In this whitepaper:
Creating Value Through Digital Transformation
Yokogawa’s Value Proposition
Four Emerging Themes DrivingThe Future of Automation
Industrial Operations Get Smart
Artificial Intelligence Delivers Insights
Seeing Double, Virtually
The New Reality Bridges Gaps
Links Within and Between Industries
Co-creating Value with Customers
Works Cited
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Technologies such as the Internet of Things, artificial intelligence, virtual and augmented reality and blockchain are becoming familiar to many people through consumer goods. But they hold even greater promise for industry, where they will allow companies to do more, with greater safety and efficiency and less energy and environmental impact. The Fourth Industrial Revolution is under way.
Digital transformation is a huge challenge. Most companies are in the first stage, digitization, adopting digital technologies to drive automation; or in the second stage, digitalization—using digital data to improve or simplify operations and generating new revenue through business models that put digital information at the core. The third stage is true digital transformation, in which digital developments lead to changes in business models that allow a company to capture and create value for customers. Fewer than 10% of companies in process industries have attained the third stage, in which data and digital processes permeate a company, informing decision making, optimizing operations, automating operations, innovating business processes and implementing smart manufacturing.
10
Fewer than 10% of companies in process industries have attained the third stage
%
Fewer than 10% of companies in process industries have attained the third stage
10
%
In a recent global survey by the Global Center for Digital Business Transformation,
only 31% of top corporate executives polled said their organizations were actively responding to digital disruption, even though half said it was affecting their industries and a third said it was transforming their industries, However, that response is up sharply from fewer than 1% in 2015. Clearly, the importance of digital transformation is getting the attention of top corporate management.
Digital transformation generates revenue and profit not only through immense new efficiencies but, most importantly, by helping a company better respond to customers’ demands and needs, not just today but as customers themselves evolve and grow.
of top corporate executives said their organizations
are actively responding to
digital disruption.
31
%
Innovating business processes
Realizing
smart manufacturing
Optimizing supply
chain
Automating more opreations
Creating
new business models
Generating further
revenue
Improving decision - making process
Changing culture, organization and
mindset
Companies can’t make the digital transformation alone. They need to leapfrog innovation by partnering with visionary specialists in digital transformation—experts fluent in both operational technology (OT) and information technology (IT). The critical success factor for true OT-IT convergence is business and domain knowledge. After all, an understanding of the key objectives for business and plant management is required before thinking about technologies and their implementation. Yokogawa integrates its business and domain knowledge with digital automation technologies and co-innovates with customers to drive their business process transformation in order to deliver Synaptic Business Automation. That creates new value by connecting everything, from data, systems and organizations to knowledge and supply chains, with business and domain knowledge, like a neural network.
Yokogawa’s Value Proposition
To support customers business challenges, Yokogawa has been expanding its capabilities from OT and IT to BM (Business Management) via process and business consulting. Yokogawa’s long-term experience in OT assures the reliable process data handling. The capabilities for IT, such as IIoT (Industrial Internet of Things), secure cloud and remote technology, cyber physical systems, digital twins, artificial intelligence, machine learning and big data analytics provide comprehensive expertise in the latest technologies. The unique combination of OT, IT and BM provides one-stop comprehensive solutions from business to operations.
Digital transformation depends on each company’s starting point. But regardless of how far a company has already progressed, four overarching themes are clear: the augmented operator; digitization, digitalization and platforms; new collaboration and innovation models; and lifecycle services.
Within those themes are rosters of technologies. This report will examine five in detail: the Industrial Internet of Things, artificial intelligence, digital twins, augmented and virtual reality and blockchain. The technologies are at different stages of development and adoption and even are starting to be used to complement each other.
Four emerging themes driving the future of automation
Augmented Operator
Digitization, Digitalization & Platforms
Yokogawa’s dedication
to customer excellence puts it at the forefront
of digital transformation in the industrial sector, and its focus on
co-innovation ensures that solutions are tailored to customer needs.
New Collaboration
& Innovation Models
Lifecycle Services
• Mobility
• Augmented reality (AR) / Virtual Reality (VR)
• Situation-based human-machine collaboration
• Expert systems,unmanned operation
• Interactive work instructions (IWIs)
Trends
Augmented
Operator
Industrial operations
get smart
What you know you can control for; risk comes from a lack of information. The Industrial Internet of Things (IIoT) allows industry to gather various types of information about field and operations and to analyze it. The IIoT embeds technology, such as sensors, in objects, systems, equipment and applications to allow those
things to communicate with each other, with people or with other systems.
