Daily Archives: January 5, 2022

The Cybersecurity and Infrastructure Security Agency has warned that in addition to greater efficiency, increased automation in the manufacturing sector will also bring greater digital risks that malicious hackers can exploit.

Manufacturers were already moving towards automation and remotely operated processes before the COVID-19 pandemic, but the onset of the virus led to a fierce acceleration of those trends as factories dealt with quarantines and limited the number of in-person employees on factory floors.

In a document published this week, CISA noted that this shift, while necessary for many companies to keep operations running, may also introduce unfamiliar technologies that increase the attack surface for cyber criminals, ransomware groups, and nation-state hackers.

For example, the shift to automation and remotely operated machinery requires retraining operators on new processes, strong connectivity, and a specialized cybersecurity workforce familiar with the intricacies of manufacturing technologies who can put in place effective policies around control, validation, and monitoring of cybersecurity risks.

Manufacturers have already been disproportionately targeted by ransomware actors and other cyber criminals during the pandemic, but CISA said that if current trends around automation hold, attacks against the sector are likely to get even worse as more vulnerable systems are brought online and connected to operational technology (OT) and machinery.

Environments previously air-gapped may become more connected to enterprise networks, as well as to public clouds, vendor networks, and other third parties for remote management, the agency warned. This rapid expansion of the threat landscape and attack surface has made it far more likely manufacturing organizations will experience a cyber event significant enough to degrade or impede safety and availability of production.

At a time when many brick-and-mortar companies struggle to stay open, automation has been a lifeline for the manufacturing industry. A report and survey on the sector conducted by Ericsson earlier this year found that 69% of businesses in the sector reported unchanged or improved financial performance during the pandemic, even as eight out of 10 said theyve had to cut costs.

There are signs that economic drivers could push the industry towards a wholesale transformation before it can adequately plan or assess what that future environment will look like and how it will operate. The cybersecurity implications of more widespread automation are just one of those unknowns. Theres also a major gap between how employers and employees perceive the future of the workforce.

Full automation is approaching, but neither decision makers nor production employees fully grasp the consequences, the report noted in one conclusion. While almost two-thirds of the surveyed manufacturers expect to be automated to at least 80 percent within 10 years, more than half of the production employees still believe more people will be needed in similar roles by 2030, and only 1 in 5 think companies will need fewer people. Close to 9 in 10 decision makers expect to use AI in their production processes within the next 10 years, however 3 in 4 think humans will still make at least half of all production decisions.

Like many industries, manufacturing needs to invest more in cybersecurity talent, whether through recruitment or retraining of existing staff. CISA said that given reduced crew density, it's essential for manufacturers to develop cybersecurity and operational knowledge within the shop floor environment. The agency also added that manufacturers must train security analysts so that these companies can conduct remote monitoring of factory environments.

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CISA highlights the gains (and security risks) of increased automation in the manufacturing sector - SC Magazine

Youve likely heard about the log4j cybersecurity vulnerability. Chances are, however, that youve mostly heard how this primarily affects public-facing internet systems. Some of the higher profile exploits of this vulnerability include penetration of Belgiums defense ministry, several ransomware hackings, and taking control of computers to mine cryptocurrency, according to the Washington Post.

Though no incursions of industrial controls systems via the log4j vulnerability have yet been reported, we do know that the potential exists. According to aDolus Technology, a supply chain cybersecurity provider, several million operations technology (OT) software packages use log4j. Most OT software suppliers use log4j because it is opensource software that effectively handles required logging tasks. aDolus explains that the log4j vulnerability (called Log4Shell) is a result of overly-provisioned features enabled byan insecure default configuration and the implicit trust of messages.

The National Institute of Standards National Vulnerability Database reports that Log4Shell has been disabled from log4j 2.15.0 and completely removed from version 2.16.0.

If you don't know that the software you use contains log4j, you won't know whether you should patch or block certain traffic, or perhaps do nothing at all.

As with most cybersecurity correction measures, protecting your operations requires identification of the vulnerability in your systems. After all, as aDolus notes, if you don't know that the software you use contains log4j, you won't know whether you should patch or block certain traffic, or perhaps do nothing at all.

According to aDolus, a software bill of materials (SBOMs) is the best tool for uncovering hidden vulnerabilities like Log4Shell. TheFACT platformfrom aDolus reportedly providesenriched SBOMsthat report all the subcomponents of a software package and can be a valuable tool for cybersecurity assessments. Source code analysis is another option if you have access to the source code, but that's often not the case in the OT world, according to aDolus.

More detailed information about mitigating Log4Shell and other log4j-related vulnerabilities can be found at https://www.cisa.gov/uscert/ncas/alerts/aa21-356a.

ISA99 Update

As 2022 began, the ISA99 Committee on Industrial Automation Control Systems (IACS) Cybersecurity issued an update to stakeholders about its focus moving forward considering the ever-evolving cybersecurity threats facing industry.

