by Gary Mintchell | Jan 7, 2020 | Operations Management
I give up. To me, the end of the decade is next year figuring there was not a year 0, then the beginning of the new calendar was year 1 and the end of the first decade was year 10. Oh, well, mainstream media just can’t wait to jump into wrap-up frenzy. So, me, too.
The last 10 years in industrial technology was busy with new buzz words—heavier on marketing than on substance in many ways. We breezed through Industrie 4.0 with its cyber-physical systems. Then we had Internet of Things borrowed from the consumer, largely iPhone, space. But borrowing from GE advertising of the “Industrial Internet”, the “Industrial Internet of Things” became originally the European counterpoint to Germany’s Industry 4.0 and then grew into general adoption.
Not finished with all this buzz, the industry discovered “digital”. We had digital twin (derived from cyber-physical systems). But these had to be connected with the digital thread. And all led into a digital transformation.
Let’s take a look at some specific topics.
Innovation
Much of the foundation was laid in the decade before. Maybe I should say decades. The industry started digitizing in the 1980s. It’s been building ever since. Through the first decade of this millennium great strides were made in control technology, usability, sensors (both sensitivity and communication), networks moving from analog to digital and through field buses to Ethernet.
In this decade, most companies grew by acquisition of smaller, innovative companies and start-ups. The remaining automation giants pieced together strategies based on visions of which companies to acquire and what customer solutions were required. Looking ahead, I’m considering what additional consolidation to anticipate. I think there will be more as the market does not seem to be growing dramatically.
Most innovation came in the realm of data. Decreasing costs of memory, networking stacks, and other silicon enabled leaps in ability to accumulate and communicate data. Borrowing software advances from IT, historians and relational databases grew more powerful along with new types of data handling and analysis coming from the “big data” and powerful analytics technologies.
Another IT innovation that finally hit industrial companies was adoption of “cloud” with the eventual development of edge. Instead of the Purdue Enterprise Reference Model of the control/automation equipment being the gateway of all data from the processes, companies began to go sensor to cloud, so to speak, breaking down the rigidity of PERA thinking.
Digital Everything
It is now old news that digital is everywhere. And, it is not a sudden development. It has been building for 30 years. Like all technology, it builds over time until it’s suddenly everywhere. The question is no longer what is becoming digital, nor is it speculating over marketing terms like digital transformation.
The question about digital everything is precisely how are we to use it to make things better for humans and society.
Sensors—At least by 2003, if not before, I was writing about the converging trends in silicon of smaller and less expensive networking, sensing, processing, and memory chips and stacks that would enable an explosion of ubiquitous sensing. It’s not only here; it is everywhere. Not only in manufacturing, but also in our homes and our palms.
Design—CAD, CAM, PLM have all progressed in power and usability. Most especially have been the development of data protocols that allow the digital data output of these applications to flow into operations and maintenance applications. Getting as-built and as-designed to align improves maintenance and reliability along with uptime and productivity. And not only in a single plant, but in an extended supply chain.
Networking—The emergence of fast, reliable, and standardized networking is the backbone of the new digital enterprise. It is here and proven.
Software—Emergence of more powerful databases, including even extension of historians, along with data conversion protocols and analysis tools provides information presented in an easily digestible form so that better decisions may be made throughout the extended enterprise.
IT/OT
Industry press have talked about IT/OT convergence until we are all sick of the phrase. Add to that stories of in-fighting between the organizations, and you have the making of good stories—but not of reality or providing a path to what works. As Operations Technology (OT) has become increasingly digital, it inevitably overlaps the Information Technology (IT) domain. Companies with good management have long since taken strides to foster better working relationships breaking the silos. Usually a simple step such as moving the respective manager’s offices close to each other to foster communication helps.
New Entrants
Speaking of IT and OT, the modification of the Purdue Enterprise Reference Modal to show data flowing from the plant/sensor level directly to the “cloud” for enterprise IT use has enticed new entrants into manufacturing technology.
If we are not forced to go through the control system to provide data for MES, MOM, ERP, CRS, and the like, then perhaps the IT companies such as Dell Technologies, Hewlett Packard Enterprise, and Hitachi Vantara can develop their compute platforms, partnerships, and software to provide that gateway between plant floor and enterprise without disturbing the control platform.
Therefore we are witnessing proliferating partnerships among IT and OT automation suppliers in order to provide complete solutions to customers.
