Previewing “The Future Is Smart”: Siemens Leads Way In IoT Transformation

Huzzah!

On August 7th, HarperCollins’ new Leadership imprint (formerly Amacom) will publish The Future Is Smart, my guide to IoT strategy for businesses and the general public.  BTW: write me if you’d like to arrange a speaking engagement/book signing event!

As part of the build-up to the release, here’s another excerpt from the book, drawn from Chapter 5: “Siemens and GE:Old War Horses Leading the IoT Revolution.” It zeroes in on these two industrial companies from the 19th (!!) century that are arguably among the top IoT companies in the world (although, sadly, GE’s transformation, which I’ll detail in the next excerpt, has not resulted — so far — in a return to its former profitability). I highlighted these two companies in part to give comfort to old-line manufacturers that have been reluctant to embrace the IoT, and in part to shame them: if they can do it, why can’t you?

Siemens is a particularly exciting example, applying IoT thinking and technology to gain a competitive edge in the railroad business, which it has been involved in since the 19th century, and because its Amberg “Factory of the Future” is the epitome of the benefits of applying the IoT to manufacturing,  The excerpt is long, but I think the details on Siemens’ IoT transformation will make it worthwhile reading.

 


For all their (referring to Siemens and GE) own distinctive products and services, there are startling parallels between the two that are relevant to this book, particularly for readers whose companies have been unaware of the IoT or are modestly testing the waters. Both Siemens and GE have fully committed to the IoT and are radically reinventing themselves, their products, and their services. 

At the same time, they are not abandoning the physical for the digital: they still make products such as trains (NB: since this book went to press, GE announced it will quit to locomotive business as it struggles to regain momentum) and large medical diagnostic devices that remain necessary in the new economy, and those devices (as well as the new software lines) are used by many other companies in their own manufacturing. Both companies aren’t just testing the IoT: they are on the bleeding edge of innovation in terms of both IoT technology and services.

Siemens and GE embody most of the marks of the IoT company outlined in the first chapter:

  • Unprecedented assembly-line precision and product quality
  • Drastically lower maintenance costs and product failure
  • Increased customer delight and loyalty
  • Improved decision-making
  • Creating new business models and revenue streams

And, while they haven’t formally addressed the sixth IoT hallmark, the circular management organization, both companies exhibit management characteristics consistent with it.

Bottom-line: if these two relics of the early Industrial Age can make the IoT transformation, why can’t you?

(Siemens’) innovations in industrial automation are now associated with the concept of the digital factory. “Siemens set the course for the digital automation of entire production facilities as far back as 1996, when the launch of its Totally Integrated Automation (TIA) Portal enabled companies to coordinate elements of their production operations and to closely intermesh hardware with software.”

Siemens has benefited in recent years from the German government’s formal strategy for what it calls “Industrie 4.0,” to merge physical products with digital controls and communications. The initiative is supported by funding from the German Federal Ministry of Education and Research and the German Federal Ministry of Economic Affairs and Energy and emphasizes the merger of the digital and physical in manufacturing through cyber-physical control systems. Because the U.S. federal government doesn’t weigh in on specific economic plans to the same extent, the concept is more advanced in Europe, and the term has gathered cachet, especially as specific examples have proved profitable.

Factory of the Future:
The shining example of Industrie 4.0 is the previously mentioned Siemens plant in Amberg. It has increasingly computerized over the past 25 twenty-five years, and now is a laboratory for fusion of the physical and digital.

The plant’s 99.99885 percent quality rate would be astounding by any measure, but is even more incredible when you realize that it does not do daily repetitions of the same mass-production product run. Instead, Amberg is where the company makes the Simatic programmable logic controls (PLCs) .. that are the heart of its industrial output and which are used worldwide to allow Machine-to-Machine (M2M) automated assembly line self-regulation. They are made in more than a thousand variations for 60,000 customers worldwide, requiring frequent readjustments of the production line. In one of the ultimate examples of eating your own dog food, a thousand Simatic units are used to control the assembly line. Total output at the factory is 12 million yearly, or approximately one per second.