Key aspects of this notice from the committee include:

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Log4j Cybersecurity Concerns in Industry - Automation World

Germany is also the leading maker, just as a devoted adopter of assembling robots. Germany's blasting auto industry can be credited with driving the relationship between's bot thickness and modern development.

Germany is also the leading maker, just as a devoted adopter of assembling robots. Germany's blasting auto industry can be credited with driving the relationship between's bot thickness and modern development.

Then again, The United States falls behind different nations in availability for an undeniably robotized world.

Team Norvergence discusses the case of the USA w.r.t the Impact on Labour Market.

A significant long-run shift in U.S. labour markets is the reduction of middle-skill professions, like manufacturing and production positions, and the augmentation in both high- and low-skill employments, like administrative positions on one end and assignments that aid or consideration for others on the other.

As has been contended in the economic literature, the most probable drivers of occupation polarization are automation and offshoring because both these powers bring down the interest for centre ability occupations comparative with the rest.

Robotization alludes to any innovation that lessens the requirement for human help. For example, cycles, such as supermarket checkout, have been robotized by and large and require less work to perform routine errands.

Also, a few phrases of the creative interaction of a decent or administration can be acted in foreign nations; in this way, specific assignments can be re-appropriated. By and large, the sorts of projects that can be rethought are, for the most part, routine errands.

Work in routine occupations has been consistent or declining in recent years, and mechanization is one reason for this underlying change in the labour market.

The utilization of robots underway has been consistently expanding since the mid-1990s in most exceptional economies all over the planet.

We utilized an interesting dataset with data on the supply of modern robots at the degree of enterprises to build action for a driving zone's openness to robots.

Our examination uncovered a negative connection between mechanization and routine manual work in nearby labour markets, which upholds the proposition that robotization might be a significant driver of polarization in the work market.

While we zeroed in on routine manual occupations in this article, robotization could affect a more extensive arrangement of professions.

With propels in artificial reasoning and automation, a few intellectual abilities, for example, penmanship acknowledgement and pretrial research, have been robotized partially.

For example, other intellectual abilities, decision-production under testing circumstances in intensive care units(ICUs) may before long be enhanced by algorithmic proposals. In this way, mechanization can have extensive outcomes that might prompt immediate changes in the labour market.

Robotics Automation Industry in Germany

Germany's mechanical technology and mechanization (R&A) industry has appreciated remarkable accomplishment throughout the last decade or thereabouts, nearly multiplying turnover in the period 2010 to 2019. The primary indications of post-Covid recuperation are being felt, with the area conjecture to produce a turnover of EUR 13.4 billion every 2021.

The R&A enterprise is one of the most imaginative German mechanical design areas. German OEMs number among the world's driving R & R&A organizations. Human-robot collaboration (HRC) and machine vision (MV) technologies are essential qualities in a worldwide centre that flaunts mechanical technology players from all markets sections. Machine vision considers one of the significant development areas in the R&A business and has turned into the critical innovation for the robotization business around the world.

The expanding application level of HRC addresses an ideal illustration of the move towards network inside cutting edge production. Innovative improvements in automated reasoning, including A.I. and profound learning, will prompt further uses of ordinary modern robots and cooperative robots.

Automation and the execution of machine vision (MV) innovation assist with making reliably excellent, long-lasting detectability and 100% creation exactness a reality. Significant degrees of creation adaptability can be accomplished, and item changes are immediately acknowledged utilizing adequate robotization arrangements.

Germany is the important deals market for the European picture handling industry, with more than 30% of total industry turnover produced locally.

Past the car business and the electrical and hardware enterprises (counting semiconductors), different areas - including the metal, food, and bundling just as non-assembling ventures (for example, intelligent traffic technology, indicative clinical gear and surgical technologies) - are progressively utilizing machine vision innovation.

Machine vision plays a significant enhancement in Industrie 4.0 because of its excellent information social affair and investigation capacities.

Industrie 4.0 has turned into a global by-word for insightful, organized creation - with Germany solidifying its notoriety as the world's plant supplier and a country equipped for meeting the difficulties of the automated age.

Collaborative robots ("cobots") supplement creation is brilliant industrial facility conditions and makes automated producing reasonably for SMEs not beforehand ready to bear the cost of turnkey arrangements.

R&A innovation gives the central components to the shift towards Industrie 4.0. Cooperative robots support human work via robotizing dreary and truly requesting undertakings.

They can be employed in present-day creation locales for various applications and don't need confines. Pick-and-place arrangements address one common space of cobot movement.

Human-robot collaboration exercises work with speedy preparation and can be controlled using stages that permit robots to be conveyed at the proper workstation and the responsibility to be expanded or diminished subject to changing creation prerequisites.

Even though robots don't influence the entire business, they affect fabricating work in Germany. We ascertain that one extra robot replaces two blue-collar positions overall. This suggests that robots have obliterated approximately 275,000 full-time producing occupations in 1994-2014.

