The IoT Can Improve Safety and Profitability of Inherently Dangerous Job Sites

You may remember I wrote several months ago about a collaboration between SAP and SK Solutions in Dubai (interesting factoid: Dubai is home to almost 25% of the world’s cranes [assume most of the rest nest at Sand Hill, LOL], and they are increasingly huge, and that makes them difficult to choreograph.

I’m returning to the subject today, with a slightly broader emphasis on how the IoT might manage a range of dangerous job sites, such as mining and off-shore oil rigs, allowing us to do now that we couldn’t do before, one of my IoT Essential Truths.

I’m driven in part by home-town preoccupation with Boston’s bid for the 2024 Olympics, and the inevitable questions that raises on the part of those still smarting from our totally-botched handling of the last big construction project in these parts, the infamous “Big Dig” tunnel and highway project.

I’m one of those incurable optimists who think that part of ensuring that the Olympics would have a positive “legacy” (another big pre-occupation in these parts) would be to transform the city and state into the leading example of large-scale Internet of Things implementation.

There are a couple of lessons from SAP and SK Solutions’ collaboration in Dubai that would be relevant here:

    • The system is real-time: the only way the Boston Olympic sites could be finished in time would be through maximizing efficiency every day. Think how hard that is with a major construction project: as with “for want of a nail the kingdom was lost,” the sensitive interdependence between every truck and subcontractor on the site — many of which might be too small to invest in automation themselves — is critical. If information about one sub being late isn’t shared, in real-time, with all the other players, the delays — and potential collisions — will only pile up. The system includes an auto-pilot that makes immediate adjustments to eliminate operator errors. By contrast, historical data that’s only analyzed after the fact won’t be helpful, because there’s no do-overs, no 2025 Olympics!
    • The data is shared: that’s another key IoT Essential Truth.  “Decision-makers using SK Solutions on a daily basis span the entire organization. Besides health and safety officers, people responsible for logistics, human resources, operations and maintenance are among the typical users.”  The more former information silos share the data, the more likely they are to find synergistic solutions.
    • The system is inclusive, both in terms of data collection and benefits: SK Solutions’ Founder and Inventor Séverin Kezeu, came up with his collision-avoidance software pre-IoT, but when the IoT became practical he partnered with SAP, Cisco, and Honeywell to integrate and slice and dice the data yielded by the sensors they installed on cranes and vehicles and other sources.  For example, the height of these cranes makes them vulnerable to sudden weather changes, so weather data such as wind speed and direction must be factored in, as well as the “machinery’s position, movement, weight, and inertia…. The information is delivered on dashboards and mobile devices, visualized with live 3-D images with customizable views. It’s also incredibly precise.”As a result, by using SAP’s HANA platform, a system developed to reduce construction accidents also makes predictive maintenance of the cranes and other equipment, and lets the construction companies monitor Key Performance Indicators (KPIs) such as asset saturation, usage rates, and collisions avoided.  McKinsey reports that construction site efficiency could improve dramatically due to better coordination: “One study found that buffers built into construction project schedules allowed for unexpected delays resulting in 70 to 80 percent idle time at the worksite.Visibility alone can allow for shorter buffers to be built into the construction process.”

Several other great IoT solutions come to mind at the same time, both relating to dangerous industries. Off-shore oil rigs and mining were treated at length in the recent McKinsey omnibus IoT forecast, “The Internet of Things: Mapping the Value Beyond the Hype:”

  • off-shore rigs: “Much of the data collected by these sensors [30,000 on some rigs] today is used to monitor discrete machines or systems. Individual equipment manufacturers collect performance data from their own machines and the data can be used to schedule maintenance. Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.” (my emphasis). 
  • mining: “In one mining case study, using automated equipment in an underground mine increased productivity by 25 percent. A breakdown of underground mining activity indicates that teleremote hauling can increase active production time in mines by as much as nine hours every day by eliminating the need for shift changes of car operators and reducing the downtime for the blasting process. Another source of operating efficiency is the use of real-time data to manage IoT systems across different worksites, an example of the need for interoperability. In the most advanced implementations, dashboards optimized for smartphones are used to present output from sophisticated algorithms that perform complex, real-time optimizations. In one case study from the Canadian tar sands, advanced analytics raised daily production by 5 to 8 percent, by allowing managers to schedule and allocate staff and equipment more effectively. In another example, when Rio Tinto’s (one mine) crews are preparing a new site for blasting, they are collecting information on the geological formation where they are working. Operations managers can provide blasting crews with detailed information to calibrate their use of explosives better, allowing them to adjust for the characteristics of the ore in different parts of the pit.”
 In all of these cases, the safety and productivity problems — and solutions are intertwined.  As McKinsey puts it:
“Downtime, whether from repairs, breakdowns, or maintenance, can keep machinery out of use 40 percent of the time or more. The unique requirements of each job make it difficult to streamline work with simple, repeatable steps, which is how processes are optimized in other industries. Finally, worksite operations involve complex supply chains, which in mining and oil and gas often extend to remote and harsh locations.”
Could it be that the IoT will finally tame these most extreme work situations, and bring order, safety, and increased profitability?  I’m betting on it.

McKinsey IoT Report Nails It: Interoperability is Key!