One downside of the Amberg system’s efficiency is that automation has nearly eliminated assembly line jobs: the only time humans touch one of the products is to put the initial circuit board on the assembly line. The 1,100-person workforce deals almost entirely with computer issues and overall supervision of the assembly line. Nevertheless, Siemens doesn’t visualize a totally automated, workerless factory in the future:

“We’re not planning to create a workerless factory,” says [Plant Manager Professor Karl-Heinz] Büttner. After all, the machines themselves might be efficient, but they don’t come up with ideas for improving the system. Büttner adds that the employees’ suggested improvements account for 40 percent of annual productivity increases. The remaining 60 percent is a result of infrastructure investments, such as the purchase of new assembly lines and the innovative improvement of logistics equipment. The basic idea here, says Büttner, is that “employees are much better than management at determining what works or doesn’t work in daily operation and how processes can be optimized.” In 2013 the [plant] adopted 13,000 of these ideas and rewarded employees with payments totaling around €1 million.

As Siemens develops new IIoT software, it is deployed at the Amberg factory to control the Simatic control units, which generate more than 50 million data points daily for analysis. Among other programs, the factory runs the NX and Teamcenter project lifecycle management software, allowing the staff to share realtime insights on the assembly line and fine-tune its operation.

Siemens’s strategy of merging the physical and digital has meant that its software offerings constantly expand, and they facilitate the kind of real and virtual collaborative workstyles that will be discussed at length in Chapter 8. Among others, they include offerings that specifically address key aspects of the IoT:

  • Product Lifecycle Management software programs, which let engineers both model new products and extensively test them virtually, without having to build and test physical models. This both cuts costs and allows more experimentation with “what if” variations on a design, because the risk of creating alternatives is so low. As we will see later, products designed with PLM can reach the market 50 percent faster. One particularly interesting part of the PLM offerings is one specifically for additive manufacturing (i.e., 3-D printing), to capitalize on this emerging option. Siemens has brought all of these programs together under the Teamcenter label, emphasizing that it provides an “open framework for interoperability,” a critical example of the “share the data” Essential Truth discussed in Chapter 2, allowing anyone who needs it companywide to access critical realtime data.
  • Digital Twins used in coordination with PLM, discussed earlier (Chapter 4) as the highest manifestation of the digital/physical synthesis, allow rigorous testing of products before they are launched.
  • Perhaps the most important of these software offerings for full realization of the Industrie 4.0 vision is the new combination of Siemens XHQ Operations Intelligence Software with the open-systems Siemens MindSphere cloud that adds advanced analytics and machine learning. Also, because it is cloud-based, the XHQ data can be ported to other cloud-based applications. If your company is considering an IoT initiative, the cloud-based alternative not only can save money compared to self-storage, but also opens the opportunity for using cloud-based Software as a Service (SaaS).

 

Railigent

Fittingly, some of the most dramatic examples of Siemens’s IoT thinking in action have centered on one of its oldest lines of business: those electric trains invented in the nineteenth century.  The company’s Railigent system (which connects to its IoT Mindsphere platform) can:

  • cut rail systems’ operating costs by up to 10%
  • deliver eye-popping on-time performance (only 1 of 2,300 trains was late!)
  • and assure 99% availability through predictive maintenance.

Its new Mobility Services have taken over maintenance for more than fifty rail and transit programs.

Again, the company’s years of experience building and operating trains pays off in the cyberworld. Dr. Sebastian Schoning, ceo of Siemens’s client Gehring Technologies, which manufactures precision honing tools, told me that it was easier to sell Siemens’s digital services to his own client base because so much of the products they already own include Siemens devices, giving his customers confidence in the new offerings.

The key to Siemens’s Mobility Services is Sinalytics, its platform architecture for data analysis not just for rail, but also for industries ranging from medical equipment to windfarms. More than 300,000 devices currently feed realtime data to the platform. Sinalytics capitalizes on the data for multiple uses, including connectivity, data integration, analytics, and the all-important cyber security. They call the result not Big Data, but Smart Data. The platform also allows merging the data with data from sources such as weather forecasts which, in combination, can let clients optimize operating efficiency on a real-time M2M basis.

