Will some smart home device makers ever grow souls??

(Please cut me a little slack on this post, dripping with sarcasm: these latest examples of some smart home device makers’ contempt/obliviousness toward customers’ privacy and security shoved me over the edge!).

Once upon a time two smart boys in their dorm room thought up a new service that really made a new technology hum. When they turned it into a tiny company, they ever adopted a cute motto: “don’t be evil.” Neat!

Then their little service got very, very big and very, very profitable. The motto? It kinda withered away. Last year it was even dropped from the company’s code of conduct.

Which, conveniently, allowed that once tiny company to produce this abomination: the Google Nest Guard (the alarm, keypad, and motion sensor portion of Nest’s Secure home protection system) featuring a mic.

Oh, did I point out that Nest didn’t mention the mic’s presence? No, that fact only emerged when it announced the Guard’s integration with Google’s Assistant voice device (Sample command: “OK, Google, surveil my family.”) and Business Insider ferreted out the mic’s presence:

“The existence of a microphone on the Nest Guard, which is the alarm, keypad, and motion-sensor component in the Nest Secure offering, was never disclosed in any of the product material for the device.”

On Tuesday, a Google spokesperson told Business Insider the company had made an “error.”

“The on-device microphone was never intended to be a secret and should have been listed in the tech specs,” the spokesperson said. “That was an error on our part.”

Oh. All is forgiven. It was just an “error on our part.”

Except, how can I say this politely?, that’s utter baloney. It seems as if the mic just sorta got there. No engineer suggested adding it. No executives reviewing the design conveniently overlooked it.

Nope, that mic was there intentionally, and Google is so morally corrupt and/or amoral that they simply chose to ignore telling the public.

And, while we’re at it, let’s not heap all the opprobrium on Google. Amazon subsidiary Ring actually let its employees view videos shot with its doorbell device:

“These videos were unencrypted, and could be easily downloaded and shared. The team was also given a database that linked each video to the Ring customer it belonged to.”

As I’ve said many times before, my perspective on the issues of privacy and security are informed by my prior work in corporate crisis management, which taught me that far too many engineers (I have many friends in the profession, but if the shoe fits, wear it) are simply oblivious to privacy and security issues, viewing them as something to be handled through bolt-on protections after the fun part of product design is done. In fact, in adding the prior link, I came across something I wrote last year in which I quoted from the Google log — which contained nary a mention of privacy concerns — about an aspect of AI that would allow identification of what shop a batch of ramen came from. Funny, huh? No — scary.

Another lesson I drew from my past was the phenomenon of guilt by association, which is incredibly rampant right now: people conflate issues as diverse as smart home privacy violations, Russian election tampering, some men’s inability to find dates (I kid you not, and the result may be lethal for some women), the so-called “deep state,” etc., etc. The engineers I know tend to dismiss these wacky ideas because they aren’t logical. But the fact that the fears aren’t logical doesn’t mean they aren’t very, very real to those who embrace them.

That means that even those companies whose smart home devices DO contain robust privacy protections risk people rejecting their devices as well. Trust me on this one: I work every day with rational people who reject the cloud and all the services that could enrich their lives due to their fear of privacy and security violations.

That’s why responsible IoT companies must become involved in collaborations such as the Internet of Things Association, and IMC, working on collaborative strategies to deal with these issues.

Let’s not forget that these gaffes come at the same time as there’s a lot more interest among regulators and elected officials in regulating and/or even breaking up the Silicon Alley behemoths. You’d kinda think they’d be on their best behavior, not doing stupid things that just draw more criticism.

I’m fed up, and I won’t shut up. Write me if you have feasible suggestions to deal with the problem.

IMPORTANT POSTSCRIPT!