I’ll be posting on various aspects of McKinsey’s new “The Internet of Things: Mapping the Value Beyond the Hype” report for quite some time.

First of all, it’s big: 148 pages in the online edition, making it the longest IoT analysis I’ve seen! Second, it’s exhaustive and insightful. Third, as with several other IoT landmarks, such as Google’s purchase of Nest and GE’s divestiture of its non-industrial internet division, the fact that a leading consulting firm would put such an emphasis on the IoT has tremendous symbolic importance.

McKinsey report — The IoT: Mapping the Value Beyond the Hype

My favorite finding:

“Interoperability is critical to maximizing the value of the Internet of Things. On average, 40 percent of the total value that can be unlocked requires different IoT systems to work together. Without these benefits, the maximum value of the applications we size would be only about $7 trillion per year in 2025, rather than $11.1 trillion.” (my emphasis)

This goes along with my most basic IoT Essential Truth, “share data.”  I’ve been preaching this mantra since my 2011 book, Data Dynamite (which, if I may toot my own horn, I believe remains the only book to focus on the sweeping benefits of a paradigm shift from hoarding data to sharing it).

I was excited to see that the specific example they zeroed in on was offshore oil rigs, which I focused on in my op-ed on “real-time regulations,” because sharing the data from the rig’s sensors could both boost operating efficiency and reduce the chance of catastrophic failure. The paper points out that there can be 30,000 sensors on an rig, but most of them function in isolation, to monitor a single machine or system:

“Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.”

Yet, the researchers found that only about 1% of the rig data was being used, because it rarely was shared off the rig with other in the company and its ecosystem!

The section on interoperability goes on to talk about the benefits — and challenges — of linking sensor systems in examples such as urban traffic regulation, that could link not only data from stationary sensors and cameras, but also thousands of real-time feeds from individual cars and trucks, parking meters — and even non-traffic data that could have a huge impact on performance, such as weather forecasts.  

While more work needs to be done on the technical side to increase the ease of interoperability, either through the growing number of interface standards or middleware, it seems to me that a shift in management mindset is as critical as sensor and analysis technology to take advantage of this huge increase in data:

“A critical challenge is to use the flood of big data generated by IoT devices for prediction and optimization. Where IoT data are being used, they are often used only for anomaly detection or real-time control, rather than for optimization or prediction, which we know from our study of big data is where much additional value can be derived. For example, in manufacturing, an increasing number of machines are ‘wired,’ but this instrumentation is used primarily to control the tools or to send alarms when it detects something out of tolerance. The data from these tools are often not analyzed (or even collected in a place where they could be analyzed), even though the data could be used to optimize processes and head off disruptions.”

I urge you to download the whole report. I’ll blog more about it in coming weeks.

Incredible example of rethinking “things” with Internet of Things

Ladies and gentlemen, I give you the epitome of the IoT-enabled product: the trash can!

My reader statistics do not indicate this blog has a heavy readership among trash cans, but let me apologize in advance to them for what I’m about to write: it’s not personal, just factual.

I’m sorry, but you municipal trash cans are pathetic!

Dented. Chipping paint. Trash overflowing. Smelly. Pests (ever seen any of those prize city rats? Big!!!) Sometime even knocked over. And, worst of all, you are so…. DUMB. You just sit there and don’t do anything.

BigBelly trash compactor and recycling center

But that was then, and this is now.

I have seen the future of trash cans, and, equally important, perhaps the best example I’ve seen of how smart designers and company strategists can –and must — totally rethink products’ design and how they are used because of the Internet of Things! 

At last week’s Re-Work Internet of Things Summit there were many exciting new IoT examples (I’ll blog others in coming weeks) but perhaps the one that got more people talking was the BigBelly trash compactor & recycling system, high-tech successor to the lowly trash can.

The company’s motto is that they are “transforming waste management practices and contributing to the Smart Cities of tomorrow.” Indeed!

I was first attracted to the BigBelly systems because of my alternative energy and environmental passions: they featured PV-powered trash compactors, which can quintuple the amount a trash container can hold, eliminating overflowing containers and the need to send trucks to empty them as frequently. Because the containers are closed, there’s no more ugly banana peels and McDonald’s wrappers assaulting your delicate eyes — or noses! Equally important, each is paired with a recycling container, which are almost never seen on city streets, dramatically reducing the amount of recyclables that go into regular trash simply because no recycling containers are accessible downtown.  These features alone would be a noteworthy advance compared to conventional trash cans.

But BigBelly wasn’t content to just improve the efficiency of trash and recyclable collection: they decided to make the containers smart.

The company worked with Digi to add wireless communications to the bins. This is a critical part of BigBelly’s broader significance: when the IoT first started to creep into corporate consciousness, of course designers thought about smart versions of high-value products such as cars, but lowly trash cans? That deserves real praise, because they fundamentally re-examined not only the product as it existed, but also realized that an IoT-based version that could also communicate real-time data would become much more versatile and much more valuable.