However, those sizable misfortunes are completely counterbalanced by work gains outside assembling. As such, robots have unequivocally changed the work structure by driving the decrease of blue-collar positions.

Robots were answerable for practically 23% of this decrease. Be that as it may, they have not been significant executioners up until this point regarding the complete number of positions in the German economy.

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In the case of Robotic Process Automation- Germany is far ahead of the USA | RoboticsTomorrow - Robotics Tomorrow

The world of banking and finance faces aggressive change in innovation, increasing the need to adapt to new evolutionary cycles in financial technology. As customers want more resources and guidance with their finances, institutions such as JPMorgan Chase must nimblyrespond in a waythat belies their large size.

Gill Haus, CIO of consumer and community banking (Chase) at JPMorgan Chase, spoke with InformationWeek about his institutions approach to finding the right tech talent to meet demands for innovation, the growing importance of automation, and the personal directives he follows.

When looking at technology recruitment, what skillsets isChase seeking, both to meetcurrent needs and alsofor what may come next?

At the root of what we do, we are in the business of building complex features and services for our customers. We have about 58 million digitally active customers; they depend heavily on the services we provide. Technology is behind all those products and services we offer. We are looking for the quintessential engineers that have the background in Java, machine learning engineers, those that have mobile experience as well. We also have technologies that are in heritage -- systems that weve had for many years and were looking for engineers that understand how to use those technologies. Not just to support them but to modernize them. The key of our practice is to make sure also that we have those engineers and talent in general that is adaptable because the market is constantly changing.

Why this is important is not just so we can have talent come in and help us build great solutions; it is also a great opportunity for talent to grow themselves. We provide our employees opportunities to use those new technologies whether its public cloud, private cloud, or machine learning. Also, to grow the breadth of their experiences, whether theyre working on mobile technologies, backend systems, or some other solution that touches millions and millions of customers. We offer our employees the opportunity, whether they are an entry-level software engineer, we have programs like our software engineer program where we bring in talent from universities and boot camps to do training. We offer things across the organization where our talent can contribute and learn with teams to build solutions, learn how to use other technology, and become more adaptable.

Are there particular technologies or methodologies that have come into play of late that Chase has wanted to adopt or look at?

Weve made a large move to be an agile organization to organize around our products versus organizing around our businesses. The reason for that is we need to be able to build solutions quickly and those local teams -- the product, technology, data, and design leaders -- theyre more able to see whats happening in the market, make decisions quickly, decide what to build or what service to provide, and make sure were applying that for our customer versus being organized in a way that makes it more difficult to operate.

The move to an agile work style is really key for us to compete.

The other [part] is the skills themselves. At our scale, machine learning absolutely. We have tons of data about our customers, on how customers are using our products. Customers ask us to provide them insights or guidance. If you go into our mobile app, we have something called Snapshot that tells you how youre spending money compared to other people like you, ways you can save. Machine learning is the essence and power behind making that happen.

Mobile engineering is also incredibly important for us because more and more of our customers are moving to be digitally active in the mobile space. We want to be where our customers are.

What isnt often talked about is a lot of our backend services, which is the main Java programming that we do, empowers all of this. From APIs to public cloud because when you deposit money, youre using those rails. When you are executing machine learning models, youre still using a lot of those rails.

While we are focused on a lot of the new, were also focused on modernizing the core that we have because that is so fundamental to the services we provide.

In terms of scouting tech talent, is there an emphasis on finding brand new graduates of schools that offer the latest skills, retraining existing staff to make use of their institutional knowledge as well?

All the above. The purpose-driven culture we have is really a big factor for us. Money is at the center of peoples lives. If you can create a positive experience for customers in using their money, whether they are able to save more, to pay for something they didnt expect, or prevent fraud for them, it provides an incredible positive benefit to that individual. Thats important. Many of the people joining, or already at that firm, want to have that positive impact.

One of our software engineering programs is called Tech Connect, which is how we get in software engineers who might not have come in through the traditional software engineering degrees. Its a way for them to go through training here and find a role within the organization. We also have the software engineering program where we look at entry level candidates coming in from colleges with computer science and other engineering degrees. For employees that we have here, we have programs like Power Up, which is at 20 JPMorgan Chase technology centers where over 17,000 employees meet on an annual basis. There they learn all different types technologies, from machine learning, to data, to cloud. That allows us not only to have people that are here be trained but it makes it compelling to join the firm.

What are some of your guiding principles as a CIO?

We want to remove roadblocks from people being about to do the jobs we want them to do so they can build incredible experiences for our customers. That is a main focus for us, but also diversity. Diverse teams are more innovative, are more productive. We should be doing that. Plus, we know our customers are diverse and we should reflect that as well.

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Chase's Gill Haus Discusses Recruitment, Agile, and Automation - InformationWeek

Wednesday 05 January 2022 6:05 am

Digital change and automation are driving enormous productivity gains in the world of work.

