1、Stayup-to-date withthe OReilly Solid NewsletterLearn about the latest in the rapidly emeginga ea of the connected world,Internet ofThings, and dis uptive innovation.luu- e-Paw -au.oFO9!Li See asample:寸 eEpam paa1,s8a e,s0801, 0a0aqLu- 芒 e-PaW_A au.o lON 寸oidFTWARE/HARDWAREEVERYWHEREIndustrial Intern

2、etJon BrunerIndustrial Internetby Jon BrunerCopyright 2013 OReilly Media. All rights reserved. Printed in the United States of America.Published by OReilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472.OReilly books may be purchased for educational, business, or sales promotional

3、 use. Online editions are also available for most titles (). For more information, contact our corporate/institutional sales department: (800) 998- 9938 or .March 2013:First EditionRevision History for the First Edition:2013-03-27: First releaseSee h

4、ttp://catalog/errata.csp?isbn=9781449368258 for release details.Nutshell Handbook, the Nutshell Handbook logo, and the OReilly logo are registered trademarks of OReilly Media, Inc.Many of the designations used by manufacturers and sellers to distinguish their prod ucts are claimed as trad

5、emarks. Where those designations appear in this book, and OReilly Media, Inc. wasawareofatrademarkclaim, thedesignationshavebeenprinted in caps or initial caps.While every precaution has been taken in the preparation of this book, the publisher and authors assume no responsibility for errors or omis

6、sions, or for damages resulting from the use of the information contained herein.ISBN: 978-1-449-36825-8Table ofContentsAcknowledgments.v1. The industrial internet.1Characteristics2Internet architecture and practice applied to industrial settings2Software abstraction makes the physical world accessi

7、ble3Optimization above the level of asingle machine4Substitution of software for assets5Substitution of software for labor5Everything becomes a sensor7Machines built nightly7Ultra-transparent markets replace regulation8Security problems arise from systems that were builtwithout connectivity in mind9

8、2. Security.113. Industry Focus15Energy15Building controls and demand response17Utilities19Generation21Automotive23Transportation26Aviation27Railroads32Health care34Manufacturing35iii4. TheroleofSiliconValleyincreatingtheindustrialinternet.39Silicon Valley and industry adapting to each other405. Con

9、clusion.43AcknowledgmentsI am grateful to more than 50 experts from the industries discussed in this report for speaking with me, hosting me on illuminating visits, and introducing me to their helpful contacts. Many of them gave me permission to share their insights here but asked that their names a

10、nd affiliations not be published.General Electric has generously underwritten this report, and it put its industry experts at my disposal while I wrote it. Nevertheless, the thematic development of the industrial internet in this report is strictly my own, formed from discussions with my colleagues

11、at OReilly and outside experts.Weve been developing our framing of the industrial internet since the fall of 2012, and we will continue to cover this space with blog posts, interviews, and videos at http:/oreil.ly/industrial-internet. Jon Brunerv CHAPTER 1The industrial internetThe barriers between

12、software and the physical world are falling. Its becoming easier to connect big machines to networks, to harvest data from them, and to control them remotely. The same changes in soft ware and networks that brought about decades of Silicon Valley in novation are now reordering the machines around us

13、.Since the 1970s, the principles of abstraction and modularity have made it possible for practically anyone to learn how to develop soft ware. That radical accessibility, along with pervasive networks and cheap computing power, has made it easy to create software solutions to information problems. I

14、nnovators have responded, and have re shaped practically any task that involves gathering information, ana lyzing it, and communicating the result.Something similar is coming to the interfaces between software and the big machines that power the world around us. With a network connection and an open

15、 interface that masks its underlying complex ity, a machine becomes a Web service, ready to be coupled to software intelligence that can ingest broad context and optimize entire systems of machines.The industrial internet is this union of software and big machines what you might think of as the ente

16、rprise Internet of Things, operating under the demanding requirements of systems that have lives and ex pensive equipment at stake. It promises to bring the key characteristics of the Web modularity, abstraction, software above the level of a single device to demanding physical settings, letting inn

17、ovators break down big problems, solve them in small pieces, and then stitch together their solutions.1The foundational technologies of the industrial internet are available now to anyone from big industrial firms to garage inventors. These technologies include: pervasive networks; open-source micro

18、control lers; software that can analyze massive amounts of data, understand human preferences, and optimize across many variables; and the com puting power needed to run this intelligence, available anywhere at little cost.Anyone who can recast physical-world problems into software terms now has acc

19、ess to the broad world of “stuff that matters”: conserving energy and reducing our impact on the environment; making our world safer, faster, and more comfortable; improving the productivity and well-being of workers; and generating economic opportunity.CharacteristicsThe industrial internet1 is an

20、approach to bringing software and ma chines together, not a particular group of technologies. These are the principles driving its development.Internet architecture and practice applied to industrial settingsThe industrial internet isnt necessarily about connecting big machines to the public Interne

21、t; rather, it refers to machines becoming nodes on pervasive networks that use open protocols. Internet-like behavior follows: machines publish data to authorized recipients and receive operational commands from authorized senders.Think of the difference between an airplane built 40 years ago and a