I just discovered a Verge piece from last month to the effect that Google is belatedly getting religion about personal privacy, even — and this wins big points in my book — putting its privacy policies in plain English (yes!) rather than legalese. Here’s a long piece from the article. If they follow up, I’d be the first to praise them and withdraw my criticism, although not of the industry as a whole:

“So today, as Google announced that it’s going to sell a device that’s not all that different from the Facebook Portal, whose most every review wondered whether you should really invite a Facebook camera into your home, Google also decided to publicly take ownership for privacy going forward.
As we discovered in our interview with Google Nest leader Rishi Chandra, Google has created a set of plain-English privacy commitments. And while Google didn’t actually share them during today’s Google I/O keynote, they’re now available for you to read on the web.
Here’s the high-level overview:
We’ll explain our sensors and how they work. The technical specifications for our connected home devices will list all audio, video, and environmental and activity sensors—whether enabled or not. And you can find the types of data these sensors collect and how that data is used in various features in our dedicated help center page.
We’ll explain how your video footage, audio recordings, and home environment sensor readings are used to offer helpful features and services, and our commitment for how we’ll keep this data separate from advertising and ad personalization.
We’ll explain how you can control and manage your data, such as providing you with the ability to access, review, and delete audio and video stored with your Google Account at any time.
But the full document gets way more specific than that. And remarkably, a number of the promises aren’t the typical wishy-washy legalese you might expect. Some are totally unambiguous. Some of them go against the grain, like how Nest won’t let you turn off the recording light on your camera anymore because it wants to assure you!
‘Your home is a special place. It’s where you get to decide who you invite in. It‘s the place for sharing family recipes and watching babies take first steps. You want to trust the things you bring into your home. And we’re committed to earning that trust,’ Google says.”

Maybe somebody’s listening!

Live-Blogging From #LiveWorx!

Posted on 10th June 2019 in Uncategorized

I’m back at PTC’s annual LiveWorx lollapalooza, gathering ideas for my Industry Week column, starting with a presentation by Dell’s Supply Chain Director, Gentry Pate on how the IoT is transforming their global service parts planning:

  • real-time connectivity between their vendors & Dell
  • autonomous planning capabilties incorporating predictive modeling
  • real-time alerts, inventory & delivery time
  • Smart Warehouse using latest robotics
  • Digital Repair

Requires changes in people’s roles, processes & tech. Evaluated their existing process & switched to new roles. Also have to deal with fast-changing tariff and other issues. Worked with PTC to create a simplified execution structure through online collaboration, exception-based engagement, and single source of communication.

Also automated purchase orders, do machine learning for network replenishment, intermittent forecast model improvements.

Most orders now automated using SPM. Now place most POs every 6 weeks, vs. 2 weeks. He outlined their entire complex autonomous planning journey.

Added “Control Center Intelligence” that’s proactive, uses visualization, diagnostic, predictive, simulations.

He concluded by discussing Dell’s future organization skill sets.

More Monday afternoon content….

Pushing the Service Envelope With Predictive Analytics

Digital transformation of service:

  • reduce unscheduled downtime
  • provides signal of impending part failure to user to reduce equipment downtime

Microsoft describes their cloud/edge collaboration with PTC — just the topic of my most recent Industry Week column! OMG: talked about new autonomous cloud capsule that Microsoft is mooring in the ocean — bringing the cloud to where the people are!

Microsoft marine cloud capsule: cloud in the water!

Common IoT Commercialization Errors

Two top errors picked by the audience in a poll were projects that are slow-paced, when speed and agility are needed, and weak use cases (i.e., “they are too ambiguous about the value for the user.”)

For example, Kodak was there early with digital photography, but didn’t move quickly. Need to have quick feedback: that’s where my “circular company” concept and my “Essential Truth” about replacing liner processes with cyclical ones comes in!

Case Study: How Caterpillar Develops Compelling IIoT Apps

Remote Asset Monitoring of remote generators. Promotes peace of mind for customers. Started this in 1991! Based on realization that one-size-doesn’t-fit-all with connected devices. They use a hybrid Waterfall/Sprint project style.