However, the rapid changes mean many individuals, businesses and even entire nations will be hugely impacted by automation and tech, with some roles and jobs to be replaced by robots altogether.

Many of the industries that are most at risk of seeing jobs being taken over by robotics have over time evolved to an automated process and fall into categories such as administrative tasks and manual labour.

Pricing platform Small Business Pricesanalysed a variety of metrics to find the countries most ready for the future due to their use of automation, and which jobs are most at risk. The company shared its findings exclusively with City A.M.

Out of 702 jobs analysed the occupation that ranks the highest for chances of being replaced by automation is telemarketing.

This is followed by title examiners, abstractors, and searchers roles that involve mainly clerical tasks in second place and hand-sewers come in as the third most likely to see their job be replaced by automated technology.

According to analysts, there are three aspects to jobs that ensure they are less likely to be affected by the increase of modern technology; those roles that involve genuine creativity, jobs that involve building complex relationships with humans and careers that have a high sense of unpredictability.

The study determines that the job thats the least likely to be replaced by tech is that of a Recreational Therapist; this is a role that involves the human aspect and complex relationship building which requires emotional skills robots are (not yet) capable of.

The jobs that are second least likely to become fully automated are First-Line Supervisors of Mechanics, Installers, and Repairers, due to the role being highly unpredictable; one will never know when and where an expert in this field will be needed and problems are often nuanced, hence the need for human touch.

Emergency Management Directors are the third least likely to see their bread and butter be taken over by robotics. Given the sensitive nature and nuance of their jobs and again the unpredictability of things such as natural disasters and emergencies, it will remain a human task to delegate back to safety.

On average, 74 robots for every 10,000 employees will be performing tasks in the manufacturing industry. South Korea, however, leads the world rankings in terms of implementing robotics in their manufacturing processes: 631 robots per 10,000 human workers in 2016.

This is followed by another Asian nation known for its big technological advancements: Singapore. As of 2016, 488 industrial robots are put in place for every 10,000 employees.

Germany is the third most advanced country in terms of implementing robotics in their production lines with 309 robots per 10,000 people.

Technological advancement and the automation of various processes arent limited to just the workforce; governments also need to ensure they arent stuck behind when it comes to automation.

Looking at a variety of factors such as the availability of online services, human capital and the level of telecommunication infrastructure weve determined which countries are leading the way and are deemed the most future-proof.

Coming in first is the European government of Denmark, scoring highly for every metric researched such as E-government (electronic government) scoring 0.9758 with the highest possible score being 1.

This in essence means the utilisation of the Internet, computers, and other digital communications by a government.

Another aspect Denmark scores high on (0.9643) is e-participation, which means many services provided by a government such as administrative purposes and decision-making involve technological advancement.

In second place is the government of a country home to many tech giants; South Korea. The Asian republic scores 0.956 on the e-government index, as well as a full 1 on both the e-participation and online service index.

Third place is for another European government; Estonia. It scores high on all metrics including 0.9941 on the online service index, 0.9266 on the human capital index, and 0.9212 in terms of telecommunication infrastructure.

Iran has made big advancements in terms of technological and educational advancement in recent years, which could be a contributing factor to the massive amount of jobs that were created across markets and taken on over the last decade; between 2012 and 2019 the country saw an increase of employment of 29% across all sectors.

Following suit with an increase of an employed population of 27%, is the European country of Lithuania, as well as The Netherlands where employment rates saw an increase of 21% in recent years.

The industry that has experienced the biggest dip in employment over the past decade is the sector of clerical support workers, which saw a decrease of 13.5 per cent from 2012 to 2019.

According to the research, these are the types of jobs most at risk of dying out. Following are Market-oriented skilled agricultural workers as well as Handicraft and printing workers, which both saw a decrease of employment of 10 per cent.

Other sectors such as sales and agricultural careers have seen no increase in the availability of jobs despite the increase of demand.

Out of all nations analysed, South Korea by far spends the biggest percentage of their Gross Domestic Product on projects relating to research and development. With 4.1 per cent, this investment is helping the country move forward and keep up with technology to ensure its future-proof, which lines up with the nation being the second-best e-government.

Japan invests the second-biggest amount of their GDP into research and development with 3.4%, followed closely by Switzerland which spends 3.2 per cent on keeping up with technological advancements.

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Tech Special: The jobs, sectors and countries most at risk of automation and robotics in 2022 - City A.M.

Even though manual application testing is the norm in most IT environments, it can add unnecessary risks, delays, and complexities to long-term digital transformation plans. Once automated, this task can drive faster application releases and dramatically lower the cost of moving to intelligent technology.

Application testing is one of those tasks that IT organizations know they cannot do without but wish it consumed less of their time, budget, and resources. With limited visibility into test conditions, upcoming software release cycles, and overly broad scopes, teams constantly react to bug-laden user experiences, delays to user productivity, poor integration, and excessive hypercare to address production errors.