Here’s what has resulted so far (and I suspect that as the BigBellys are more widely deployed and both city administrators and others become aware of their increased functionality, other features will be added: I see them as “Smart City Hubs!”):

  • heatmap of trash generation in Lower Manhattan using real-time data from BigBellys and CLEAN dashboard

    instead of traditional pickup routes and schedules that were probably based on sheer proximity (or, as BigBelly puts it a little more colorfully, “muscle memory and gut instincts”), they now offer a real-time way to monitor actual waste generation, through the “CLEAN Management Console,” which allows DPW personnel to monitor and evaluate bins’ fullness, trends and historical analysis, for perspective. Collections can now be dynamic and driven by current needs, not historical patterns.

  • For those cities that opt for it, the company offers a Managed Services option where it does the analysis and management of the devices — not unlike the way jet turbine manufacturers now offer their customers value-added data that allows them to optimize performance — and generates new revenue streams for the manufacturers.
  • You may remember that I blogged a while ago about the “Collective Blindness” analogy: that, until the IoT, we humans simply couldn’t visualize much about the inner workings of the material world, so we were forced to do klugy work-arounds.  That’s not, strictly speaking, the case here, since trash in a conventional can is obviously visible, but the actual volume of trash was certainly invisible to those at headquarters. Now they can see — and really manage it.
  •  They can dramatically increase recycling programs’ participation rate and efficiency. As BigBelly says, the system provides “intelligent infrastructure to support ongoing operations and free up staffing and resources to support new and expanded recycling programs. Monitoring each separate stream volumes, days to fullness, and other activities in CLEAN enables you to make changes where needed to create a more effective public recycling program. Leverage the stations’ valuable sidewalk real estate to add messaging of encouraging words to change your users’ recycling behaviors.”Philadelphia is perhaps the best example of how effective the system can be. The city bought 210 of the recycling containers in 2009. On average, each collected 225 pounds of recyclables monthly, resulting in 23.5 tons of material diverted from landfills. Philly gets $50 per ton from the recycling — and avoiding $63 in landfill tipping fees, with a total benefit to the city of $113 per ton, or $2599 per month.

Here’s where it really gets neat, in my estimation.

Because the BigBellys are connected in real time, the devices can serve a number of real-time communication functions as well (enabled by an open API and an emphasis by BigBelly on finding collaborative uses). That includes making them hubs for a “mesh network” municipal wi-fi system (which, by the way, means that your local trash container/communications hub could actually save your life in a disaster or terror attack, when stationary networks may be disrupted, as I explained years ago in this YouTube video).

The list of benefits goes on (BigBelly lists all of them, right down to “Happy Cities,” on its web site). Trust me: if my premise is right that we can’t predict all of the benefits of the IoT at this point because we simply aren’t accustomed to thinking expansively about all the ways connected devices can be used, there will be more!

So here’s my take-away from the BigBelly:

If something as humble and ubiquitous as a municipal trashcan can  be transformed into a waste-reduction, recycling collection, municipal communication hub, then to fully exploit the Internet of Things’ full potential, we need to take a new, creative look at every material thing we interact with, no longer making assumptions about its limited role, and instead looking at it creatively as part of an interconnected network whose utility grows the more things (and people!) it’s connected with!

Let me know your ideas on how to capitalize on this new world of possibilities!

Sensors remain critical to spread of Internet of Things

What happens with sensor design, cost, and security remains front-and-center with the Internet of Things, no matter how much we focus on advanced analytical tools and the growing power of mobile devices.

That’s because, on one hand, truly realizing the IoT’s full potential will require that at least some sensors get to the low-power, tiny size and cheap costs needed to realize Kris Pister’s dream of “smart dust” sensors that can be strewn widely.

On the other hand, there’s the chance that low-end sensors that don’t include adequate security firmware can’t keep up with the changing nature of security risks and may give hackers access to the entire network, with potentially disastrous effects.

That’s why several reports on sensors caught my eye.

PWC released a report, Sensing the Future of the Internet of Things, zeroing in on sensor sales as a proxy for increased corporate investment in the IoT, and concluding that by that measure, “the IoT movement is underway.” Based on its 2014 survey of 1,500 business and technology leaders worldwide, there was one eye-popping finding: the US lags behind the entire rest of the world in planned spending on sensors this year: 26% of Asian and almost as many from South America (percentage not given)  followed closely by Africa, with 18%.  The surprising laggards? Europe with 8% and North America, dead last at only 7%.  Hello?????

Equally interesting was the company’s listing of the industry segments leading the deployment of sensors and examples of the sensors they’re using:

  • Energy & Mining: 33%. “Sensors continuously monitor and detect dangerous carbon monoxide levels in mines to improve workplace safety.”
  • Power and Utilities: 32%.  Instead of the old one-way metering, “Internet-connected smart meters measure power usage every 15 minutes and provide feedback to the power consumer, sometimes automatically adjusting the system’s parameters.”
  • Automotive: 31%.  “Sensors and beacons embedded in the road working together with car-based sensors are used for hands-free driving, traffic pattern optimization and accident avoidance.”
  • Industrial: 25%. “A manufacturing plant distributes plant monitoring and optimization tasks across several remote, interconnected control points. Specialists once needed to maintain, service and optimize distributed plant operations are no longer required to be physically present at the plant location, providing economies of scale.”
  • Hospitality: 22%. “Electronic doorbells silently scan hotel rooms with infrared sensors to detect body heat, so the staff can clean when guests have left the room.”
  • Health Care: 20%. “EKG sensors work together with patients’ smartphones to monitor and transmit patient physical environment and vital signs to a central cloud-based system.”
  • Retail: 20%. “Product and shelf sensors collect data throughout the entire supply chain—from dock to shelf. Predictive analytics applications process this data and optimize the supply chain.”
  • Entertainment: 18%. “In the gaming world, companies use tracking sensors to transfer the movements of users onto the screen and into the action.”
  • Technology: 17%. “Hardware manufacturers continue to innovate by embedding sensors to measure performance and predict maintenance needs before they happen.”
  • Financial Services: 13%. “Telematics allows devices installed in the car to transmit data to drivers and insurers. Applications like stolen vehicle recovery, automatic crash notification, and vehicle data recording can minimize both direct and indirect costs while providing effective risk management.”