The IIoT can improve productivity, avoid costly shutdowns and enhance worker safety. IIoT dashboards give executives visibility to the factory floor. The IIoT also gathers data for performance metrics that can cross organizational performance and escape siloed decision-making. Long-term trends of those performance metrics, combined with artificial intelligence, can warn when equipment needs maintenance—before damage occurs. The IIoT eliminates guesswork from business.
For example, temperature sensors deployed across a plant can quickly detect hot spots, even in difficult areas that previously would have been blind spots, such as on the surfaces of tanks or furnaces. By signaling hot spots in real time as they’re developing rather than after they have become a problem, plant- wide temperature sensors let managers know when to take action.
Sensors can alert remote managers to dangers. Fiber-optic sensors that stretch for kilometers can run all the way from, say, an oil-well drill hole to a pipeline, then a midstream storage tank, through a pipeline again and to a downstream plant like a refinery. Such comprehensive sensor coverage not only enhances safety, it gives managers visibility to the entire process, letting them see any problems at the precise location so they can take action quickly.
The global IIoT market is expected to top US$176 billion by 2022, with compound annual growth of more than 8% over the next four years, according to Market Research Engine.
$176
billion (USD) by
2022
Industrial
operations
get smart
Artificial intelligence delivers insights
Making sense of all the data from IIoT sensors requires serious computing power and specially designed algorithms that can spot patterns and thus make predictions and, based on those, make decisions about what to do next, without human intervention — artificial intelligence (AI).
Compound annual growth for the global market for AI is forecast at over 35% between 2015 and 2022, according to Orbis Research, with the fastest growth in Asia Pacific. AI adoption is being driven by sectors with many digital natives, while industrial companies have been slower to adopt it, largely because of a talent shortage. It’s why some companies are turning to partners to bridge the AI knowledge gap.
One form of AI, machine learning, is helping to bridge the talent gap. Many companies are facing a shortage of engineers at production sites who are experienced enough to detect anomalies just by noticing unusual noises, vibrations or deformations in equipment. The myriad inputs, collected by engineers’ senses, are analyzed through the prism of their years of experience. In the absence of enough skilled engineers, sensors can collect many measurements—more numerous and accurate than humans can do—which are transmitted to a machine-learning program that analyzes them to calculate an anomaly score. Like a human, the machine gets better at the job over time.
AI not only is important for using the IIoT to its fullest, but is crucial for deployment of other technologies such as robotics, autonomous vehicles, computer vision and virtual agents.
AI is forecast at over 35% between 2015
and 2022, according to Orbis Research, with
the fastest growth in Asia Pacific.
In pumps and pipes, the formation of bubbles, called cavitation, can reduce efficiency at the least and cause failure at the worst. Traditionally, cavitation would be detected only when nearby workers noticed noise or vibration from bubbles popping. Instead, sensors and actuators measure and collect data that then goes into an AI cavitation machine-learning model to accurately predict when cavitation is starting. This allows pumps to operate at maximum efficiency, because flows can be adjusted in real time to avoid cavitation or stop it before it can do damage.
Another application for AI is robotics. Collaborative robots use AI and machine learning in order to work with unpredictable situations—like alongside humans—or to be reprogrammed for new tasks. Industrial robot sales rose 31% to 387,000 in 2017 from a year earlier, with more than three million industrial robots forecast in factories by 2020, according to the International Federation of Robots. The market for AI robots is expected to grow to US$12.36 billion by 2023, from US$3.49 billion this year, according to Research and Markets.
The beauty of pairing AI with industrial automation is that it produces synergies far beyond what either can do alone, and, thanks to machine learning, keeps improving.
35
%
Seeing double, virtually
Digital twins combine the IIoT and AI to reproduce certain facilities and products digitally. This allows a company to do simulations on the digital version—a safer, cheaper and faster alternative to real-life testing. Digital twins cut cycle times and improve agility by allowing for quick design changes.