Some organizations, however, are rising above these challenges by automating application testing. According to the commissioned Forrester Consulting study, "The Total Economic Impact of SAP Application Testing Solutions by Tricentis," automation accelerates application delivery as much as four times - with fewer errors, less risk, and higher time to value.

Forrester also noted that scaling automation across the application life cycle with technology, such as SAP application testing solutions by Tricentis, can yield a 334% return on investment (ROI) and organizational benefits totaling upward of US$7.8 million over three years. And more importantly, the intelligent nature of automated testing produces a wide variety of benefits that can energize a future of meaningful digital transformation.

By leveraging change impact analytics, organizations can determine the conditions that should be tested to reduce errors and those that do not carry that risk. As a result, the number of conditions that need to be tested for a single application can be reduced by 84%, compared to manual testing methods.

An ERP principal test manager who participated in the Forrester study remarked how an automated testing solution enabled the identification of programs impacted by any given change. Instead of running all conditions to mitigate all risks, the organization only works on approximately 20% of the initial scope.

With a narrower testing scope, organizations can also decrease errors and bugs in an application moved to production - from an average of 1.5 to 0.3 per project. And for users, their application experience can become one that enhances their productivity as quickly as their first interaction.

By reducing the risk of incidents that made it into the application during development and in production, IT teams can positively impact employees' everyday work experiences. Workplace frustration declines, workloads are lower, and the need for hypercare is minimized.

Even if 70% of their testing processes are automated, moving closer toward full automation can prompt a 25% savings in testing-time costs. For some teams, that is an equivalent of 10,000 person-hours that can be reallocated to more strategic projects. And the impact is even more significant within six months, when a team moves from a 100% manual testing model to an enterprise continuous testing solution that enables 50% automation.

Additionally, the use of embedded machine learning in application testing solutions can establish self-healing test cases, lowering test costs even further.

The added effect of automation that is difficult to miss is the opportunity to accelerate the time needed to test all relevant conditions, improving release rates by 300%. In the past, IT organizations may have gone live with new applications every six months with manual processes. Now, they can release new features, applications, and mobile apps in a matter of two months or four more times annually.

This advantage opens the door to an improved transition to intelligent solutions and platforms, such as SAP S/4HANA Cloud. Organizations can migrate faster and at a lower cost with automated testing than manual methods.

Just think of the possibilities when performance testing goes from 20 person days to one hour. When automation reduces the time required by 99%, IT teams can conduct performance testing once or twice a week - instead of quarterly - to help ensure updates and added features function as designed.

In one of Forrester's interviews with study participants, an IT services test manager noted how the gains achieved through automation go beyond just faster application delivery. Since users only need to verify that they have the capabilities necessary to get work done, his team can now confidently skip manual regression testing.

These outcomes of automated application testing put application developers and the rest of the IT organization in an enviable position in their company's digital transformation journey. They are not only delivering applications that improve process efficiency and business productivity, but are also empowering the entire workforce to adapt and respond to changes in highly engaging, purpose-driven, and strategic ways.

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SAP : Five Ways Automated Application Testing Adds Value to Your Business - marketscreener.com

By Douglas Greenwell, Chief Strategy Officer,Duco

The way a business manages its growing volumes of data can make the difference between clear insights that aid business growth, and slow reporting processes that cost time, money and fall short of regulatory standards.

The accelerated momentum for improving data quality in financial services has been driven by growth in digital services all of which rely on high quality data combined with the pandemic shedding light on the issue of data integrity and data reconciliation.

Laws and regulations such as BCBS 239, Sarbanes-Oxley, Basel III, SFTR, IFRS17, GAAP and the new US depository regulations are also making compliance increasingly complex, requiring organisations to guarantee that appropriate systems and procedures are in place to effectively manage and control operational risk.

Despite the mission-critical reliance on good quality data, many financial services firms are still using outdated legacy systemsand manual processes to managetheir reconciliations. These systems are unable to handle complex and changing data formats, resulting in inconsistencies that require human intervention.

The current state of data reconciliation

Financial services organisations are at breaking point with their current legacy systems and manual processes.

Manual processes and legacy systems are not only costing organisations a lot of money and man hours, but they are also causing problems with transparency, which can also have costly affects in the form of regulatory fines.

Financial firms are at this breaking point because many organisations are finding that the amount and complexity of data they now handle as a business is unmanageable with their current systems and processes. And this complexity is leading to transparency issues, with the lack of a transparent, consolidated view of reconciliations being a major problem.

Concerns about data inconsistency and lineage issues are also at the front of companies minds as they plan for future growth. Without automation, automated data lineage is not possible, meaning that instead of a holistic view of the data presented in a structured way, financial services firms are dealing with unstructured data silos with teams and individuals unable to see how upstream data feeds affect them and what downstream business processes rely on their data.