Strategy
Remember—it is all meaningless unless it gets translated into intelligent action to make the manufacturing supply chain more productive with better quality and more humane.
by Gary Mintchell | May 24, 2018 | News, Technology
Living with technology a decade from now. Dell Technologies and the Institute for the Future conducted an in-depth discussion with 20 experts to explore how various social and technological drivers will influence the next decade and, specifically, how emerging technologies will recast our society and the way we conduct business by the year 2030.
There is no universally agreed upon determination of which technologies are considered emerging. For the purpose of this study, IFTF explored the impact that Robotics, Artificial Intelligence (AI) and Machine Learning, Virtual Reality (VR) and Augmented Reality (AR), and Cloud Computing, will have on society by 2030. These technologies, enabled by significant advances in software, will underpin the formation of new human-machine partnerships, according to the IFTF.
Talk of digital transformation is virtually everywhere in Information Technology circles and Operations Technology circles. My long and varied experiences have often placed me at the boundaries where the two meet—and are now increasingly overlapping.
The take on robotics is right on target. And forget about all the SciFi scare stories that mainstream media loves to promote. The future is definitely all about human-machine partnership or collaboration. For example I often talk with EMTs about life in the rescue squad. These people are always in the gym. Our population in the US has gotten so large and obese that they often have to lift 300+ lb. people who haven’t the strength to help themselves up. Think about a robot assistant helping the EMT.
The AI discussion is also fraught with prominent people like Ray Kurzweil or Elon Musk giving dystopian SciFi views of the future. We are a long way from “intelligence.” Where we are is really the use of machine learning and neural networks that help machines (and us) learn by deciphering recurring patterns.
Back to the study, the authors state, “If we start to approach the next decade as one in which partnerships between humans and machines transcend our limitations and build on our strengths, we can begin to create a more favorable future for everyone.”
Jordan Howard, Social Good Strategist and Executive Director of GenYNot, sees tremendous promise for the future of human-machine partnerships: “Many of the complex issues facing society today are rooted in waste, inefficiency, and simply not knowing stuff, like how to stop certain genes from mutating. What if we could solve these problems by pairing up more closely with machines and using the mass of data they provide to make breakthroughs at speed? As a team, we can aim higher, dream bigger, and accomplish more.”
Liam Quinn, Dell Chief Technology Officer, likens the emerging technologies of today to the roll-out of electricity 100 years ago. Quinn argues that we no longer fixate on the “mechanics” or the “wonders” of electricity, yet it underpins almost everything we do in our lives. Similarly, Quinn argues, in the 2030s, today’s emerging technologies will underpin our daily lives. As Quinn provokes, “Imagine the creativity and outlook that’s possible from the vantage point these tools will provide: In 2030, it will be less about the wonderment of the tool itself and more about what that tool can do.”
By 2030, we will no longer revere the technologies that are emerging today. They will have long disappeared into the background conditions of everyday life. If we engage in the hard work of empowering human-machine partnerships to succeed, their impact on society will enrich us all.
Robots
While offshoring manufacturing jobs to low-cost economies can save up to 65% on labor costs, replacing human workers with robots can save up to 90% of these costs.
China is currently embarking upon an effort to fill its factories with advanced manufacturing robots, as workers’ wages rise and technology allows the industry to become more efficient. The province of Guangdong, the heartland of Chinese manufacturing, has promised to invest $154 billion in installing robots.
Buoyed by their commercial success, the adoption of robots will extend beyond manufacturing plants and the workplace. Family robots, caregiving robots, and civic robots will all become commonplace as deep learning improves robots’ abilities to empathize and reason. Google recently won a patent to build worker robots with personalities.
Artificial Intelligence and Machine Learning
Approximately 1,500 companies in North America alone are doing something related to AI today, which equates to less than 1% of all medium-to-large companies. We’re seeing this in the financial services industry already, with data recognition, pattern recognition, and predictive analytics being applied to huge data sets on a broad scale. In a 2015 report, Bank of America Merrill Lynch estimated that the AI market will expand to $153 billion over the next five years—$83 billion for robots, and $70 billion for artificial intelligence-based systems.
In addition to their ability to make decisions with imperfect information, machines are now able to learn from their experiences and share that learning with other AI programs and robots. But AI progress also brings new challenges. Discussions surrounding who or what has moral and ethical responsibility for decisions made by machines will only increase in importance over the next decade.
Virtual Reality and Augmented Reality
Although both Virtual and Augmented Reality are changing the form factor of computing, there is a simple distinction between the two. VR blocks out the physical world and transports the user to a simulated world, whereas AR creates a digital layer over the physical world.