The surprises there were that health care penetration was so low, especially because m-health can be so helpful in diagnosis and treatment, while the examples of telematics seemed off the mark in the financial services category. Why not examples such as ApplePay?

More compelling were the relatively high rates of sensor deployment in high-stakes fields such as energy, utilities, and automotive: those are such huge industries, and the benefits of real-time data are so compelling that they show the IoT is really maturing.

Finally, the percentage of companies investing in sensors grew slightly, from 17% to 20%, with 25%of what PWC labels “Top Performers” are investing in them compared to 18% the previous year. Surprisingly, most companies don’t get it about sensors’ importance: only “14% of respondents said sensors would be of the highest strategic importance to their organizations in the next 3–5 years, as compared to other emerging technologies.”

Most important, 54% of those “Top Performers” said they’d invest in sensors this year.


 

Sensors’ promise as the size decreases — radically — and functionality increases was highlighted by The Guardian.  It focused on PragmaticIC Printing, a British firm that prints tiny, hairlike sensors on plastics. CEO Scott White’s hope is that:

” the ultra-thin microcircuits will soon feature on wine bottles to tell when a Chablis is at the perfect temperature and on medication blister packs to alert a doctor if an elderly patient has not taken their pills.

“With something which is slimmer than a human hair and very flexible, you can embed that in objects in a way that is not apparent to the user until it is called upon to do something. But also the cost is dramatically lower than with conventional silicon so it allows it to be put in products and packaging that would never justify the cost of a piece of normal electronics,” said White.

 

These uses certainly meet my test of real innovation: what can you do that you couldn’t do before. Or, as White puts it, “It is the combination of those factors [price and size] which allows us to start thinking about doing things with this which wouldn’t even be conceivable with conventional silicon based electronics.”

Another article that really caught my eye regarded a new category of “hearable” — and perhaps even, more radically, “disappearables” –sensors which the headline boldly predicted “As Sensors Shrink, Wearables Will Dis-appear.” But they were barely here in the first place, LOL!  The article mentioned significant breakthroughs in reducing sensors’ size and energy requirements, as well as harvesting ambient energy produced by sources such as bodily movement:

“Andrew Sheehy of Generator Research calculates that, for example, the heat in a human eyeball could power a 5 milliwatt transmitter – more than enough, he says, to power a connection from a smart contact lens to a smartphone or other controlling device.”

 The same article mentioned some cutting-edge research such as a Google/Novartis collaboration to measure glucose levels in tears via a contact lense, and an edible embedded microchip — the size of a grain of sand — and powered by stomach juices, which would transmit data by Bluetooth.
Elsewhere, a sampling of sensor design breakthroughs in recent months show the potential for radical reductions in costs and energy needs as well as increased sensitivity and data yield:

HOWEVER, as I said above, here’s what worries me. Are developers paying enough attention to security and privacy? That could be a real downfall for the IoT, since many sensors tend to be in place for years, and the nature of security challenges can change dramatically during that time.  Reducing price can’t be at the expense of security.

Let me know what steps you’re taking to boost sensor security, and I’ll mention them in a future post!

IoT: What Can You Do That You Couldn’t? Heavy Construction

Not sure why, but I’m particularly fascinated by how the IoT can transform parts of the economy that have been around for more than 100 years, such as the way the Union Pacific uses it to reduce derailments — and worse.

One of those tradition-bound industries where the IoT Essential TruthWhat Can You Do Now That You Couldn’t Do Before” is starting to revolutionize both daily practices and strategy is heavy construction, both for buildings and public works.

First of all, heavy construction is inherently dangerous, so anything that can be done to manage that danger is beneficial.

Lots of very heavy machinery; many people, frequently on foot; almost impossible to coordinate all of them in the past, especially as vehicles enter and leave the site.  According to OSHA, in the US alone, 796, or 20.3% of all workers killed on the job in 2003 were killed on construction sites, primarily through falls, struck by objects, electrocution or “caught-in-between.” Of those, lack of coordination probably resulted in most of the struck by objects and “caught-in-between” deaths.

One of the most exciting developments in that regard is SAP’s demonstration program with SK Solutions, which makes anti-collision software, on a construction site in Dubai. They are capitalizing on new construction cranes and construction vehicle  that have sensors built in so their real-time location can be determined instantly. SAP and SK Solutions combine sensor-based data – such as 3-D motion control, location, load weight, equipment usage and wind speed – to avoid collisions with trucks  to enhance worker safety, improve productivity and reduce costs. The site and project managers monitor the equipment via a dashboard.