In fact, in a study conducted by Duco surveying 300 heads of global reconciliation utilities, chief operating officers, heads of financial control and heads of finance transformation working in large financial services organisations nearly half (42%) of financial services firms said they are currently struggling with poor data quality and data integrity within their organisations.

Why change is difficult

While agility and fraud are big drivers of the move towards automation and away from legacy systems, often the biggest business case for change is simply cost control. When businesses assess the cost of ownership of technology from data normalisation, data prep and infrastructure to hosting, running and upgrades, the opportunity for technology rationalisation becomes clear.

However, despite there being a compelling argument for changing the status quo, businesses are still finding it difficult to shake things up.

According to our survey, 44% believe that reconciliation without manual processes would be too challenging due to the different types and sources of data they are dealing with. A further 42% believe that the risk of disrupting their business to improve data reconciliation is not worth the benefits of data automation.

But, while there is still some nervousness around the perceived disruption that a move to automation and machine learning will involve, the appetite to become more automated is strongly evident amongst financial services organisations.

Moving towards intelligent data automation

The pandemic, however, has provided the much-needed impetus for change, at a time when conveniently, intelligent data automation (IDA) has become commercially viable.

IDA is a data management strategy that uses no-code, cloud-based technology to automate and control all financial, operational and commercial data across an organisation helping firms to cut costs significantly while reducing risk and improving compliance.

With its use of fully customisable, low-cost solutions that can sit alongside or on top of legacy systems, an IDA approach is key to not only successfully managing data, but to unlocking the full benefits of that data for the business.

By employing an over-arching, self-optimised level of automation, an IDA approach enables businesses to get a detailed view of data across the entire enterprise. With this level of insight, financial services organisations can better understand the performance of their operations, uncover and address weaknesses and identify new opportunities, all of which drives greater efficiency and agility across the organisation and improves regulation reporting accuracy.

With internal and external factors pressurising firms to change, financial services organisations are beginning to look towards IDA as a tool to secure their prosperity in the long term.

Encouragingly, almost half (49%) of financial services firms surveyed say that intelligent data automation is the future, and organisations will need to embrace it to survive. Furthermore, 42% say they will investigate the use of more machine learning in 2021 for the purposes of intelligent data automation.

Covid-19 has accelerated the adoption of machine learning and data automation. We can expect this momentum to continue, driven by the benefits to the business and the end user which make IDA a game-changer for financial services compliance, risk management and in reducing costs.

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Why intelligent data automation is important and how to harness it - Global Banking And Finance Review

DUBLIN--(BUSINESS WIRE)--The "Digital Technology Innovations in Preoperative Surgical Planning" report has been added to ResearchAndMarkets.com's offering.

Rising healthcare and surgery costs are increasing the burden on healthcare systems, making it difficult for hospitals to offer high-quality care at affordable prices. Time-consuming manual processes that significantly impact surgeon time and workload, hospital cost increases due to delayed surgery, and low patient satisfaction levels due to human error are the current challenges in surgery.

Artificial intelligence technologies are increasingly critical in preoperative surgical planning to help surgeons create accurate surgical plans, assess patient risks of intraoperative and postoperative complications, and improve patient outcomes. AI refers to the capability of a computer program to perform tasks and processes associated with human intelligence. AI enables risk assessment, systems scheduling, segmentation of anatomical structure, and automation in the preoperative phase during a surgical procedure.

The growing adoption of AI and ML technologies in surgical planning will accelerate due to their potential to reduce costs, shorten patient wait times, generate precise data for clinical decision-making, and improve surgical outcomes.

Key Questions This Research Will Answer

Key Topics Covered:

1. Strategic Imperatives

1.1 Why Is It Increasingly Difficult to Grow? The Strategic Imperative: Factors Creating Pressure on Growth

1.2 The Strategic Imperative

1.3 The Impact of the Top Three Strategic Imperatives on AI in the Preoperative Surgical Planning Industry

1.4 About the Growth Pipeline Engine

1.5 Growth Opportunities Fuel the Growth Pipeline Engine

2. Key Findings

2.1 Research Methodology

2.2 Key Findings

3. Growth Environment and Market Segmentation

3.1 Scope of Analysis

3.2 Market Segmentation

3.3 Application Segmentation

3.4 High Healthcare Expenditure and Costly Surgical Procedures are Key Challenges

3.5 Artificial Intelligence has the Potential to Address Preoperative Surgery Challenges

4. Technology Snapshot

4.1 AI Mimics Intelligent Human Behavior and Analyzes Large and Complex Datasets to Identify Patterns and Make Accurate Predictions