Elements of an IoT system on the trains that can be adapted to other physical products include:

  • Sensing. There are sensors on the engines and gearboxes. Vibration sensors on microphones measure noises from bearings in commuter trains. They can even measure how engine oil is aging, so it can be changed when really needed, rather than on an arbitrary schedule, a key predictive maintenance advantage.
  • Algorithms: These make sense of the data and act on it. They read out patterns, record deviations, and compare them with train control systems or with vehicles of the same type.
  • Predictive Maintenance: This replaces scheduled maintenance, dramatically reducing downtime and catastrophic failure. For example: “There’s a warning in one of the windows (of the control center display): engine temperature unusual. ‘We need to analyze the situation in greater depth to know what to do next—we call it root cause analysis,’ (says) Vice-President for Customer Support Herbert Padinger. ‘We look at its history and draw on comparative data from the fleet as a whole.’ Clicking on the message opens a chart showing changes in temperature during the past three months. The increased heat is gradually traced to a signal assembly. The Siemens experts talk with the customer to establish how urgent the need for action is, and then take the most appropriate steps.”8 Padinger says that temperature and vibration analyses from the critical gearboxes gives Siemens at least three days advance notice of a breakdown—plenty of time for maintenance or replacement. Predictive maintenance is now the norm for 70 to 80 percent of Siemens’s repairs.
  • Security: This is especially important given all of the miles of track and large crowds on station platforms. It includes video-based train dispatch and platform surveillance using Siemens’s SITRAIL D system, as well as cameras in the trains. The protections have to run the gamut from physical attacks to cyber-attacks. For security, the data is shared by digital radio, not networks that are also shared by consumers.

When operations of physical objects are digitized, it allows seamlessly integrating emerging digital technologies into the services—making these huge engines showcases for the newest technologies. For example, Siemens Digital Services also included augmented reality (so repair personnel can see manuals on heads-up displays), social collaboration platforms, and—perhaps most important—3-D printing-based additive manufacturing, so that replacement parts can be delivered with unprecedented speed. 3-D printing also allows a dramatic reduction in parts inventories, It allows for replacement of parts that may no longer be available through conventional parts depots. It may even improve on the original part’s function and durability, based on practical experience gained from observing the parts in use. For example, it’s often possible with 3-D printed replacement parts to consolidate three or four separate components into a single one, strengthening and simplifying it. Siemens has used 3-D printing for the past last three years, and it lets them assure customers that they will have replacement parts for the locomotive’s entire lifespan, which can exceed thirty years.

The new Mobility Services approach’s results are dramatic:

  • None of the Velaro trains that Siemens maintains for several operators have broken down since implementing Sinalytics. Among those in Spain only one has left more than fifteen minutes behind time in 2,300 trips: a 0.0004 percent lateness rate.
  • Reliability for London’s West Coast Mainline is 99.7 percent.
  • Perhaps most impressive because of the extreme cold conditions it must endure, the reliability rate for the Velaro service in Russia is 99.9 percent.11

Siemens’s ultimate goal is higher: what the company calls (pardon the pun) 100 percent Railability.

When it does reach those previously inconceivable quality benchmarks, Siemens predicts that, as the software and sensors evolve, the next stage will be new business models in which billing will be determined by guaranteeing customers availability and performance. The manufacturing industry is now at the stage where the automation of complete workflows is the only way to ensure a long-term, defendable, competitive position.

Siemens emphasizes that it’s not enough to simply digitize the design process. Everything from design through supply chain, manufacturing, distribution, and service must be linked in a continuous digital web, with “complete digital representation of the entire physical value chain is the ultimate goal.”

 

The fact that Siemens doesn’t just sell these IoT services but makes their own manufacturing the laboratory to develop and test them is an incredible testimonial to the IoT’s transformative potential in every aspect of companies’ operations. So, as I asked above, why are you holding back? Like to think that The Future Is Smart will give you the manual you need to make the transition (why wait for August  7, when you can preorder today?).

I have seen the future, and it’s written in Chalk (PTC’s Vuforia Chalk, that is!)

I just had to take time out from my live blogging of PTC’s LiveWorx ’18 to focus on one of the topics Jim Heppelmann mentioned in passing in his keynote: the new variation on the company’s Vuforia AR app: Chalk.

Significant in its own right, I suspect Chalk will have an additional, critical impact: democratizing AR.

