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Overview

• The Goal: Near-zero-downtime for manufacturing, mining, farming, service, etc. equipment and processes.


• The Means: Modeling optimum machine performance and monitoring real-world performance degradation, using sensor data already available (but underutilized) on most state-of-the-art equipment. Developing software systems to share this information over networks. Using the networked devices to schedule predictive maintenance before failure occurs. Ultimately, creating machines that learn, self-optimize, and even repair themselves.


• The Players: A university-industry partnership called The Center for Intelligent Maintenance Systems (IMS), consisting of The University of Wisconsin at Milwaukee and The University of Michigan, along with more than 40 corporate members and sponsors, including GM, Rockwell Automation, Harley-Davidson, Hitachi (Japan), Intel, ITRI (Taiwan), KONE Elevators (Finland), Questra, Siebel, United Technologies, Xerox, and others.


• The Gains: An estimated $35B per year savings across the US economy, not to mention incalculable growth opportunities in smart services.

Computing in the Real World
Marvin Minsky, one of the fathers of artificial intelligence, likes to say that we can make a computer capable of beating the reigning genius of chess, but we can’t make a robot capable of walking across the street as well as any normal two-year-old child.

Why? The real world is not a strictly regulated, closed system like a chess game. Sensing a player’s moves on a wired chessboard and responding quickly and intelligently is one thing. Sensing and physically responding to reality—stones, curbs, potholes, pedestrians, oncoming cars—is quite another.

Not long ago, the booming AI industry collapsed—taking with it many worthy businesses founded by serious scientists, such as Danny Hillis’s Thinking Machines—largely because it was unable to meet the unrealistic public and investor expectations generated by non-real-world computing triumphs like those of IBM’s “Deep Blue” chess-playing machine.

The Evolution of Product, Manufacturing, and Quality Goals as Automation Has Matured

Smart machines and products, increasing business automation, and next-generation e-services are intertwined phenomena. (Click the image for a larger on-screen version.) Source: Center for Intelligent Maintenance Systems (IMS)

Digital computing has radically transformed human affairs, but so far that transformation has taken place entirely on the computer’s terms. Computing’s many marvels have occurred in rigidly regulated systems to which human beings have adapted. With people as its focus and its crutch, IT has managed to float blissfully above the profound messiness of reality.

Today, if you want the benefits of computing, you sit down at a computer. Once at the computer, you do things the way the computer expects them to be done. If your hardware and software are decently designed, the experience feels relatively “natural” after a while—but only because you, the amazingly adaptable human being, have adapted to it.

To this day, IT has been something like a baby in diapers—cared for by people, coddled by people, tolerated by people. And rather astonishingly, most people don’t expect IT to get out of its diapers. They expect it to get cheaper, faster, and perhaps more entertaining, but they don’t expect it to grow up.

Academics and Entrepreneurs
Thus the promise of the M2M / Pervasive Internet era—i.e., billions of smart devices sharing their real-world, real-time data and controlling each other on a global network—has often been greeted with the kind of cynicism that killed its sexier predecessor, AI.

Even without AI’s massive self-hype, pervasive technologies face overt hostilities from various quarters (labor unions, misguided privacy protectors, misinformed members of the public and their elected representatives), as well as the standards battles being waged by private-sector companies who want the next era of computing to be based upon their proprietary technologies. The editor of a leading magazine for the “digerati” recently said, in a private conversation, “We’ve been hearing for years about the day when any electronic device will be able to talk to any other device. When is it actually going to happen?”

The dot-com crash caused investors to treat Internet technologies like the plague, but the people who actually understand and create high-tech innovation knew better. They knew that the crash was merely a speed-bump in an unstoppable journey. To continue innovating, and especially to “cross the chasm” between innovation and real-world impact, they had to find sources of greater sanity and support than a fickle investment community obsessed with quarterly reports.

In the years since the crash, academic / industry cooperation has proven to be indispensible. One excellent example is MIT’s Auto-ID Center, which was founded with the mission of building “an Internet of things.” The Center gathered over 100 corporate sponsors and delegates, created the Electronic Product Code (EPC™—now widely accepted as the successor to the barcode), and specified numerous proposed standards and industry milestones that have greatly advanced the commercialization of RFID technology. (Its work completed, the Auto-ID Center officially closed on October 26, 2003, transferring its technology to EPCglobal. Its university labs continue to exist as Auto-ID Labs.)

IMS and Automated “Machine Health”
The Center for Intelligent Machine Maintenance (IMS), headquartered at the University of Wisconsin at Milwaukee, is another example of academic researchers and scientists joining with industry stakeholders to create a future that everyone wants. IMS is a National Science Foundation Industry / University Cooperative Research Center whose industry members contribute cash or in-kind donations of technology, equipment, and expertise that enable the Center to create the research environment, industrial testbeds, and standardized software tools that will make automated “machine health” a reality.

When smart machines are networked and remotely monitored, and when their data is modeled and continually analyzed with sophisticated systems, it is possible to go beyond mere “predictive maintenance” to true machine “prognostics”—the process of pinpointing exactly which components of a machine are likely to fail, and when.

IMS’s mission is to achieve near-zero-downtime of industrial machinery. When the “health” of machinery is almost perfectly visible, a business can plan intelligently rather than being blindsided by failure. If a machine is about to fail, a sibling machine’s output might be accelerated (even automatically) to compensate for it, or another machine’s output might be slowed down, or the delivery of raw goods to the failing machine might be postponed. Whatever the case, knowledge becomes the power to optimize processes, save significant amounts of money, and achieve across-the-board “business automation.”