Despite the difference, both technologies represent a fundamental shift in information presentation because they allow people to engage in what Toshi Hoo, Director of IFTF’s Emerging Media Lab, calls “experiential media” as opposed to representative media. No longer depending on one or two of our senses to process data, immersive technologies like AR and VR will enable people to apply multiple senses—sight, touch, hearing, and soon, taste and smell—to experience media through embodied cognition.
Over the next decade, Hoo forecasts that VR, combined with vast sensor networks and connected technologies, will be one of many tools that enable distributed presence and embodied cognition, allowing people to experience media with all their senses.
Cloud Computing
It’s important to recognize that Cloud Computing isn’t a place, it’s a way of doing IT. Whether public, private, or hybrid (a combination of private and public), the technology is now used by 70% of U.S. organizations. This figure is expected to grow further, with 56% of businesses surveyed saying they are working on transferring more IT operations to the cloud, according to IDG Enterprise’s 2016 Cloud Computing Executive Summary.
While the cloud is not a recent technological advancement, cloud technology only really gathered momentum in recent years, as enterprise grade applications hit the market, virtualization technologies matured, and businesses became increasingly aware of its benefits in terms of efficiency and profitability. Increasing innovation in cloud-native apps and their propensity to be built and deployed in quick cadence to offer greater agility, resilience, and portability across clouds will drive further uptake. Start-ups are starting to use cloud-native approaches to disrupt traditional industries; and by 2030, cloud technologies will be so embedded, memories from the pre-cloud era will feel positively archaic by comparison.
Human Machine Partnership
Recent conversations, reports, and articles about the intersection of emerging technologies and society have tended to promote one of two extreme perspectives about the future: the anxiety-driven issue of technological unemployment or the optimistic view of tech-enabled panaceas for all social and environmental ills.
Perhaps a more useful conversation would focus on what the new relationship between technology and society could look like, and what needs to be considered to prepare accordingly.
By framing the relationship between humans and machines as a partnership, we can begin to build capacity in machines to improve their understanding of humans, and in society and organizations, so that more of us are prepared to engage meaningfully with emerging technologies.
Digital (Orchestra) Conductors
Digital natives will lead the charge. By 2030, many will be savvy digital orchestra conductors, relying on their suite of personal technologies, including voice-enabled connected devices, wearables, and implantables; to infer intent from their patterns and relationships, and activate and deactivate resources accordingly.
Yet, as is often the case with any shift in society, there is a risk that some segments of the population will get left behind. Individuals will need to strengthen their ability to team up with machines to arrange the elements of their daily lives to produce optimal outcomes. Without empowering more to hone their digital conducting skills, the benefits that will come from offloading ‘life admin’ to machine partners will be limited to the digitally literate.
Work Chasing People
Human-machine partnerships will not only help automate and coordinate lives, they will also transform how organizations find talent, manage teams, deliver products and services, and support professional development. Human-machine partnerships won’t spell the end of human jobs, but work will be vastly different.
By 2030, expectations of work will reset and the landscape for organizations will be redrawn, as the process of finding work gets flipped on its head. As an extension of what is often referred to as the ‘gig economy’ today, organizations will begin to automate how they source work and teams, breaking up work into tasks, and seeking out the best talent for a task.
Instead of expecting workers to bear the brunt of finding work, work will compete for the best resource to complete the job. Reputation engines, data visualization, and smart analytics will make individuals’ skills and competencies searchable, and organizations will pursue the best talent for discrete work tasks.
by Gary Mintchell | Apr 12, 2018 | Internet of Things, Manufacturing IT, Software
The Internet of Things ecosystem is changing computing in almost a seismic shift. But like geology, it builds up over time and then the event happens before you know it.
We had centralized, on-site computing revolutionized by PCs. We networked PCs and wound up with centralized computing in the cloud. Demands from building the Internet of Things (or Industrial Internet of Things for us manufacturing and production geeks) expose the flaws of cloud computing. The next hot thing—edge.
Yesterday the CEO/co-founder of Zededa talked with me about the computing platform his company is building with no less a mission than to build the largest computing company on Earth without owning infrastructure. Its vision—create a new edge economy that allows applications to run anywhere.
Some of what follows may sound familiar. I’ve talked with many companies doing a piece of what Zededa has laid out, but none are as audacious as this.