The IIoT provides the data needed to know how, for example, machinery actually is working. AI analyzes the data to forecast preventive maintenance, optimize operations or run models. The virtual image of the physical asset—whether a product, a machine or an entire facility—can be maintained throughout the asset’s life cycle and can be accessed easily from multiple places at any time.
For example, high-fidelity, molecular-enabled digital twins of refinery and petrochemical plants in the cloud use data from control systems, historians and labs for constant monitoring and analysis.
Forrester predicts the digital twin will lie at the heart of digitized industrial processes. The fastest growth is likely to be in Asia-Pacific, where IIoT sensors are being deployed at a rapid pace, connected to the cloud, MarketsandMarkets forecasts.
They enhance efficiency by allowing parameters to be
fine-tuned in real time for optimal performance, cutting
downtime and maintenance costs.
The New Reality Bridges Gaps
Virtual reality (VR) and augmented reality (AR) offer an opportunity to reduce human error by standardizing processes and creating a digitized log of actions taken. VR and AR also can be used to train employees, especially to teach them how to handle rare but dangerous situations, without actually exposing them to danger. In a report by A.T. Kearney and the World Economic Forum, pilot programs of AR and VR in training improved operator productivity 25% while decreasing time needed to learn the new skills.
For example, a mobile tablet with a distributed control system can recognize instruments that need field work, provide current process values and pull up information about the instrument, such as instruction manuals and maintenance records, so the engineer doesn’t have to go back to the office to look it up. Such
an AR tool can cut the time to calibrate multiple instruments by up to 47%.
AR can be especially effective when combined with
mobile technology—putting it in workers’ hands
in the field or on the factory floor.
Another example would help remedy the engineer shortage by creating a cloud-based platform that would allow young engineers in the field to show more experienced engineers in a control room the situation on the ground in order to share information and transfer advice about what to do. Although humans gather
information from all five senses, visual information makes up about 80% of perception. Rather than rely on novice engineers to try to put into words what is happening, they can instead both speak and show images of the field situation
via a video call to experienced engineers.
How we perceive information
is visual
80%
Oil and gas platforms often are in areas that are harsh and dangerous (polar zones) or downright off-limits to humans (deep sea). Such platforms are increasingly automated—sometimes fully automated. However, even automated facilities need maintenance, which is difficult not only because of the platforms’ locations and conditions but because skilled workers are expensive and difficult to find. Instead, platforms can be maintained by humans remotely, using AR and VR to operate robots that do the actual work on site.
Distributed ledger technology, or blockchain, is best known as the foundation for Bitcoin and other cryptocurrencies. However, blockchain’s applications are expected to touch any domain where trust, verification and security are important. With blockchain, all the parties have a copy of every transaction, and the transactions can’t be altered. They can, however, be searched, making them easy for members to see. The system engenders trust and is hard to attack. Blockchain is likely to bring down costs by eliminating the need for middlemen, while also enhancing cybersecurity.
Supply chains, for example, are global and often opaque, yet companies are under pressure from the public and from governments to verify every link. Issues include product safety, environmental impact, counterfeiting and conditions of suppliers’ employees. Despite the best efforts of companies to conduct due diligence, suppliers sometimes lie. Blockchain offers a means of irrefutable authentication—a potential
boon for supply-chain transparency.
Blockchain also can tell managers where spare parts are, or can track raw materials all the way back to their origin.
Eventually, blockchain will merge with the IIoT. Sensors will detect when parts need to be ordered; the signal will go to the central IT system, which will automatically send an order, with blockchain validating the process.
The market for blockchain solutions for utilities is forecast to grow to US$3.7 billion by 2026, Navigant Research predicts.
Links within and between industries
Blockchain is still rarely used outside cryptocurrencies. Although blockchain is simple, implementing it is complex. Its potential in industry is huge, as it offers a way to add cybersecurity at the moment industry is adopting the IIoT and enlarging its target surface.
In industry, AR and VR are used by only cutting-edge leaders at the moment. Businesses bought only 24,000 AR glasses last year, according to CCS Insight, but enterprise AR and VR sales are expected to hit a million units by 2022 as business applications multiply.
Co-creating Value with Customers
Digitally transforming industrial operations requires a deep understanding of operational technology and fast-developing digital technologies based on business and domain knowledge. The IIoT and AI are quickly becoming the norm for operations. AR and VR are moving into business from consumer applications.