Less dramatic than collision avoidance is the way that construction companies are using real-time data from the equipment to maximize operating efficiency and reduce maintenance costs through innovations such as “predictive maintenance.”  As my Boston IoT MeetUp co-director Chris Rezendes of INEX Advisors discussed at the recent Association of Equipment Management Professionals Asset Management Symposium, “instrumentation of assets” through digital plans and models, sensors, data and embedded communication devices in buildings and bridges is becoming a key differentiator in the industry. According to Rezendes:

““Everybody in tech wants to instrument your assets, inventories, operations, people and processes… They are looking at instrumenting all manner of industrial machines, equipment and more. And they’re doing it really well…. You should feel threatened, at least a little bit, by big technology companies trying to instrument your assets for you, maybe to you… I’m going to tell it to you straight: He or she who controls the intelligence–the data about those assets, inventories and areas of operation–will control that market, the customer, the regulatory environment and the supply chain. They will control you.”

What a seismic shift from the old days of heavy construction, which was largely a matter of brute force and difficult demands on operators to remain always vigilant in the midst of loud noises.  Add in the sensors that these construction crews are now embedding in bridges’ structure and in buildings to monitor a wide range of stresses and environmental conditions, and the conclusion is inescapable: every industry can and will be fundamentally altered in the coming decade as equipment and processes begin switch the requirements from brawn to brains.

Lifting the Veil After the Sale: another IoT “Essential Truth”

Count me among those who believe the Internet of Things will affect every aspect of corporate operations, from manufacturing to customer relations.

Perhaps one of the most dramatic impacts will be on the range of activities that take place after the sale, including maintenance, product liability, product upgrades and customer relations.

In the past, this has been a prime example of the “Collective Blindness” that afflicted us before the IoT, because we basically had no idea what happened with our products once they left the factory floor.

In fact, what little data we did have probably served to distort our impressions of how products were actually used. Because there was no direct way to find out how the products were actually used, negative data was probably given exaggerated weight: we heard negative comments (warrantee claims, returns, liability lawsuits, etc.), loud and clear, but there was no way to find out how the majority of customers who were pleased with their products used them.

That has all changed with the IoT.

Now, we have to think about products  in totally new ways to capitalize on the IoT, and I think this merits another “Essential Truth” about the IoT:

Everything is cyclical.

Think about products — and industrial processes in general — in the old industrial system. Everything was linear: perhaps best exemplified by Henry Ford’s massive River Rouge Complex, the world’s largest integrated factory, and the epitome of integrated production.

Ford River Rouge Complex

“Ford was attempting to control and coordinate all of the necessary resources to produce complete automobiles.  Although Ford’s vision was never completely realized, no one else has come so close, especially on such a large scale.  His vision was certainly a success, one indication of this is the term Fordism, which refers to his style of mass-production, characterized by vertical integration, standardized products and assembly-line production”

At “The Rouge,” raw materials (literally: it had its own coke ovens and foundry!)  flowed in one side, and completed cars flowed out the other, bound for who knows where. Once the cars were in customers’ hands, the company’s contact was limited to whatever knowledge could be gleaned from owners’ visits to dealers’ service departments, irate calls from customers who had problems, and (in later days) safety recalls and/or multi-million dollar class-action lawsuits.

That linear thinking led to a terrible example of the “Collective Blindness” phenomenon that I’ve written about in the past: who knew how customers actually thought about their Model T’s? How did they actually drive them? Were there consistent patterns of performance issues that might not have resulted in major problems, but did irritate customers?

Sure, you could guess, or try to make inferences based on limited data, but no one really knew.

Fast forward to the newest auto manufacturer, Tesla, and its factory in Fremont, California (aside: this massive building — Tesla only uses a portion, used to be the NUMMI factory, where Chevy built Novas and Toyota built Corollas. Loved the perceptual irony: exactly the same American workers built mechanically identical cars [only the sheet metal varied] but the Toyotas commanded much higher prices, because of the perception of “Japanese quality.” LOL. But I digress….).

Tesla doesn’t lose track of its customers once the cars leave the plant.

Tesla assembly line

In fact, as I’ve written before, these “iPhones on wheels” are part of a massive cyclical process, where the cars’ on-board communications constantly send back data to the company about how the cars are actually doing on the road. And, when need be, as I mentioned in that prior post, the company was able to solve a potentially dangerous problem by simply sending out a software patch that was implemented while owners slept, without requiring customer trips to a repair shop!

I imagine that the company’s design engineers also pour over this data to discern patterns that might indicate elements of the physical design to tweak as well.

Of course, what would a blog post by me about IoT paradigm shifts be without a gratuitous reference to General Electric and its Durathon battery plant (aside to GE accounting: where should I send my W-9 and invoice so you can send me massive check for all the free PR I’ve given you? LOL)?