In brief, Zedeta…
- Closes $3.06M in Seed Funding
- Pioneering a secure, cloud-native approach to real-time edge applications at hyperscale for solutions ranging from self-driving cars to industrial robots
- Built a team comprised of distinguished engineers from top tech companies in cloud, networking and open source to solve the edge computing puzzle and disrupt the status quo
- Seed round was led by Wild West Capital; other investors include Almaz Capital, Barton Capital and Industry Veteran Ed Zander, former CEO of Motorola and former COO of Sun Microsystems
“Tomorrow’s edge computing environment that enables digital transformation will be distributed, autonomous and cooperative. The edge is complex and not only has to scale out securely, but simultaneously must become friendlier for app developers. That’s the problem we are solving at ZEDEDA,” stated ZEDEDA CEO and Co-Founder Said Ouissal. “It will require a drastic shift from today’s embedded computing mindset to a more secure-by-design, cloud-native approach that unlocks the power of millions of cloud app developers and allows them to digitize the physical world as billions of ‘things’ become smart and connected.”
ZEDEDA will use the funding for continued research and product development, investment in community open-source projects for edge computing as well as further investment in sales and marketing initiatives. ZEDEDA investors include Wild West Capital and Almaz Capital, whose funding was part of a broader group investors, some of whom also invested in IoT/edge companies Theatro and Sensity Systems (now Verizon).
In the coming wave of pervasive computing, real-time apps, cyber-physical systems and data services such as machine learning and analytics will become commonplace. ZEDEDA envisions an open ecosystem and a completely new technology stack that creates a service fabric essential to achieving the hyperscale that will be required in edge computing.
To realize that goal, ZEDEDA has pulled together a distinguished roster of industry veterans from legendary technology companies with expertise in areas of operating systems, virtualization, networking, security, blockchain, cloud and application platforms. This unique blend of skills combines with the team’s deep connections to core open-source projects and standardization bodies. The team’s work has directly contributed to software and system patents as well as industry standards used by billions of people around the world today.
“A new paradigm and massive innovation is needed to meet demand for IoT and edge computing,” said Kevin DeNuccio, Founder of Wild West Capital and ZEDEDA’s lead investor. “Massive shifts in technology, including the proliferation of IoT, paves the way for industry disruption, which large incumbents tend to inhibit. Disruption takes a combination of an entrepreneurial team with a very unique set of collective experience, groundbreaking ideas, and the ability to garner immediate traction with global industrial leaders, who can transform their business with machine learning and artificial intelligence delivered by the Edge connected IoT world. ZEDEDA is simply one of the most promising edge computing startups out there.”
“Operations Technology teams face major challenges when it comes to fully realizing the advantages of an IoT world. Their worlds are becoming massively connected systems dealing with virtualization, networking and security,” stated Christian Renaud, Research Director, IoT at 451 Research. “Our recent research shows that while OT teams have the application plans for leveraging IoT, the vast majority of organizations’ IT resources and capabilities are maxed out. This leaves open the question of how these edge applications and IoT will scale out without compromising security or taxing resources even further in the future.”
Ouissal told me, “Edge is the next big wave, bigger than cloud, simply because of the sheer size of the number of devices. The goal is ubiquitous compute where applications want to interact real-time. The problem with the cloud is that it’s centralized. This ecosystem is truly Cyberphysical—just like your Industry 4.0.”
The current IoT model of sending all data to the cloud for processing, won’t scale due to:
- Bandwidth
- Latency
- Privacy issues
Three problems that the company is attacking:
1. Moving apps now running in the cloud to the edge
2. Edge-to-edge communication, key for autonomous systems, peer-to-peer
3. Security, cloud requires cyber security, but at the edge we must add physical security—someone could walk in and carry out an intelligent device
Ouissal often mentioned the need to rethink management of the edge. There exists a big difference between managing cloud and edge. Zedeta is tacking the variety of management challenges for updating and managing thousands to millions of embedded devices.
Solutions the team are developing include:
1. Security-built on platform, use keys, trusted, health check with every plug in, embedded virtualization
2. management-virtualization->can run multiple sessions on a device, eg robot motion on one session and analytics on another all on same embedded system, can scale this to millions of devices
3. Networking-monitor, watch lists, anomaly detection, analyze why, VPN architecture
This is all fascinating. I can’t wait to talk with competitors and potential competitors in a couple of weeks in Hannover and during some upcoming trips to get responses.
by Gary Mintchell | Oct 18, 2017 | Internet of Things, Operations Management, Software
There are two types of people in industry—operations technology and information technology. God forbid if they should actually talk with each other.
Everywhere I go there is talk of overcoming the OT/IT divide. Something just crossed my email stream where there was a survey about whether the departments have merged anywhere. They were shocked, shocked I say, that only about 1 in 10 companies have merged the two departments. I think the purveyors of that survey must have been on Mars for the past bunch of years.