Blockchain, though still very new in industrial settings, is developing fast. However, digital transformation isn’t a bolt-on addition. It must be integrated to create sustainable value by connecting everything such as data, systems, organizations, knowledge and supply chains with business and domain knowledge, like a
neural network.
For industrial companies, trying to keep pace with changing and emerging technologies requires lightning- fast management but also extremely capable and agile partners who can tailor the best solutions to their needs and speed them on the path to digital transformation. Yokogawa helps customers achieve digital
transformation through Synaptic Business Automation by providing its key enablers named “OpreX” with business and domain knowledge.
OpreX is the new comprehensive brand for Yokogawa’s industrial automation and control business. The OpreX brand stands for excellence in the technology and solutions that Yokogawa cultivates through the co-creation of value with its customers. The new brand encompasses all the Yokogawa control products,
services and other solutions that customers are using to digitalize and transform their businesses and drive growth in this time of unprecedented change.
Under the OpreX brand name and based on the Co-innovating tomorrow corporate brand slogan, Yokogawa will continue to co-create value with its customers and help to create a brighter future for all.
Creating Value Through Digital Transformation
Hover over each hotspot
• Supply / program-driven to
demand-driven models
• Blockchain-enabled custody tranfser
• Gain-share business models
• Open ecosystem approaches
Trends
New Collaboration & Innovation Models
Trends
• Outcome-based service offerings
• Asset-based apps
• Multi-year lifecycle service engagements
• Production-as-a-service (3D Printing)
• Operations and profit management
Trends
Lifecycle
Services
industrial robots in factories by 2020
million
+3
Market for AI robots this year is
(Billion USD)
b
$3.49
Industrial robot sales
rose 31% from 2016-2017
%
+31
(Billion USD)
By 2023, the market for AI robots will grow to
b
$12.4
Where next?
A Bold New World
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Transformation of Excellance (Download the printable version)
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Transformation of Excellence
Key Digital Technologies to Revolutionize Industry
Digitisation, Digitalization
& Platforms
• Advanced visualization
• AI/Machine learning and advanced analytics
• Cognitive-based diagnostics & decisions engine
• Intelligent / collaborative robotics
• Industrial Internet of Things (IIoT)
• Digital Twin
is from sound, smell, taste and touch
20%
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A Bold New
World
(Billion USD)
By 2023, the market for AI robots will grow to
b
$12.4
Market for AI robots this year is
(Billion USD)
b
$3.49
industrial robots in factories by 2020
million
+3
Industrial robot sales
rose 31% from 2016-2017
%
+31
Founded in 1915, Yokogawa engages
in broad-ranging activities in the areas
of measurement, control, and information. The industrial automation business provides vital products, services, and solutions toa diverse range of process industries including oil, chemicals, natural gas, power, iron
and steel, and pulpand paper. With the life innovation business, the company aims
to radically improve productivity across the pharmaceutical and food industry value chains. The test & measurement, aviation, and other businesses continue to provide essential instruments and equipment with industry-leading precision and reliability. Yokogawa co-innovates with its customers through a global network of 113 companies spanning 60 countries.
Wall Street Journal Custom Content is a unit of The Wall Street Journal advertising department. The Wall Street Journal news organization was not involved in the creation of this content.
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Technologies such as the Internet of Things, artificial intelligence, virtual and augmented reality and blockchain are becoming familiar to many people through consumer goods. But they hold even greater promise for industry, where they will allow companies to do more, with greater safety and efficiency and less energy and environmental impact. The Fourth Industrial Revolution is under way.
Digital transformation is a huge challenge. Most companies are in the first stage, digitization, adopting digital technologies to drive automation; or in the second stage, digitalization—using digital data to improve or simplify operations and generating new revenue through business models that put digital information at the core. The third stage is true digital transformation, in which digital developments lead to changes in business models that allow a company to capture and create value for customers. Fewer than 10% of companies in process industries have attained the third stage, in which data and digital processes permeate a company, informing decision making, optimizing operations, automating operations, innovating business processes and implementing smart manufacturing.