It is an app aimed at, and accessible to, both corporate audiences AND the general public.  Downloadable for both iPhone & iPads & Android devices, I suspect that it will quickly become popular both to support remote repair staff for companies and just plain folks who are trying, for example to help a family member far away to deal with a car or plumbing repair. Not to mention the fact (mandatory disclaimer: while I work part-time for Apple, I’m not privy to any corporate internal strategy) that the spiffy new $329 6th-generation iPad really facilitates AR, and Chalk was developed in conjunction with the Apple ARKit technology so it should really become popular.

Chalk has two components:

  • real-time video and voice sharing of the same view
  • Chalk Marks, simple handswipes that allow one of the participants to highlight the part that is the subject of the question.  The “Marks” appear to be anchored to the subjects they’re “drawn” on.

Real-world uses vary from a remote super-expert helping a field technician to identify and deal with a rare problem to your millennial helping Mom master her personal technology. I saw an amazing demo this morning with one mechanic in Germany (ok, he was actually 2′ away…) directing the mechanic working on a Mercedes how to add coolant.  As the press release announcing the app said:

“Today, remote assistance can be frustrating and cumbersome. People struggle for words to describe things that are unfamiliar, whether it be a new appliance or the back of a cable box. And when the problem can’t be described clearly, it becomes almost impossible for someone else to solve. Vuforia Chalk provides a simple and intuitive solution where people can now use Chalk Marks to get a common understanding of a problem, and the steps required to solve it.”

I’ve written before that I suspected many companies got into e-commerce in the 9o’s because a CEO’s kids got him to order a book from Amazon during the holidays & he came back raving about this new device.  I can’t help thinking that this will be just the kind of low-cost (heck, in this case, no-cost) introduction to AR And the IoT that will break down some companies’ skepticism, pay off with immediate bottom line benefits in cost savings and efficiency in service operations, and get them interested in most expensive AR such as PTC’s digital twins and predictive maintenance.  Or, as ABI analyst Eric Abbruzzes said:

“Mainstream augmented reality is at the beginning of a strong positive inflection point, and Vuforia Chalk is a great example of how AR can transition from enterprise-only to use in everyday life,” said Eric Abbruzzese, ABI Research. “We see Vuforia Chalk as a fundamentally disruptive form of remote communication that will be well received across multiple sectors and for multiple use cases.”

Now to get my granddaughter to download the app so we can collaborate on the 3D-printer that I got her for her 12th- birthday!

ThingWorx Analytics Video: microcosm of why IoT is so transformative!

I’ll speak at PTC’s LiveWorx lollapalooza later this month (ooh: act quickly and I can get you a $300 registration discount: use code EDUCATE300) on my IoT-based Circular Company meme, so I’ve been devouring everything I can about ThingWorx to prepare.

Came across a nifty 6:09 vid about one component of ThingWorx, its Analytics feature. It seems to me this video sez it all about both how you can both launch an incremental IoT strategy (a recent focus of mine, given my webinar with Mendix) that will begin to pay immediate benefits and can serve as the basis for more ambitious transformation later, especially because you’ll already have the analytical tools such as ThingWorx Analytics already installed.

What caught my eye was that Flowserve, the pump giant involved in this case, could retrofit existing pumps with retrofit sensors from National Instruments — crucial for two reasons:

  • you may have major investments in existing, durable machinery: hard to justify scrapping it just to take advantage of the IoT
  • relatively few high-end, high-cost machinery and devices have been redesigned from the ground up to incorporate IoT monitoring and operations.

Note the screen grab: each of these sensors takes 30,000 readings per second. How’s that for real-time data?  PTC refers to this as part of the “volume, velocity and variety challenge of data” with the IoT.

As a microcosm of the IoT’s benefits, this example shows how easy it is to use those massive amounts of data and how they can be used to improve understanding and performance.

There are three major components:

  • ThingWatcher:
    This is the most critical component, because it sifts through the incredible amount of data from the edge, learns what constitutes normal performance for that sensor (creating “pop-up learning flags”), and then monitors it future performance for anomalies and, as the sample video shows, delivers real-time alerts to users (without requiring human monitoring) so they can make adjustments and/or order repairs.  Finds anomalies from edge devices in real-time. Automatically observes and learns the normal state pattern for every device or sensor. It then monitors each for anomalies and delivers re- al-time alerts to end users.
  • ThingPredictor:
    For the all-important new function of predictive maintenance, two different types of ThingPredictor indicators pop up when if anomalies are detected, predicting how long it may be until failure, allowing plenty of time for less-costly, anticipatory repairs. Because the specific deviation is identified in advance, repair crews will have the needed part with them when needed, rather than having to make an additional trip back to pick up parts.