Seeing Failure Before it Occurs
Most machine maintenance today is either purely reactive (fixing or replacing equipment after it fails) or blindly proactive (assuming a certain level of performance degradation, with no input from the machinery itself, and servicing equipment on a routine schedule whether service is actually needed or not). Both scenarios are extremely wasteful.

To human beings, it often seems that machines fail suddenly, but in fact machines usually go through a measurable process of degradation before they fail. Today, that degradation is largely invisible to human users, even though a great deal of technology has been developed that could make such information visible.

Most state-of-the-art manufacturing, mining, farming, and service machines (e.g., elevators) are already quite “smart,” containing many sophisticated sensors and computerized components capable of delivering data about a machine’s status and performance.

The problem is that little or no practical use is made of most of this data. We have the smart devices, but we do not have a continuous and seamless flow of information throughout entire processes. Sometimes this is because the available data are not rendered in useable form. More often, no infrastructure exists for delivering the data over a network, or for managing and analyzing the data even if the devices were networked.

IMS’s leadership and industry partners are creating consensus and developing technologies that will make that continuous and seamless information-flow possible, and save industry literally billions of dollars in downtime-related costs. For example, in most production equipment or systems, different sensors measure different aspects of the same physical phenomena. In much the way that human “stereo” vision gives us depth perception, or multiple 2D perspectives can be combined into a 3D view, IMS is working on techniques for “sensor fusion” that will combine currently incompatible data from a variety of sensors to model a useable, holistic image of the actual state of a machine component.

Jay Lee and Jun Ni, the Co-Directors of IMS, recently estimated that the application of the “business automation” techniques and procedures being developed by their organization could result in a $35B annual savings across the US economy¹, broken down as follows:

• Spare parts inventory reduction: $6B annually


• Improved resources scheduling: $9B annually


• Enhanced logistics and supply chain: $15B annually


• Equipment uptime improvement: $5B annually

Turning Manufacturers into Service Providers
Bear in mind, however, that the Pervasive Internet’s vast power and reach is barely suggested by those numbers. Savings related to better machine uptime and supply chain visibility are only the beginning of the story. When a manufacturer is able to monitor its equipment remotely, and offer intelligent service plans based upon the real-world status of machines, the manufacturer is in a position to sell not merely equipment but a full business solution based upon that equipment—a solution that amounts to true, across-the-board “business automation.”

This will be of particular interest to OEMs that find themselves increasingly “disintermediated” from their ultimate customers. An OEM that stays connected to a customer for the life of a product can provide solutions-packages that might include not only smart maintenance scheduling but also vastly more intelligent, targeted marketing, as well as offers (from the company itself, or from partners) of data-warehousing and management services, upgrades, third-party merchandise, business expertise, and so on.

Even makers of commercial equipment (typically not as disintermediated as OEMs of retail products) stand to benefit greatly from the Pervasive Internet work being done at IMS. For example, KONE Corporation, one of IMS’s member companies, is the world’s fourth-largest manufacturer of elevators, escalators, and autowalks. Yet 60% of KONE’s revenue comes from maintenance and modernization of its machines, as well as maintenance of automatic building doors from other manufacturers. Despite its manufacturing, the company calls itself a service business.² Because KONE has had the foresight to position itself as a leading service provider in its market, the machine prognostics of IMS will gracefully blend with KONE’s existing business model and serve to improve that model and enhance the company’s profitability.

Conclusion
To participate in such savings, efficiencies, and new growth opportunities, companies need to understand and act upon the opportunities now. Beyond the technology itself, the Pervasive Internet is about forging new alliances and doing business in a new way. Driven by innovative collaborations like IMS and the Auto-ID Center, and with the additional impetus of new social drivers like homeland security, the technical “plumbing” issues of global device networking—and the applications for true enterprise automation—will see remarkable advances in the next calendar year.

Members of research and development partnerships like IMS will have earliest access to full solutions, and this will provide an important advantage. Early adopters will create significant barriers to latecomers. Yes, the tools of device networking and Web-based business services will be commonly available soon. So why not wait? Well, a crucial differentiator will be the imagination, creativity, and efficiency with which companies use the capabilities engendered by global device networking: automated asset management, supply-chain management, customer-relationship management, and so on. Intelligent use of these new capabilities will take time to plan. Often, it will involve significant re-structuring of business processes, business models, and business alliances. Potential adopters who are waiting on the sidelines for the M2M phenomenon to “shake out” or “get safe” will find themselves playing a game of catch-up that may be impossible to win.

The Pervasive Internet is nothing less than the next great era of digital technology. It marks a distinct divide between 20th century business and 21st century business, and its opportunities will literally dwarf those of the PC and dot-com eras. Right now, foresighted companies are hammering out the technological and business details of supply and adoption. If your company is not among them, your competitors are stepping into the future without you, and that may well cost you your chance for 21st century global market leadership.

NOTES
¹ Telephone interview with Dr. Jay Lee of the Center for Intelligent Maintenance Systems (IMS).

² KONE Web site.

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What do your colleagues and customers think about key Pervasive issues? Find out, fast and free.
Harbor’s site visitors are technologists and business leaders with the same thing on their minds: Internet-enabled device networking, smart services, and enterprise automation.

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Visit our site and try out the polls and charts. Click “Vote!” in the main navigation.