I can’t think of a better example of this switch to cyclical thinking:

  • including sensors into the batteries at the beginning of the production process rather than slapping them on at the end means that the company is actually able to monitor, and fine tune, the manufacturing process to optimize the critical chemical reaction. The same data allows the workers to remove defective batteries from the assembly line, so that every battery that ships works.
  • once in the field (and, remember: these batteries are deployed in incredibly remote areas where it might take days for a repair crew to reach and either service or repair them) the same sensors send back data on how the batteries are functioning. I don’t know about the specifics in the case of these batteries, but GE has actually created new revenue streams with other continuously-monitored devices by selling this data to customers who can use it (because the data is shared on a real-time basis, not just historically) to optimize performance.

Elsewhere, as I’ve mentioned before, General Electric’s William Ruh has said that being able to lift the veil of “Collective Blindness” through feedback from how customers actually use their products has even revolutionized their product design process:

“… G.E. is adopting practices like releasing stripped-down products quickly, monitoring usage and rapidly changing designs depending on how things are used by customers. These approaches follow the ‘lean start-up’ style at many software-intensive Internet companies. “’We’re getting these offerings done in three, six, nine months,’ he (Ruh) said. ‘It used to take three years.’”

Back in the ’90’s, I used to lecture and consult on what I called “Natural Wealth,” a paradigm shift in which we’d find all the inspiration we needed for an information-based economy in a table-top terrarium that embodies billion-year-old  principles of nature:

  • embrace chaos, don’t try to control it. (i.e., use open systems rather than proprietary ones)
  • create symbiosis: balance competition with cooperation (IFTTT.com, where you release your APIs to create synergistic mashups with others).
  • close the loop.

With the IoT, we can finally put that last principle into practice, substituting cyclical processes for linear ones.  At long last, the “systems dynamics” thinking pioneered by Jay Forrester and his disciple, Peter Senge, can become a reality. Here’s a closing tip to make that possible: in addition to SAP’s HANA or other analytics packages, look to systems dynamics software such as isee systems’  iThink to model your processes and transform linear into cyclical ones. Now get going: close the loop!

Is GE the future of manufacturing? IoT + nanotech + 3D-printing

The specific impetus for this post was an article in The Boston Globe about heart stents that fit perfectly because they’re 3-D printed individuallly for each patient.

GE jet engine 3-D-printed fuel nozzle

That prompted me to think of how manufacturing may change when three of my favorite technologies — nanotech, 3-D printing and the Internet of Things — are fully mature and synergies begin (as I’m sure they will) to emerge between the three.

I’m convinced we’ll see an unprecedented combination of:

  • waste elimination: we’ll no longer do subtractive processes, where a rough item is progressively refined until it is usable.  Instead, products will be built atom-by-atom, in additive processes where they will emerge exactly in the form they’re sold.
  • as with the stents, products will increasingly be customized to the customer’s exact specifications.
  • the products will be further fine-tuned based on a constant flow of data from the field about how customers actually use them.

Guess what?  The same company is in on the cutting edge of all three: General Electric (no, I’m not on their payroll, despite all my fawning attention to them!):

  • Their Industrial Internet IoT initiative is resulting in dramatic changes to their products, with built-in sensors that relay data constantly to GE and the customer about the product’s current status, allowing predictive maintenance practices that cuts repair costs, optimizing the device’s performance for more economical operations, and even allowing GE to switch from selling products to leasing them, with the lease price determined dynamically using factors such as how many hours the products are actually used.  Not only that, but they practice what they preach, with 10,000 sensors on the assembly line at their Durathon battery plant in Schenectady, plus sensors in the batteries themselves, allowing managers to roam the plant with an iPad to get instant readings on the assembly line’s real-time operation, to fine-tune the processes, and to be able to spot defective batteries while they are still in production, so that 100% of the batteries shipped will work.
    They’re also able to push products out the door more rapidly and updating them quicker based on the huge volumes of data they gather from sensors built into the products: “… G.E. is adopting practices like releasing stripped-down products quickly, monitoring usage and rapidly changing designs depending on how things are used by customers. These approaches follow the ‘lean start-up’ style at many software-intensive Internet companies. “’We’re getting these offerings done in three, six, nine months,’ he [William Ruh] said. ‘It used to take three years.’”
  • They’ve made a major commitment to 3-D printing, with 100,000 3-D printed parts scheduled to be built into their precision LEAP jet engines — a big deal, since there’s not a great deal of fault tolerance in something that may plunge to the earth if it malfunctions! As Bloomberg reported, “The finished product is stronger and lighter than those made on the assembly line and can withstand the extreme temperatures (up to 2,400F) inside an engine.”  They’re making major investments to boost the 3-D printers’ capacity and speed.  Oh, and did I mention their precedent-setting contest to crowd-source the invention of a 3-D printed engine mount?
  • They’re also partnering with New York State on perhaps the most visionary technology of all, nanotech, which manipulates materials on the molecular level. GE will focus on cheap silicon carbide wafers, which beat silicon chips in terms of efficiency and power, leading to smaller and lighter devices.

GE is the only member of the original Dow-Jones Index (in 1884) that still exists. As I’ve said before, I’m astounded that they not only get it about IoT technology, but also the new management practices such as sharing data that will be required to fully capitalize on it.

Thomas A. Edison is alive and well!