    If you ask for a standard predictive scoring you don’t specify which performance features to include and get a simple predictive score. However, you can specify several key features to evaluate and get a more detailed (and probably more helpful) answer. For example,  “if you indicate an important feature count of three, the causal scoring output will include the three most influential features for each record and the percentage weights of each feature’s influence on the score.”

  • ThingOptimizer:
    Finally, you can use “ThingOptimizer” to do some what-if calculations to decide which possible “levers,” as ThingWorx calls the key variables, could change the projections to either maximize a positive factor or minimize the negatives. “Prescriptive scoring results include both an original score (the score before any lever attributes are changed) and an optimized score (the score after optimal values are applied to the lever attributes). In addition, for each attribute identified in your data as a lever, original and optimal values are included in the prescriptive scoring results.” It sort of reminds me how the introduction of VisiCalc allowed users, for the first time, to play around with variables to see which would have the best results.
Best of all, as the video illustrates, ThingWorx Analytics would facilitate the kind of “Circular Company” I’ll address in my speech, because the exact same real-time data could simultaneously be used by operating personnel to fine tune operations and catch a problem in time for predictive maintenance, and by senior management to get an instant overview of how operations are going at all the installations. Same data, many uses.
Bottom line: a robust IoT platform could be the key to an incremental strategy to begin by improving daily operations and reducing maintenance problems, and also be the underpinning for more radical transformation as your IoT strategy becomes more advanced!  See you at LiveWorx!

Game-changer! AR Enables IoT merging of physical and digital

Several months ago I wrote about an analogy to the world of business prior to the Internet of Things,  in which a metaphorical illness called “Collective Blindness” affected every human for all time, so that we were unable to peer inside things. We just accepted that as an inevitable limitation, creating all sorts of work-arounds to try to be able to cope in the absence of real-time information about things of all sorts.

I then said that the Internet of Things would allow us to end Collective Blindness, getting — and sharing — the real-time data we’d need to make better decisions and work more precisely.

Now I’ve seen the tool that allows us to end that Collective Blindness: PTC’s Augmented Reality (AR), tool, Vuforia.

At last week’s PTC Liveworx conference, there was a mind-blowing demo of Vuforia by Terri Lewis, director of solutions and tech at Caterpillar, as it applied to the company’s XQ Gen Set, a portable power generator for job sites and special events.  As PTC CEO James Heppelmann reiterated several times, the software is creating

a single new reality that’s physical and digital at the same time….. and democratizing AR.”
(my emphasis)

Used as a sales tool, Vuforia Studio Enterprise lets the customer look inside the product, as contrasted with a static brochure.  That’s neat, but what’s really incredible is how it lets maintenance people peer inside the device, and do so in a way (as Heppelmann said, “humans prefer to use sight an sound simultaneously”) that is much more effective in terms of zeroing in not only on what’s wrong, but also these specifics (such as replacement part numbers, etc.) to quickly repair them.  Incidentally Heppelmann and Harvard Prof. and biz guru Michael Porter are collaborating on another article, this one on how to apply AR in a business setting (turns out that Porter is a member of the PTC board, and in the past few years he’s been using it as a lab to evaluate business use of the IoT).

Another example of Vuforia’s work in maintenance demonstrated at the conference was by Flowserve, the world’s largest flow control company. Vuforia helps them manage devices in real-time (the person at the pump can see what is actually happening), cutting the number of repair trips from three to one, because they are able to diagnose the problem at the beginning, and bring the replacement parts with them. Then they can do do real-time simulations to see if the problem has been solved. The company believes they saved $2 billion in excess repart costs in 2015 alone.

 Vuforia Studio AR lets users set up augmented reality simulations in minutes without writing code, and can also be used in product design review.

I had a chance to try the XQ Gen Set visualization with an AR headset myself, and it was as powerful as promised.