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My Latest Industry Week Column: why the edge is critical for IoT

As is so often the case, technological success can often result in unintended consequences that, left unremedied, could negate the benefits.

As my latest Industry Week column I looked at one of those issues — the explosion of real-time sensor data collected by the IoT — and the solution to the problem that adds many other benefits in the process, shifting at least part of the data processing from the cloud to the “edge” of the system, preferably at the point of collection.

As I pointed out, if the data must be moved to the cloud first for processing (no mean feat, BTW, because it can also overwhelm the transmission networks) and then back to the collection point for action, it negates the IoT’s major benefit, being able to collect and then act on data in near-real time, allowing precise regulation of things.

Of course edge processing adds additional costs for distributed processing hardware and software, and can add risk if the device is easily tampered with, but, overall, it seems to me the edge should not replace, but definitely supplement the cloud in robust IoT systems.

I based the column on a comprehensive, short-of-over-promotion report, Data at the Edge, created by an industry consortium, State of the Edge. It’s a quick read, and I recommend it!

Read it and let me know what you think.

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LifePod: could voice-powered devices change aging?

It’s been a while since I’ve addressed my concept of “SmartAging,” which combines “Quantified Self” health devices that can improve seniors’ health and transform their relationship to their doctors into more of a partnership, and smart home devices that help people manage their homes more easily as they age.

Since I’m nearing my 74th birthday next week, LOL, it seemed an appropriate time to return to the meme.

What triggered my interest was LifePod, a new desktop device similar to an Amazon Echo or Google Assistant, which also is available separately as a platform that can be used on either of those devices or an Apple HomePod.

LifePod

It reminds me of my only slightly tongue-in-cheek post last year about the SNL Amazon/AARP Echo “Silver Edition,” which was aimed at the Greatest Generation and offered features such as shouting, instead of speaking to you, and answering to 250 or so names that had something in common with Alexa, LOL. As I’ve found in my 5+ years of explaining advanced tech to seniors, especially those older than 80 who may have never encountered it in the workplace, there was an element of truth in the SNL “ad”: voice really could be the killer input device, because you don’t have understand the underlying technology — you just have to speak the relevant command.

In fact, I read a piece this morning quoting a leading venture capitalist who predicted that keyboards as an input device will become a quaint relic in the next five years, and that voice “is the opportunity of the decade.” I became a believer eight years ago, when I was writing Data Dynamite, and, facing a bad case of writer’s block, ended up dictating the first draft using Dragon Dictate!

LifePod is a second-generation voice device, built on the abilities of devices such as the Echo, which is billed as a “voice-controlled virtual caregiver, companion and digital assistant.” It adds a significant component beyond what those devices offer: users no longer have to use the prompts such as “Hey, Siri,” or “Alexa,” to “wake” it (don’t know about you, but on occasion I’ve been known to summon one or the other of those gals using the wrong name — sometimes on purpose to see what “she” will answer, LOL).

“Instead, it will start conversations with the elderly user based on 5 preset schedules (wake-up, morning, afternoon, evening, and bedtime) created by an adult child or other remote caregiver. This can be particularly valuable for early-stage dementia patients who may simply forget key actions such as taking a morning pill or staying hydrated.

Equally important is the role the LifePod can play in dealing with a critical problem for house-bound seniors, social isolation, which is increasingly seen as a crucial factor in aging. Among other things, it can offer them “.. quizzes, health and nutrition info, games, music, audiobooks, jokes, history and trivia, and social networking” that provoke interaction.

The company says that LifePod will incorporate AI that will recognize deviations in factors such as sleep patterns and physical activity, then automatically alert their caregivers.