In a recent global survey by the Global Center for Digital Business Transformation,
only 31% of top corporate executives polled said their organizations were actively responding to digital disruption, even though half said it was affecting their industries and a third said it was transforming their industries, However, that response is up sharply from fewer than 1% in 2015. Clearly, the importance of digital transformation is getting the attention of top corporate management.
Digital transformation generates revenue and profit not only through immense new efficiencies but, most importantly, by helping a company better respond to customers’ demands and needs, not just today but as customers themselves evolve and grow.
Technologies such as the Internet of Things, artificial intelligence, virtual and augmented reality and blockchain are becoming familiar to many people through consumer goods. But they hold even greater promise for industry, where they will allow companies to do more, with greater safety and efficiency and less energy and environmental impact. The Fourth Industrial Revolution is under way.
Digital transformation is a huge challenge. Most companies are in the first stage, digitization, adopting digital technologies to drive automation; or in the second stage, digitalization—using digital data to improve or simplify operations and generating new revenue through business models that put digital information at the core. The third stage is true digital transformation, in which digital developments lead to changes in business models that allow a company to capture and create value for customers. Fewer than 10% of companies in process industries have attained the third stage, in which data and digital processes permeate a company, informing decision making, optimizing operations, automating operations, innovating business processes and implementing smart manufacturing.
In a recent global survey by the Global Center for Digital Business Transformation,
only 31% of top corporate executives polled said their organizations were actively responding to digital disruption, even though half said it was affecting their industries and a third said it was transforming their industries, However, that response is up sharply from fewer than 1% in 2015. Clearly, the importance of digital transformation is getting the attention of top corporate management.
Digital transformation generates revenue and profit not only through immense new efficiencies but, most importantly, by helping a company better respond to customers’ demands and needs, not just today but as customers themselves evolve and grow.
Technologies such as the Internet of Things, artificial intelligence, virtual and augmented reality and blockchain are becoming familiar to many people through consumer goods. But they hold even greater promise for industry, where they will allow companies to do more, with greater safety and efficiency and less energy and environmental impact. The Fourth Industrial Revolution is under way.
Digital transformation is a huge challenge. Most companies are in the first stage, digitization, adopting digital technologies to drive automation; or in the second stage, digitalization—using digital data to improve or simplify operations and generating new revenue through business models that put digital information at the core. The third stage is true digital transformation, in which digital developments lead to changes in business models that allow a company to capture and create value for customers. Fewer than 10% of companies in process industries have attained the third stage, in which data and digital processes permeate a company, informing decision making, optimizing operations, automating operations, innovating business processes and implementing smart manufacturing.
In a recent global survey by the Global Center for Digital Business Transformation,
only 31% of top corporate executives polled said their organizations were actively responding to digital disruption, even though half said it was affecting their industries and a third said it was transforming their industries, However, that response is up sharply from fewer than 1% in 2015. Clearly, the importance of digital transformation is getting the attention of top corporate management.
Digital transformation generates revenue and profit not only through immense new efficiencies but, most importantly, by helping a company better respond to customers’ demands and needs, not just today but as customers themselves evolve and grow.
Technologies such as the Internet of Things, artificial intelligence, virtual and augmented reality and blockchain are becoming familiar to many people through consumer goods. But they hold even greater promise for industry, where they will allow companies to do more, with greater safety and efficiency and less energy and environmental impact. The Fourth Industrial Revolution is under way.
Digital transformation is a huge challenge. Most companies are in the first stage, digitization, adopting digital technologies to drive automation; or in the second stage, digitalization—using digital data to improve or simplify operations and generating new revenue through business models that put digital information at the core. The third stage is true digital transformation, in which digital developments lead to changes in business models that allow a company to capture and create value for customers. Fewer than 10% of companies in process industries have attained the third stage, in which data and digital processes permeate a company, informing decision making, optimizing operations, automating operations, innovating business processes and implementing smart manufacturing.
In a recent global survey by the Global Center for Digital Business Transformation,
only 31% of top corporate executives polled said their organizations were actively responding to digital disruption, even though half said it was affecting their industries and a third said it was transforming their industries, However, that response is up sharply from fewer than 1% in 2015. Clearly, the importance of digital transformation is getting the attention of top corporate management.
Digital transformation generates revenue and profit not only through immense new efficiencies but, most importantly, by helping a company better respond to customers’ demands and needs, not just today but as customers themselves evolve and grow.