I must admit the first time I tried on an AR headset — and almost jumped on one of the other users because I was jumping back to avoid falling several hundred feet off a sharp cliff into the ocean — I was amazed by the realism, but didn’t really think much about its serious business uses.  PTC’s Vuforia Studio AR made me a believer: it’s helping us cure Collective Blindness, and AR will be yet another tool to bring about unprecedented precision and efficiency in every aspect of manufacturing and product maintenance!

Failure to inspect oil rigs another argument for “real-time regulation”

The news that the Bureau of Land Management has failed to inspect thousands of fracking and other oil wells considered at high risk for contaminating water is Exhibit A for my argument we need Intnet of Things-based “real-time regulation” for a variety of risky regulated businesses.

According to a new GAO report obtained by AP:

“Investigators said weak control by the Interior Department’s Bureau of Land Management resulted from policies based on outdated science and from incomplete monitoring data….

“The audit also said the BLM did not coordinate effectively with state regulators in New Mexico, North Dakota, Oklahoma and Utah.”

Let’s face it: a regulatory scheme based on after-the-fact self-reporting by the companies themselves backed up by infrequent site visits by an inadequate number of inspectors will never adequately protect the public and the environment.  In this case, the GAO said that “…. the BLM had failed to conduct inspections on more than 2,100 of the 3,702 wells that it had specified as ‘high priority’ and drilled from 2009 through 2012. The agency considers a well ‘high priority’ based on a greater need to protect against possible water contamination and other environmental safety issues.”

By contrast, requiring that oil rigs and a range of other technology-based products, from jet engines to oil pipelines, have sensors attached (or, over time, built in) that would send real-time data to the companies should allow them to spot incipient problems at their earliest stages, in time to schedule early maintenance that would both reduce maintenance costs and reduce or even eliminate catastrophic failures. As I said before, this should be a win-win solution.

If problems still persisted after the companies had access to this real-time data, then more draconian steps could be required, such as also giving state and federal regulators real-time access to the same data — something that would be easy to do with IoT-based systems. There would have to be tight restrictions on access to the data that would protect proprietary corporate information, but companies that are chronic offenders would forfeit some of those protections to protect the public interest.

 

Automated factories: that’s not the IoT’s potential!

It’s easy to see why some people make the assumption that one of the results of the Internet of Things will be fully-automated factories.

After all, if automatic, real-time machine-2-machine data sharing would allow self-starting and self-regulating machinery, wouldn’t that allow us a utopian vision of completely autonomous manufacturing?

Instead, I think Bosch’s Volkmar Denner nailed it with this blog entry. He says that rather than complete automation:

“Instead, it’s about finding ways to increase agility. Putting that into figures, optimizing resource allocation within a more flexible production process can result in a jump in productivity of as much as 30 percent. Our goal is to be able to customize even the smallest unit volumes while retaining optimum productivity, and ultimately leading to achieve optimized multi-variant series production.”

I agree totally that what’s going to happen is an end to centralized management and top-down control of information (see my last post, on “Buckyball Management”!, with decentralized, self-management emerging that could threaten old industry leaders who don’t get it (see my posts about how GE does get it!) :

“… And I’m convinced that this shift will provide opportunities for established companies to offer new business models. But they too need to watch out: the IoTS is shaking up what until now has been very much a closed market, opening it up for entirely new players such as IT companies. Here, the IoTS is not just about connecting objects, machines, and systems. On the contrary, it’s also about how to use the data that this connectivity generates. And instead of using this information only within the plant itself, now everyone along the manufacturing chain can be given access to the data over the internet. Once again, the knowledge gained from these data can be applied to generate new business models.”

Denner says that one of the #IoT services that Bosch — the leading supplier of automotive sensors and one of the leaders in industrial sensors — is developing is predictive maintenance, which innovators such as GE (with its jet turbines) and the railroads (I’ve never traced my ancestry on my father’s side, but I harbor the possibility that I’m descended from the Stephensons, pere et fils, who invented the locomotive, so I have a warm spot in my heart for that industry…) are already doing.  As Denner says, “Having such a solution in place allows organizations to offer their customers new and improved levels of service, including a guarantee of reduced downtimes.”

So don’t count out the human element in manufacturing once the IoT is commonplace: in fact, it will be more important, and more valuable, than ever!

http://www.stephensonstrategies.com/">Stephenson blogs on Internet of Things Internet of Things strategy, breakthroughs and management