Macadamian, which collaborated in the platform’s creation, said that future offerings that leverage digital links that in the future mean that:

“LifePod could be integrated with personal hygiene devices like connected toothbrushes, or motion detectors to better track the actions of the user and increase their safety or further assist them in the home. It could also integrate with medical devices like blood pressure monitors, glucose meters, or sleep trackers to track the user’s health in correlation to the other data and include it in the daily reports or use it to trigger alerts.”

In the past I’ve ranted that seniors don’t want to be stigmatized by alert devices hanging around their necks that scream “I’m elderly, pity me.” LifePod, a cool device sitting on their kitchen tables or as a service added to their existing Echo or Home device, are just what the doctor ordered.

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Digital Twins: Could They Have Uncovered the Boeing 737 Problems Sooner? — and how might they benefit your company

Tragically, the Boeing 737-Max includes an Internet of Things technology — the “digital twin” — that might have avoided the current tragedies, if only its use had been extended from the engines to the entire plane’s operations. Even if your products don’t involve such high stakes as a jet plane does, your company should seriously consider adding the digital twin to your services, because it can benefit every aspect of your operations and strategy.

Let me explain.

A joint venture company between GE Aviation and a French company makes the Max’s CFM International LEAP engines.  Every one of them is paired to a digital representation of the engine, a digital twin, that allows an engineer thousands of miles away to instantly monitor an inflight engine’s current operations.  That, among many other benefits, allows GE to replace the preventive maintenance of the past, which had to rely on after-the-fact data about when the average engine needed to be maintained, with “predictive maintenance,” which uses data about the earliest evidence of a possible problem to trigger a sequence to intervene early on, well before a major problem. At its most extreme, that could mean that when a plane whose sensors have detected an engine anomaly lands at its destination, the mechanic would be ready to go, knowing not only where in the engine the problem existed, but also having had the replacement part automatically dispatched from a distribution hub, so the replacement could be done quickly and at least cost.  No wonder GE has created more than hundreds of thousands of digital twins for products ranging from the jet engines to medical devices.

What if Boeing had extended the “digital twin” concept to the entire plane’s operations, including the navigation software?  The real essence of the Internet of Things — of which the digital twin is perhaps the ideal example of how the IoT merges the digital and physical — is that it allows everyone who needs it to instantly share (the verb is critical!) that real-time data — something that was impossible in the past.  In this case, that could mean real-time sharing between the cockpit, the airline, and Boeing, rather than after the fact harvesting of data from a plane’s “black box.” Hypothetically, the ability to share the real-time cockpit data would have meant that all those parties could have collaboratively brainstormed solutions to possible in-flight problems such as the maneuvering characteristics augmentation system, (MCAS) that has been fingered the possible cause of the problems.

OK, how does this ability to share real-time data from a digital twin apply to your company’s products and operations? 

The potential benefits extend to every aspect of your operations:

More radically, the digital twin’s benefits in terms of reliability and improved design can allow a fundamental change in your business model, away from selling products to leasing them, with the customer’s actual cost based on use of the product (if the turbine is sitting on the ground being repaired, it ain’t bringing the manufacturer any revenue!).  All three major jet turbine manufacturers — GE, Pratt & Whitney, and Rolls-Royce — have made this switch. They can even create new revenue streams by selling the real-time in-flight data to airlines, which can mash it up with atmospheric conditions, fuel prices, etc., to maximize flight efficiency.  Similarly, Hortilux, which makes greenhouse lights, now provides artificial light, plus data on growing conditions, rather than selling the bulbs.

Even more important than the potential to improve individual aspects of operations through digital twins is the potential for innovation and creativity if all departments (and, if you choose, even supply chain and distribution network partners and, conceivably, your customers) look at and can discuss the data—ground truth—simultaneously.

Determination of exactly what happened and why with the 737-Maxes will require intense scrutiny, but your company can benefit from the wake-up call these tragedies have provided to the IoT’s new-found ability to gather and share operating data instantly, with the result being improving every aspect of your operations and strategy.

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No more excuses for companies to delay IoT strategies!