These people just have different jobs to do. Different things they are measured on. Different ways they contribute to the common welfare of the corporation. However, the technologies they use are overlapping at an ever greater pace.
Here is a survey that once again reveals what is seemingly a disconnect between IT and OT. But I think that interfacing to ERP systems is non-trivial. I’m actually amazed and heartened by the progress we’ve made to date.
I’d take a look at this survey and consider how far we have come—and yet, how far we still need to go.
IFS has released a primary research study on how the Internet of Things (IoT) affects readiness for digital transformation in industrial companies.
According to survey of 200 IoT decision makers at industrial companies in North America, only 16 percent of respondents consume IoT data in enterprise resource planning (ERP) software. That means 84 percent of industrial companies face a disconnect between data from connected devices and strategic decision making and operations, limiting the digital transformation potential of IoT.
The study posed questions about companies’ degree of IoT sophistication. The study also explores how well their enterprise resource planning (ERP), enterprise asset management (EAM) or field service management (FSM)software prepares them for digital transformation and to consume IoT data within enterprise software.
Respondents were divided into groups including IoT Leaders and IoT Laggards, depending on how well their enterprise software prepared them to consume IoT data—as well as Digital Transformation Leaders and Digital Transformation Laggards depending on how well their enterprise software prepared them for digital transformation.
The two Leaders groups overlapped, with 88 percent of Digital Transformation Leaders also qualifying as IoT Leaders, suggesting IoT is a technology that underpins the loose concept of digital transformation.
Digital Transformation Leaders made more complete use of IoT data than Digital Transformation Laggards; Leaders are almost three times as likely to use IoT data for corporate business intelligence or to monitor performance against service level agreements.
Digital Transformation Leaders were more likely than Digital Transformation Laggards to be able to access IoT data in applications used beyond the plant floor. They were more than four times as lilkely to have access to IoT data in enterprise asset management software, twice as likely than Digital Transformation Laggards to be able to access IoT data in high-value asset performance management software, and almost twice as likely to be able to be able to use IoT data in ERP.
The data suggests a real need for more IoT-enabled enterprise applications designed to put data from networks of connected devices into the context of the business.
In reviewing the findings, IFS Chief Technology Officer for North America, Rick Veague, commented, “Are your planning and maintenance systems robust enough to make real time decisions using IoT-sourced data? Many are facing the reality of having to answer ‘no.’ ”
“Study data suggest that the most common use case for IoT in these industrial settings is condition-based maintenance. The benefits go beyond operational improvements and maintenance cost avoidance,” said Ralph Rio, Vice President of Enterprise Software at ARC Advisory Group. “It increases uptime that provides additional capacity for increased revenue. It also avoids unplanned downtime that interrupts production schedules causing missed shipment dates and customer satisfaction issues. When married to demand and scheduling systems in ERP, IoT becomes a revenue-enhancement tool improving the top line.”
by Gary Mintchell | Aug 15, 2017 | Internet of Things
The Internet of Things technology competition remains robust. I devoted Monday to a trip to Houston to visit the campus of Hewlett-Packard Enterprise (HPE). This was the old Compaq computer campus remodeled for a new generation.
The occasion was the grand opening of the Internet of Things customer experience center. We toured several demo areas that were set up, but the capability exists for custom demos for visiting customers.
Prominent among partner companies was National Instruments, whose executive Vice President of Sales and Marketing Eric Starkloff was present to talk with customers as well as analysts and influencers. Other partners you’d recognize from our market included Schneider Electric (Foxboro), PTC (ThingWorx and Kepware), OSIsoft, and SAP.
Key points:
HPE has invested in many operations technology (OT) people. I talked with several who were quite knowledgeable about the industrial technology area.
While HPE has a typical gateway product, the featured device was the Edgeline—a powerful Xeon processor and PCI or PXI slots and mega gigs of memory. Called a “mini-data center”, it’s like having a datacenter at the Edge.
I first met Dr. Tom Bradicich [updated spelling] when he was at National Instruments evangelizing “Big Analog Data” solution—which NI still touts. He is still passionate about finding ways to use all that data generated from devices. The Edgeline is a perfect solution for him seeing that it combines the NI technology with which he’s familiar with enterprise grade architecture also with which he’s familiar.
Key takeaways:
The Edgeline takes edge computing up a notch, as Emeril would say.
HPE has made a significant investment on the OT side with several industrial technology partners.
No company can do it all alone anymore, and HPE has built a strong partner ecosystem. However, it must continue to reach out and grow it even more.