Interview w/ Echelon for its IoT blog

Just finished a delightful interview with three Echelon staffers for a forthcoming piece on its blog about my prognostications for the Industrial Internet of Things (AKA “Industrial Internet” ien GE-marketing speak).  They’ve been around in this field since the dark ages — 1988, and are now focusing on industrial applications.

My main point to them was the one I made in the SAP “Managing the Internet of Things Revolution” e-guide,  that even though the IoT hasn’t realized its full potential yet, that smart companies would begin creating and executing an IoT strategy now, “to connect their existing infrastructure and enhance key foundational IoT technologies,” optimizing their operating efficiency. Then they could build on that experience to make more fundamental transformations.

We touched 0n several other examples how the IoT could increase operating efficiency or make fundamental transformations:

At any rate, a fun time was had by all, and I’ll let you know when their blog post is up!

Egburt: key tool to make IoT pay off NOW

Posted on 31st October 2014 in data, energy, Internet of Things, maintenance, management, retail

As I’ve remarked before, writing the Managing the Internet of Things Revolution e-guide to IoT strategy for SAP was an eye-opener for me, shifting my attention from the eye-popping opportunities for radical reinvention through the IoT (products as services, user-customizable products, seamless smart phone-car integration, etc.) to very practical ways the IoT could begin optimizing companies’ current operations TODAY (BTW: much-deserved shout-out to SAP’s Mahira Kalim: it was dialogue with her that led to this insight!).

Egburt

In that vein, I was blown away at this week’s IoT Global Summit by the roll-out of Egburt by Camgian.

Egburt stresses two crucial, inter-related obstacles to widespread IoT solution deployment by mainstream businesses:

  • low cost-of-ownership sensing (by using very little energy, thereby extending battery life)
  • reducing potentially huge cloud-computing costs (because of the sheer volume of 24/7 sensor data) by allowing “fog computing,” where the processing would be done right at the collection process, with only the small amount of really relevant data being passed on to a central location.

The highlight of the product launch was a live demo of Egburt in real-time use at a chain of dollar stores in the south, monitoring a wide range of factors, from floor traffic to freezer operation (Camgian pointed out the system paid for itself in the first month of operation when it recorded failure of a freezer when the store was unoccupied, in time for immediate repairs to avoid loss of frozen foods).

Think about it: the very volume of Big Data possible with constant monitoring by a whole range of sensors can also be the IoT’s undoing. Since all that’s of interest in many cases is data that deviates from the norm, doesn’t it make sense to process that data at the collection point, then only pass on the deviations?

The company has targeted three IoT segments:

  • retail to reduce heating and lighting, and maximize sales through tracking foot traffic patterns to optimize product placement.
  • infrastructure: with sensors at key points such as bridges that will detect flooding and stress.
  • smart cities: optimizing emergency response.

In a sponsored white paper by ABI Research, “Evolution of the Internet of Things: from connected to intelligent devices,” they documented the benefits of going beyond first-generation, “connected,” IoT devices that were just sensors collecting and passing on data, to a second generation of “intelligent ones” such as Egburt the combine sensors and processing and offer not only lower operating costs but also — critically — more data security:

  • “Communication Latency: Handling more processing at the network’s edge reduces latency from the device’s actions. Use cases that are highly time-sensitive and require immediate analysis of, or response to, the collected sensor data are, in general, unfeasible under cloud- centric IoT architectures, especially if the data are sent over long distances.
  • “Data Security: By and large, sensitive and business-critical operational data are safer when encrypted adequately on the endpoint level. Unintelligent devices transmitting frequent and badly secured payloads to the cloud are generally more vulnerable to hacking and interception by unauthorized parties. Additionally, many enterprises may need to secure and control their machine data on the edge level for compliance reasons.
  • “Total Cost of Ownership: Perhaps most significantly, the paradigm shift can reduce the IoT systems’ total cost of ownership, or TCO. Intelligent devices are usually more expensive than less sophisticated alternatives, but their TCO over a long service life can be substantially lower.”

IMHO, for the IoT to be widely deployed, especially in SMEs, devices such as Egburt that reduce the cost of collecting and processing data are a critical component.


(PROMINENT DISCLAIMER: I actually won a FitBit in Camgian’s drawing at the conference. That has no impact on this review. Had I won the iPhone 6 that they also gave away, I would have totally been in the bag, LOL…)

GE & Accenture provide detailed picture of current IoT strategy & deployment

I’ll admit it: until I began writing the “Managing the Internet of Things Revolution” guide to Internet of Things strategy for SAP, I was pre-occupied with the IoT’s gee-wiz potential for radical transformation: self-driving cars, medical care in which patients would be full partners with their doctors, products that customers would be able to customize after purchase.

GE_Accenture_IoT_reportThen I came to realize that this potential for revolution might be encouraging executives to hold off until the IoT was fully-developed, and, in the process, ignoring low-hanging fruit: a wide range of ways that the IoT could dramatically increase the efficiency of current operations, giving them a chance to experiment with limited, less-expensive IoT projects that would pay off rapidly and give them the confidence and understanding necessary to launch more dramatic IoT projects in the near future.

This is crucially important for IoT strategies: instead waiting for a radical transformation (which can be scary), view it instead as a continuum, beginning with small, relatively-low cost steps which will feed back into more dramatic steps for the future.