Digital transformation depends on each company’s starting point. But regardless of how far a company has already progressed, four overarching themes are clear: the augmented operator; digitization, digitalization and platforms; new collaboration
and innovation models;
and lifecycle services.
Within those themes are rosters
of technologies. This report will examine five in detail: the Industrial Internet of Things, artificial intelligence, digital twins, augmented and virtual reality and blockchain.
The technologies are at different stages of development and adoption and even are starting to be used
to complement each other.
What you know you can control for; risk comes from a lack of information. The Industrial Internet of Things (IIoT) allows industry to gather various types of information about field
and operations and to analyze it.
The IIoT embeds technology, such
as sensors, in objects, systems, equipment and applications to allow those things to communicate
with each other, with people or with other systems.
The IIoT can improve productivity, avoid costly shutdowns and enhance worker safety. IIoT dashboards give executives visibility to the factory floor. The IIoT also gathers data
for performance metrics that can cross organizational performance
and escape siloed decision-making. Long-term trends of those performance metrics, combined
with artificial intelligence, can warn when equipment needs maintenance—before damage occurs. The IIoT eliminates guesswork from business.
Making sense of all the data from IIoT sensors requires serious computing power and specially designed algorithms that can spot patterns
and thus make predictions and,
based on those, make decisions about what to do next, without human intervention — artificial intelligence (AI).
AI not only is important for using
the IIoT to its fullest, but is crucial
for deployment of other technologies such as robotics, autonomous vehicles, computer vision
and virtual agents.
Compound annual growth
for the global market for AI is forecast at over 35% between 2015 and 2022, according to Orbis Research,
with the fastest growth in Asia Pacific. AI adoption is being driven by sectors with many digital natives, while industrial companies have been slower to adopt it, largely because
of a talent shortage. It’s why some companies are turning to partners to bridge the AI knowledge gap.
Making sense of all the data from IIoT sensors requires serious computing power and specially designed algorithms that can spot patterns
and thus make predictions and,
based on those, make decisions about what to do next, without human intervention — artificial intelligence (AI).
AI not only is important for using
the IIoT to its fullest, but is crucial
for deployment of other technologies such as robotics, autonomous vehicles, computer vision
and virtual agents.
Compound annual growth
for the global market for AI is forecast at over 35% between 2015 and 2022, according to Orbis Research,
with the fastest growth in Asia Pacific. AI adoption is being driven by sectors with many digital natives, while industrial companies have been slower to adopt it, largely because
of a talent shortage. It’s why some companies are turning to partners to bridge the AI knowledge gap.
One form of AI, machine learning, is helping to bridge the talent gap. Many companies are facing a shortage
of engineers at production sites who are experienced enough to detect anomalies just by noticing unusual noises, vibrations or deformations
in equipment. The myriad inputs, collected by engineers’ senses, are analyzed through the prism of their years of experience. In the absence
of enough skilled engineers,
sensors can collect many measurements—more numerous
and accurate than humans can do—which are transmitted
to a machine-learning program
that analyzes them to calculate
an anomaly score. Like a human,
the machine gets better at the job over time.
In pumps and pipes, the formation
of bubbles, called cavitation, can reduce efficiency at the least and cause failure at the worst. Traditionally, cavitation would be detected only when nearby workers noticed noise or vibration from bubbles popping. Instead, sensors and actuators measure and collect data that then goes into an AI cavitation machine-learning model
to accurately predict when cavitation is starting. This allows pumps
to operate at maximum efficiency, because flows can be adjusted in real time to avoid cavitation or stop it before it can do damage.
Another application for AI is robotics. Collaborative robots use AI
and machine learning in order
to work with unpredictable situations—like alongside humans—or to be reprogrammed
for new tasks. Industrial robot sales rose 31% to 387,000 in 2017 from
a year earlier, with more than three million industrial robots forecast
in factories by 2020, according
to the International Federation
of Robots. The market for AI robots is expected to grow to US$12.36 billion by 2023, from US$3.49 billion
this year, according to Research
and Markets.
The beauty of pairing AI with industrial automation is that it produces synergies far beyond what either can do alone, and, thanks
to machine learning, keeps improving.
