring in the complexity and probability of recovery.

For example, a complex denial around prior authorization has a very low probability of recovery. So you have to be smart about which ones to tackle and recognize which ones arent worth your time. Claims resources are limited, after all. Analytics works hard to determine which claims have the highest recovery potential.

3. Use analytics to monitor and improve your A/R workflow

Good analytics can also provide real, data-informed metrics on how efficiently your staff and workflow are pursuing and winning A/R recovery and denials appeals. Efficient analytics depend on metrics that reveal changes over time.

To collect maximum revenue, you need a good workflow solution thats prioritizing the tasks and providing guidance to agents to help execute the recovery. Analytics can pinpoint bottlenecks in your recovery process; providers need to know where specialists stumble so they can troubleshoot.

Unfortunately, the EMRs that most providers currently have and rely on for analytics cant provide useful insights. Is it long phone times, particular kinds of appeals, or Cigna changing its guidelines thats causing the issue? Figuring this out from the comments section of an EMR is unfortunately very challenging. But an analytics-based workflow solution can provide these answers so you can optimize the results of your A/R collections process.

Best metrics and reports to reduce A/R aging

The first step to an effective analytics-based strategy is benchmarking existing metrics and comparing those to industry averages. This will allow you to identify and deep dive into trends and challenges.

Specific metrics and reports to focus on include:

For significant backlogs, bring in a partner to maximize collections

Many providers are already in a situation where they are dealing with significant aging of accounts receivable. In these cases, the fastest way to get revenue collection under control is to bring on a third party. A partner will help you to scale your recovery efforts rapidly so you can collect as much of the aging A/R as possible.

Experienced revenue cycle staff understand payer guidelines and can negotiate with payers to resolve A/R. These experts help providers achieve faster cash flow, fewer denials, and higher recovery rates. Particularly in our current staffing environment, however, these professionals are hard to find or train.

When engaging a partner, be sure to look for one who can offer both domain expertise and best practices from a workflow perspective for A/R. As you evaluate your third-party partner, make sure they know of and are dedicated to measuring the above metrics or make an effort to implement these analytics capabilities on your own to best utilize your staffs time.

A/R collections in a challenging environment

Kaufman Hall reported that the first month of 2022 was devastating for hospitals and health systems nationwide. As a result of the Omicron wave of COVID-19 cases, actual hospital margins were negative for the first time in 11 months. Meanwhile, expenses will continue to rise, with labor shortages and supply chain interruptions increasing costs. Volumes and revenue will likely continue to be unpredictable.

Providers cannot afford unnecessary revenue leakage in 2022. But your hospital or healthcare centers financial health does not have to be a sitting duck for this turbulent outlook.

Providers can unleash AI and machine-based analytics and workflow technologies to minimize losses during a period where demand for healthcare services is increasing. RCM inefficiencies are straining margins. Improve your A/R strategy now to create the cash flow and capital that propels your practice or center through the next decade.

Photo: adventtr, Getty Images

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How to use analytics and automation to build an intelligent A/R strategy - MedCity News