4.2 AI Offers Anatomical Classification, Alignment, and Automation at High Speed with Accuracy

4.3 Growth Drivers for AI Innovation in Preoperative Surgical Planning

4.4 Growth Restraints for AI Innovation in Preoperative Surgical Planning

4.5 AI is Transforming Current Surgical Practices with Advances in Automation, Navigation, Imaging, and Robots

4.6 AI/ML Supports Automating Routine Tasks in Preoperative Surgical Planning Phase to Improve Patient Outcomes and Save Surgery Time and Costs

5. Technology Snapshot - Orthopedics

5.1 AI Technologies Reduce the Surgeon's Time Spent on Manual Image Analysis and Healthcare Costs, and Improve Patient Outcomes

5.2 AI Technologies Enable Surgeons to Study the Granularity of Anatomical Structure to Improve Preoperative Surgical Planning

5.3 Novel AI Technologies in Research Optimize the Selection of Implants in Preoperative Surgical Planning

5.4 Accuracy of Large Datasets and Data Privacy are Major Challenges Affecting the Implementation of AI in Orthopedics

6. Technology Snapshot - Neurology

6.1 AI Technologies Support Surgeons to Identify Patients Requiring Immediate Surgical Intervention and with Preoperative Planning

6.2 Novel AI Technologies in Research Build AI Algorithms and Deep Learning Models to Automate the Segmentation of Brain Structure

6.3 Large Dataset Requirements for Model Training, Slow Program Development, and Regulatory Approvals are Crucial Challenges Affecting AI Implementation in Neurosurgery

6.4 Market Participants Developing AI/ML Technologies Should Evaluate the Features on Various Statistical Measures to Prove Their Utility

7. Companies to Action

7.1 Formus Labs

7.2 PeekMed

7.3 Omniscient Neurotechnology

7.4 Numex GmbH

7.5 Enhatch

8. Patent Landscape

8.1 China is the Innovation Hub for AI-based Technologies in Preoperative Surgical Planning

8.2 Key Patents

9. Growth Opportunity Universe

9.1 Growth Opportunity 1: National and International Partnerships Among Institutions to Build Large Databases to Train AI/ML Algorithms

9.2 Growth Opportunity 2: Data Scientist-Program Developer Community Ecosystem to Build Innovative and Reliable AI/ML Models or Algorithms

9.3 Growth Opportunity 3: Building Innovative AI/ML Technologies for Complete Automation in Preoperative Neurosurgery Planning

10. Key Industry Participants

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Global Preoperative Surgical Planning Digital Technology Market Report 2021: AI is Transforming Current Surgical Practices with Advances in...

Automated guided vehicles (AGVs) are a hot topic in industry. Yet, the seeds of today's advances were planted a century ago. But what were the technologies that have led to modern AGVs, and where do we go from here?

AGVs lineage as self-propelled vehicles can be traced back to DaVinci's plans for a self-propelled cart he made in the 16th Century and the Whitehead self-propelled torpedo from the late 19th Century. But it wasnt until after the 1930s that the three technologies critical for self-propelled vehicles and todays AGVs were developed:

1. The prototype electromechanical autopilot developed by Sperry in 1933 depended on gyroscopes to ensure an accurate heading. While today we use a miniaturized version of Sperrys development, the lineage is clear.

2. The plan to land a vehicle on the moon in 1961 encountered problems with the 2.5-sec. delay for the vehicle to receive commands sent from earth. To solve that problem, NASA developed the worlds first self-driving vehicle. It had cameras mounted to it and carried a computer programmed to analyze the cameras images and then follow a solid white line on the ground.

Some AGVs in industrial use today use similar technology to follow magnetic tape embedded in the ground or mirrors aligning a route, while others rely on laser guidance and retroreflectors to calculate their positions.

Current 2D and 3D mapping systems use cameras, LIDAR and ultrasound to train AGV vehicles to establish routes for subsequent use in a warehouse or factory.

3. In 1987, German engineer Ernst Dickmanns developed dynamic vision for vehicles. It used banks of cameras and microprocessors mounted on a vehicle to detect objects in the road, filtering out the inevitable noise to identify only objects deemed important.

An advanced version of this technology is still used today in AGVs, adding stereo cameras for depth perception or time-of-flight technology to measure the transit time of reflected light.

High-resolution CMOS sensors have been developed to emulate an eagles eye. Directly imprinted on the chip are micro-objective lenses of different focal lengths and fields of vision, allowing a computer-generated field of view with the widest possible viewing range.

These three developments are key components of AGVs in use today, yet to supercharge AGV development we needed the development of critical enabling technologies.

Industry 4.0 revolutionized business, driving efficiency and productivity through machine-to-machine communications and automation using the Industrial Internet of Things (IIoT). The synergy of big data and artificial intelligence, cloud computing and augmented reality leveraged diverse applications and technologies into previously unimaginable potential. Manufacturers and logistics providers were early adopters, introducing comprehensive materials handling and transportation systems.

However, businesses today find themselves at an inflection point in AGV evolution. Existing connectivity solutions constrain the advantages of newer technologies. So, while business owners prepare to digitize their businesses, those pursuing modern AGV technology are reluctant to install what may become restricting legacy hardware.