Now, there’s a great new study, “Industrial Internet Insights Report for 2015,” from GE and Accenture, that documents many companies are in the early stages of implementing such an incremental approach, with special emphasis on the necessary first step, launching Big Data analytics — and that they are already realizing tangible benefits. It is drawn from a survey of companies in the US, China, India, France, Germany, the UK, and South Africa.

The report is important, so I’ll review it at length.

Understandably, it was skewed toward the industries where GE applies its flavor of the IoT (the “Industrial Internet”): aviation, health care, transportation, power generation, manufacturing, and mining, but I suspect the findings also apply to other segments of the economy.

The summary underscores a “sense of urgency” to launch IoT initiatives:

“The vast majority (of respondents) believe that Big Data analytics has the power to dramatically alter the competitive landscape of industries just within the next year, and are investing accordingly…” (my emphasis).

84% said Big Data analytics “has the power to shift the competitive landscape for my industry” within just the next year, and 93% said they feared new competitors will enter the field to leverage data.  Wow: talk about short-term priorities!

It’s clear the authors believe the transformation will begin with Big Data initiatives, which, IMHO, companies should be starting anyways to better analyze the growing volume of data from conventional sources. 73% of the companies already are investing more than 20% of their overall tech budget on Big Data analytics — and some spend more than 30%! 80 to 90% said Big Data analytics was either the company’s top priority or at least in the top 3.

One eye-opening finding was that 53% of respondents said their board of directors was pushing the IoT initiatives. Probably makes sense, in that boards are expected to provide necessary perspective on the company’s long-term health.

GE and Accenture present a  4-step process to capitalize on the IoT:

  1. Start with the exponential growth in data volumes
  2. Add the additional data volume from the IoT
  3. Add growing analytics capability
  4. and, to add urgency, factor in “the context of industries where equipment itself or patient outcomes are at the heart of the business” where the ability to monitor equipment or monitor patient services can have significant economic impact and in some cases literally save lives [nothing like throwing the fear of God into the mix to motivate skeptics!].
For many companies, after implementing Big Data software, the next step toward realizing immediate IoT benefits is by installing sensors to monitor the status of operating assets and be able to implement “predictive maintenance,” which cuts downtime and reduces maintenance costs (the report cites some impressive statistics: ” .. saving up to 12 percent over scheduled repairs, reducing overall maintenance costs up to 30 percent, and eliminating breakdowns up to 70 percent.” What company, no matter what their stance on the IoT, wouldn’t want to enjoy those benefits?). The report cites companies in health care, energy and transportation that are already realizing benefits in this area.
Music to my ears was the emphasis on breaking down data-sharing barriers between departments, the first time I’ve seen substantiation of my IoT “Essential Truth” that, instead of hoarding data — whether between the company and supply-chain partners or within the company itself — that the IoT requires asking “who else can use this data?” It said that: “System barriers between departments prevent collection and correlation of data for maximum impact.” (my emphasis). The report went on to say:

“All in all, only about one-third of companies (36 percent) have adopted Big Data analytics across the enterprise. More prevalent are initiatives in a single operations area (16 percent) or in multiple but disparate areas (47 percent)…. The lack of an enterprise-wide analytics vision and operating model often results in pockets of unconnected analytics capabilities, redundant initiatives and, perhaps most important, limited returns on analytics investments.”

Most of the companies surveyed are moving toward centralization of data management to break down the silos. 49% plan to appoint a chief analytics officer to run the operation, and most will hire skilled data analysts or partner with outside experts (insert Accenture here, LOL…).

The GE/Accenture report also stressed that companies hoping to profit from the IoT also must create end-to-end security. Do do that, it recommended a strategy including:
  1. assess risks and consequences
  2. develop objectives and goals
  3. enforce security throughout the supply chain.
  4. use mitigation devices specifically designed for Industrial Control Systems
  5. establish strong corporate buy-in and governance.

For the longer term, the report also mentioned a consistent theme of mine, that companies must begin to think about dramatic new business models, such as substituting value-added services instead of traditional sales of products such as jet engines.  This is a big emphasis with GE.  It also emphasizes another issue I’ve stressed in the “Essential Truths,” i.e. partnering, as the mighty GE has done with startups Quirky and Electric Imp:

“Think of the partnering taking place among farm equipment, fertilizer, and seed companies and weather services, and the suppliers needed to provide IT, telecom, sensors, analytics and other products and services. Ask: ‘Which companies are also trying to reach my customers and my customers’ customers? What other products and services will talk to mine, and who will make, operate and service them? What capabilities and information does my company have that they need? How can we use this ecosystem to extend the reach and scope of our products and services through the Industrial Internet?'”

While the GE/Accenture report dwelt only on large corporations, I suspect that many of the same findings would apply to small-to-medium businesses as well, and that the falling prices of sensors and IoT platforms will mean more smart companies in this category will begin to launch incremental IoT strategies to first optimize their current operations and then make more radical changes.

Read it, or be left in the dust!


PS: as an added bonus, the report includes a link to the GE “Industrial Internet Evaluator,” a neat tool I hadn’t seen before. It invites readers to “see how others in your field are leveraging Big Data analytics for connecting assets, monitoring, analyzing, predicting and optimizing for business success.” Check it out!

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