Frequently companies reluctant to invest in the IoT cite their massive investments in legacy production equipment that doesn’t have M2M capacity as a barrier.  However, J & J was able to cut operating cuts by 10% and reduce downtime by 5%.  As a WEF spokesman told The Irish Times,
“The fourth industrial revolution doesn’t always mean newer, more expensive machines. Rather it can mean better communicating with and responding to the technologies you do have… By implementing simple internet-of-things devices across a range of machines that were never intended to ‘talk’ to each other, the Depuy Synthes factory created real-time digital twins of its factory equipment to monitor performance.”
Another of the nine, P & G’s Rakona plant in the Czech Republic, has also brought an existing plant up to date with the IoT. Built in 1875, it “can seamlessly change the product being manufactured with a push of a button, an innovation that reduced costs by 20% and upped output by a whopping 160%.”

5G Raises the Stakes for IoT Security

Last week’s international political news was a dramatic reminder of how inextricably linked technology progress (in this case, 5G infrastructure) and high-stakes global intrigue and even warfare have become.

The speed-up in deployment of 5G networks in the US and worldwide can both dramatically increase the IoT’s benefits (with reduced latency we’ll get a significant increase in the volume of rich, near-real-time data, allowing autonomous vehicles and other hard-to-imagine advances) but also the dangers (the possibility of China, Russia or someone else launching a cyber attack through a “back door” that could cripple our critical infrastructure). That puts the IoT right in the middle of a very tense global diplomatic and technical battle, with the outcome potentially having a big impact on the IoT’s near-term growth.

The US government’s indictment of Huawei (coming on the heels of an as-yet un-corroborated Bloomberg story that Huawei had planted chips in Apple and Amazon devices that would allow “back-door” attacks not just on the devices but on overall networks) plus a little-noticed story about yet another Chinese manufacturer of cheap IoT devices that could let a bad actor install malware in its firmware are just the latest reminders that IoT privacy and security must be designed in from the beginning, using what the EU calls “privacy by design.”

Don’t forget that we’ve already had a very real preview of exactly how dangerous this can be:  the 2016 DDoS attack on Internet infrastructure company Dyn that used IoS devices with inadequate protections as its the Trojan horses to launch the attack. Much of the Internet was crippled for several hours.

It also means, as I wrote in The Future Is Smart and elsewhere that it’s not enough to design in privacy protections into your own products and services: if the public and companies lose confidence in the IoT because of an attack aimed at anyone, even the irresponsible companies that don’t worry about security, I learned during my years doing corporate crisis management that there’s an irrational but nonetheless compelling guilt-by-association phenomenon that can destroy confidence in all IoT. Is that fair? No, but that doesn’t mean it’s any less of a reality. That’s why it’s critical that you take an active role in both supporting enlightened federal policy on both 5G infrastructure and IoT regulation, especially privacy and security regulations that are performance-based, rather than descriptive (which might restrict innovation), as well as joining industry organizations working on the privacy and security issues, such as the IMC, Internet of Things Association, and IMC.

In The Future Is Smart I wrote that, counterintuitively, privacy and security can’t be bolted on after you’ve done the sexy part of designing cool new features for your IoT device or service. This news makes that even more the case. What’s required is a mind-set in which you think of privacy and security from the very beginning and then visualize the process after its initial sale as cyclical and never-ending: you must constantly monitor emerging threats and then upgrade firmware and software protections.

 

 

 

IoT-based “Regulation 3.0” Might Have Avoided Merrimack Valley Tragedies

Pardon me: this is a very personal post.

For about an hour Thursday night we didn’t know whether my son’s home in Lawrence was one of those blown up by the gasline explosions (fortunately, he and his dear family were never at risk — they’re living in Bolivia for two years — but the house was right at Ground Zero). Fortunately, it is intact.