The IIoT provides the data needed
to know how, for example, machinery actually is working. AI analyzes
the data to forecast preventive maintenance, optimize operations
or run models. The virtual image
of the physical asset—whether
a product, a machine or an entire facility—can be maintained throughout the asset’s life cycle
and can be accessed easily from multiple places at any time.
For example, high-fidelity,
molecular-enabled digital twins
of refinery and petrochemical plants in the cloud use data from control systems, historians and labs
for constant monitoring and analysis.
Forrester predicts the digital twin will lie at the heart of digitized industrial processes. The fastest growth is likely to be in Asia-Pacific, where IIoT sensors are being deployed at a rapid pace, connected to the cloud, MarketsandMarkets forecasts.
The IIoT provides the data needed
to know how, for example, machinery actually is working. AI analyzes
the data to forecast preventive maintenance, optimize operations
or run models. The virtual image
of the physical asset—whether
a product, a machine or an entire facility—can be maintained throughout the asset’s life cycle
and can be accessed easily from multiple places at any time.
For example, high-fidelity,
molecular-enabled digital twins
of refinery and petrochemical plants in the cloud use data from control systems, historians and labs
for constant monitoring and analysis.
Forrester predicts the digital twin will lie at the heart of digitized industrial processes. The fastest growth is likely to be in Asia-Pacific, where IIoT sensors are being deployed at a rapid pace, connected to the cloud, MarketsandMarkets forecasts.
For example, a mobile tablet with
a distributed control system can recognize instruments that need field work, provide current process values and pull up information about
the instrument, such as instruction manuals and maintenance records,
so the engineer doesn’t have to go back to the office to look it up.
Suchan AR tool can cut the time
to calibrate multiple instruments
by up to 47%.
Another example would help remedy the engineer shortage by creating
a cloud-based platform that would allow young engineers in the field
to show more experienced engineers in a control room the situation
on the ground in order to share information and transfer advice about what to do. Although humans gather
information from all five senses, visual information makes up about 80%
of perception. Rather than rely on novice engineers to try to put into words what is happening, they can instead both speak and show images of the field situation via a video call t
o experienced engineers.
Distributed ledger technology,
or blockchain, is best known
as the foundation for Bitcoin
and other cryptocurrencies. However, blockchain’s applications are expected to touch any domain where trust, verification and security are important. With blockchain, all the parties have a copy of every transaction, and the transactions can’t be altered. They can, however, be searched, making them easy
for members to see. The system engenders trust and is hard to attack. Blockchain is likely to bring down costs by eliminating the need
for middlemen, while also
enhancing cybersecurity.
Supply chains, for example, are global and often opaque, yet companies are under pressure from the public
and from governments to verify every link. Issues include product safety, environmental impact, counterfeiting and conditions of suppliers’ employees. Despite the best efforts
of companies to conduct due diligence, suppliers sometimes lie. Blockchain offers a means
of irrefutable
authentication—a potential boon
for supply-chain transparency.
Blockchain also can tell managers where spare parts are, or can track raw materials all the way back
to their origin.
Distributed ledger technology,
or blockchain, is best known
as the foundation for Bitcoin
and other cryptocurrencies. However, blockchain’s applications are expected to touch any domain where trust, verification and security are important. With blockchain, all the parties have a copy of every transaction, and the transactions can’t be altered. They can, however, be searched, making them easy
for members to see. The system engenders trust and is hard to attack. Blockchain is likely to bring down costs by eliminating the need
for middlemen, while also
enhancing cybersecurity.
Supply chains, for example, are global and often opaque, yet companies are under pressure from the public
and from governments to verify every link. Issues include product safety, environmental impact, counterfeiting and conditions of suppliers’ employees. Despite the best efforts
of companies to conduct due diligence, suppliers sometimes lie. Blockchain offers a means
of irrefutable
authentication—a potential boon
for supply-chain transparency.
Blockchain also can tell managers where spare parts are, or can track raw materials all the way back
to their origin.
In this whitepaper:
Creating Value Through Digital Transformation
Yokogawa’s Value Proposition
Four Emerging Themes Driving
The Future of Automation
Industrial Operations Get Smart
Artificial Intelligence Delivers Insights
Seeing Double, Virtually
The New Reality Bridges Gaps
Links Within and Between Industries
Co-creating Value with Customers
Works Cited