Business WLAN (Wi-Fi) and private 4G/LTE networks are currently used in manufacturing for remote machine and robotic control, process monitoring, predictive maintenance and current-generation AGVs. Wi-Fi supports AGVs with direct vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, while 4G/LTE systems support additional vehicle-to-network (V2N) connectivity. Yet, both systems come with peer communication limitations.

While mature, Wi-Fi is constrained by limited connectivity, having low range and reliability with high latency. It is also compatible only with other Wi-Fi devices and networks.

4G/LTE, while less mature, improves connectivity, range and reliability but retains an unacceptably high latency. It is also only backward-compatible with 2G and 3G hardware.

Both Wi-Fi and 4G/LTE are inherently unsuited for emerging AGV technologies.

V2X, the next big step, refers to vehicle-to-everything technology, which unlocks the power of AGVs and driverless cars. It includes enhanced augmented reality, cooperative driving, extended electronic (NLOS) vision and more precise positioning. V2X will be a game-changer for communication standards.

But V2X requires massive connectivity capacity. For example, it will need latency times of less than a millisecond for real-time applications and mobile broadband of more than one gigabit per second to support augmented reality. The connectivity must also be ultra-reliable.

5G technology offers a way to meet V2X demands. It will support the huge connectivity requirements and offer good range, high reliability and the low latency needed for real-time applications. 5G is also backwards-compatible with Wi-Fi and 2G, 3G and 4G networks.

5G technologies promise the next major changes in V2X connectivity and communication, smashing the current bottleneck stifling the evolution of automotive digitization and autonomous vehicles.

Yet, there is some work to be done. Industry legislation and global frequency allocation need to catch up with technological advances. Similarly, there are questions about security and privacy. Given that 5G promises to unlock the path from partial automation to full automation, where all driving modes are managed without human oversight, the question of failure tolerance is also critical.

While the term exponential is often hyperbole when used to describe change, there is no other adjective to better convey the huge acceleration of enabling technology in the last 10 years since the formalization of Industry 4.0. With 5G no longer a nascent technology, expect AGV development to advance quickly to full automation. And for those manufacturers considering AGV introduction, heres a tip: 5G appears to be the future.

Luke Goodwin is content marketing manager for FlexQube.

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Where are Automated Guided Vehicles Going, and How Will They Get There? - Machine Design

CLEVELAND, Jan. 03, 2022 (GLOBE NEWSWIRE) -- Nook Industries, Inc. (Nook or the Company), a leader in US engineered linear motion products and solutions announced today that it has sold the family-owned business to Braintree, Massachusetts based Altra Industrial Motion Corp. (Nasdaq: AIMC), a leading global manufacturer and supplier of motion control, power transmission and automation products. The Nook business, which will be integrated into Altras Thomson operating company in its Automation & Specialty (A&S) segment, expands the breadth of Altras linear products offering. Altra was deemed an excellent strategic fit as the Nook family evaluated potential suitors to acquire the 52-year-old business founded by Joseph H. Nook Jr. in 1969.

The Nook family is pleased to have found a strong strategic buyer with a history of not only preserving, but also building upon the products, brand equity and core competencies of their acquisitions. We are excited about the tremendous opportunities created by joining Altras industry leading suite of motion control products and brands. It was important for us to find a buyer that would build upon my fathers legacy, said Joseph H. Nook III, Nooks Chief Executive Officer and President. We also want to thank the Nook employees, past and present, that helped build my fathers dream into the Company it is today. Our family will be forever grateful to the dedicated and hard-working employees of Nook Industries.

KeyBanc Capital Markets, Inc. acted as financial advisor to Nook and Calfee, Halter & Griswold LLP served as legal advisor.

About Nook Industries

Founded in 1969 by Joseph H. Nook, Jr., Nook provides a broad-based offering of premium linear motion solutions. Nook provides clients with proven knowledge and flexibility to design, engineer, and manufacture premium quality linear motion systems and solutions for their most challenging applications. Its customers benefit from a wide range of premium products and services that fit well into unlimited industries.

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About Altra Industrial Motion Corp.

Altra is a premier industrial global manufacturer and supplier of highly engineered motion control, automation, power transmission, and engine braking systems and components. Altras portfolio consists of 27 well-respected brands including Bauer Gear

Motor, Boston Gear, Jacobs Vehicle Systems, Kollmorgen, Portescap, Stromag, Svendborg Brakes, TB Woods, Thomson and Warner Electric. Headquartered in Braintree, Massachusetts, Altra has over 9,000 employees and 48 production facilities in 16 countries around the world.

CONTACT:

Nook Industries (216) 271-7900

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Nook Industries, Inc. Sells Family Business to Altra Industrial Motion Corp. (Nasdaq: AIMC), a Leading Global Manufacturer and Supplier of Motion...