However, the scare took me back to an op-ed I wrote eight years ago in Federal Computer Week after the BP catastrophe in the Gulf, when I was working in disaster communications. I proposed what in fact was an IoT-based way to avoid similar disasters in the future: what I called “Regulation 3.0,” which would be a win-win solution for critical infrastructure companies (85% of the critical infrastructure in the US is in private hands) and the public interest by installing IoT-monitoring sensors and M2M control devices that would act automatically on that sensor data, rather than requiring human intervention:

  • in daily operations, it would let the companies dramatically increase their efficiency by giving real-time data on where the contents were and the condition of pipelines, wires, etc. so the operations could be optimized.
  • in a disaster, as we found out in Lawrence and Andover, where Columbia Gas evidently blew it on response management, government agencies (and, conceivably, even the general public, might have real-time data, to speed the response (that’s because of one of my IoT Essential Truths, “share data, don’t hoard it”).

We could never have that real-time data sharing in the past, so we were totally dependent on the responsible companies for data, which even they probably didn’t have because of the inability to monitor flow, etc.

Today, by contrast, we need to get beyond the old prescriptive regulations, which told companies what equipment to install (holding back progress when new, more efficient controls were created, and switch to performance-based regulation where the companies would instead be held to standards (i.e., in the not-too-distant future, when the IoT will be commonplace, collecting and sharing real-time data on their facilities), so they’d be free to adopt even better technology in the future.

However, Regulation 3.0 should become the norm, because it would be better all around:

  • helping the companies’ improve their daily operations.
  • cutting the cost of compliance (because data could be crunched and reported instantly, without requiring humans compiling and submitting it).
  • reducing the chance of incidents ever happening (When I wrote the op-ed I’d never heard of IoT-based “predictive maintenance,” which lets companies spot maintenance issues at the earliest point, so they can do repairs quickly and cheaper than if having to respond once they’re full-blown problems.).

I had a chance to discuss the concept yesterday with Rep. Joe Kennedy, who showed a real knowledge of the IoT and seemed open to the incident.

Eight years after I first broached the concept, PTC reports that the pipeline industry is now impementing IoT-based operations, with benefits including:

  • Situational awareness..
  • Situational intelligence..
  • and Predictive analytics.

Clearly, this is in the economic interests of the companies that control the infrastructure, and of the public interest.  The Time has come for IoT-based “Regulation 3.0.”

 

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?).

Live Blogging #LlveWorx ’18, Day 2

Aiden Quilligan, Accenture Industry X.0, on AI:

  • Mindset and AI: must undo what Hollywood has done on this over years, pose it as human vs. machine.
  • We think it should be human PLUS machine.
  • he’s never seen anything move as fast as AI, especially in robotics
  • now, co-bots that work along side us
  • exoskeletons
  • what do we mean by AI?  Machine learning.  AI is range of technologies that can learn and then act. AI is the “new work colleague” we need to learn to get along with.
  • predictions: will generate #2.9 trillion in biz value and recover 6.2 billion hours of worker productivity in 2021.
  • myths:
    • 1) robots evil, coming for us: nothing inherently anti-human in them.
    • 2) will take our jobs. Element of truth in terms of repetitive, boring work that will be replaced. They will fill in for retiring workers. Some new industries created by them.  Believe there will be net creation of jobs.
    • 3) current approaches will still work.

6 steps to the Monetization of IoT, Terry Hughes:

  • Digital native companies (Uber) vs. digitally transforming companies
  • also companies such as Kodak that didn’t transform at all (vs. Fujifilm, which has transformed).
  • Forbes: 84% of companies have failed with at least one transformation program.  Each time you fail you lose 1/2 billion
  • steps:
    • 1) devices with potential
    • 2) cloud network communication
    • 3) software distribution
    • 4) partner and provider ecosystem
    • 5) create a marketplace.
    • 6) monetization of assets.
  • crazy example of software company that still ships packages rather than just download because of initial cost in new delivery system
  • 3 big software challenges for digitally transforming company
    • fragmented silos of software by product, business unit & software
    • messy and complex distribution channels
    • often no link between software and the hardware that it relates to
  • importance of an ecosystem
    • Blackberry example of one that didn’t have the ecosystem
  • 3rd parties will innovate and add value around a manufacturer’s core products
  • in IoT it’s a land grab for mindshare of 3rd-party innovators.
  • need strong developer program
  • tools for app development and integration
  • ease of building and publishing apps
  • path to discovery and revenue for developer
  • IDC: developer ecosystem allow enterprises to massively scale distribution
  • digitally native companies have totally different models (will get details later…)
  • hybrids:
    • GE Healthcare:  working with Gallus BioPharma
    • Heidelberg & Eig have digital biz model for folding carton printing. Pay per use
  • Ford is heading for mobility as a transformation

 


Bernard Marr: Why IoT, Combined With AI and Big Data, Fuels 4th Industrial Revolution

 

  • connecting everything in house to Internet
  • Spotify: their vision is they understand us better. Can correlate your activity on Apple Watch (such as spinning) & create a play list based on that)
  • FitBit: the photo will estimate your calorie content.
  • John Deere
  • ShotSpotter: the company that monitors gun shots
  • understanding customers & markets better than before:
    • Facebook: better at face recognition than we are. They can predict your IQ, your relationship status.
  • Lot of frightening, IMHO, examples of AI analyzing individuals and responding without consideration of ethics and privacy
  • 3) improving operations and efficiency:
    • self-driving boats
    • drones
    • medicine through Watson

panel on IoT:

  • Don’t be afraid of the cloud
  • Ryan Cahalane, Colfax: prepare for big, start small and move fast. They had remarkable growth with switch to IoT.  Not a digital strategy, but digital in everything they do. Have “connected welders,” for example.
  • Justin Hester, Hirotec: most importatnt strategic digital transformation decision your organization can make is the selection of a platform. The platform is the underlying digital thread that enables your team to meet  the unique and chanding needs of your organization and to scale those solutions rapidly. “Assisted reality” in ThingWorx
  • Shane O’Callahan, TSM (Ireland):  Make industrial automation equipment for manufacturing. Understanding your key value driver is where to start. Then start samll, scale fast and get a win!

Jeffrey Miller, PTC: Digital Transformation:

  • if you start with digital strategy you’re starting in wrong place Start with business strategy. 
  • Couple with innovation vision merged with digital strategy. Add business use cases.
  • Jobs: it’s not how much you spend on R & D, but “about the people you have, you you’re dled, and how much you get it”
  • create an environment for innovation
    • do we encourage experimentation?
    • is it ok to fail
  • identify digital technologies to provide the required operating capabilities:
    • have we conducted proofs of concept?
    • experimented, tested  and validated?
    • reviewed use cases & success studies?
    • delivered small, important, scalable successes?

Matt,  PTC: Bringing Business Value to AR:

  • augmented service guidance
  • remote expert guidance
  • manufacturing: machine setup and turnover, assembly and process
  • example of Bell & Howell towers to store online sales in WalMart stores for customer pickup: very expensive to send one to a store for salesperson to use in sales — now just use AR app to give realistic demo without expense.
  • service: poor documentation organization, wants accurate, relevant, onsite info for technician. Want to remove return visits because the repair wasn’t done 1st time, or there’s a new technician. Manuals in binders, etc. Instead, with AR, requirements are quick access to current info. Finally, a demo.

Suchitra Bose, Accenture: Manufacturing IIoT, Driving the Speed of Digital Manufacturing:

  • convergence of IT and OT
  • expanding digital footprint across your entire factory
  • PTC has wide range of case studies (“use cases” in biz speak…) on aspects of IoT & manufacturing.
http://www.stephensonstrategies.com/">Stephenson blogs on Internet of Things Internet of Things strategy, breakthroughs and management