22、modern design like the Boeing 787. Older airplanes have direct link ages between systems from the landing-gear switch to the landing gear, for instance. Newer airplanes use standard networks, in which the landing gear is a node thats accessible to any other authorized part of the system not only the

23、 landing-gear switch, but also safety, au topilot, and data-logging systems. Software can understand the status of the airplane in its entirety and optimize it in real-time (and, with a data connection to dispatchers and the air-traffic control system, soft1. We use lowercase internet to refer gener

24、ically to a group of interconnected networks, and uppercase Internet to refer to the public Internet, which includes the World Wide Web.ware can also understand the airplanes relationship to other planes and to the airspace around it).The infrastructure of the Internet is highly flexible and scalabl

25、e. Once a system of machines is brought together on a network, its easy to add new types of software intelligence to the system, and to encompass more machines as the scope of optimization expands.Software abstraction makes the physical world accessibleWeb services mask their underlying complexity t

26、hrough software in terfaces. Need to convert an address to latitude and longitude? Googles geocoder API2 will make the conversion almost instantaneously, masking the complexity of the underlying process (text parsing, look ing up possible matches in a database, choosing the best one). Geolo cation t

27、hus becomes accessible to anyone building a Web site no expertise in cartography needed. These services become modules in Web applications, which are designed with minimal assumptions about the services they use so that a change or failure in one module wont break the entire application.In the same

28、way, the industrial internet presents machines as services, accessible to any authorized application thats on the network. The scope of knowledge needed to contribute to a physical-world solution becomes smaller in the process.Making a furnace more efficient, for instance, might involve some combina

29、tion of refining its mechanical and thermal elements (ma chine design) and making it run in better relation to the building its in and the occupants of that building (controls). The industrial inter net makes it possible to approach these challenges separately: connect the furnace to a network and g

30、ive it an API that guards against dam aging commands, and the control problem becomes accessible to someone who knows something about software-driven optimization, but not much about furnaces.In other words, the industrial internet makes the physical world ac cessible to anyone who can recast its pr

31、oblems in terms that software can handle: learning, analysis, system-wide optimization.2. /maps/documentation/geocoding/Characteristics | 9At the same time, this transfer of control to software can free machines to operate in the most efficient ways possible. Giving a fur

32、nace an advanced control system doesnt obviate the need for improvements to the furnaces mechanical design; a machine that anticipates being controlled effectively can itself be designed more efficiently.Optimization above the level of a single machineWith machines connected in Internet-like ways, i

33、ntelligence can live anywhere between an individual machines controller and the univer sal network level, where data from thousands of machines converges. In a wind turbine, for instance, a local microcontroller adjusts each blade on every revolution. Networked together, a hundred turbines can be co

34、ntrolled by software that understands the context of each machine, adjusting every turbine individually to minimize its impact on nearby turbines.Optimization becomes more effective as the size of the system being optimized grows, and the industrial internet can create systems that are limitless in

35、scope. Upgrades to the American air-traffic control system, for example, will tie every airplane together into a single sys tem that can be optimized at a nationwide level, anticipating a flights arrival over a congested city long before it approaches. (The current system is essentially a patchwork

36、of space controlled at the local and regional level.)Software intelligence, which relies on collecting lots of data to build models, will become smarter and more granular as the scope of data collection increases. We see this already in the availability of traffic congestion data gathered by network

37、ed navigation systems and smart phone apps. The next step might be cloud-level software that gathers, analyzes, and re-broadcasts other machine data from networked cars the state of headlights and windshield wipers to detect rain, for instance.Optimization can go beyond a single kind of machine to t

38、ake into account external market conditions. “Each silo has achieved its highest possible level of efficiency,” says Alok Batra, the CTO and chief archi tect for GE Global Research.3 “If we dont break down silos, we cant generate more efficiency. Nothing operates in isolation anymore. If3. Note: GE

39、has sponsored this paper. See the acknowledgements section.you operate a manufacturing plant, you need to know about wind and power supplies.”Substitution of software for assetsThe industrial internet will, as Astro Teller4, Captain of Moonshots at Googlex, suggests, “trade away physical complexity

40、for control- system problems.” As machines deliver their work more efficiently, well need fewer of them and the machines themselves will become simpler.Consider, for instance, that Californias state-wide electricity demand stays below 30 gigawatts about 80% of the time. For about 20 hours every year

41、, though, it surges past 47 gigawatts.5 Utilities must build out massive capacity thats only used during peak hours a few days each summer.Flattening out those peaks could dramatically reduce the capacity needed to reliably serve the states electricity needs, and thats a control- system problem. An

42、interconnected stack of software that extends all the way from power plants to light bulbs parts of which are some times called the “smart grid” could gather system-wide context as well as local preferences to gently control demand, dimming lights during peak hours and letting temperatures drift sli

43、ghtly in buildings whose owners accept a financial incentive in return for flexibility.Substitution of software for laborGiven a high-volume stream of accurate machine data, software can learn very fast. And, by transmitting what it learns back into a network, it can accumulate knowledge from a broa

44、d range of experiences. While a senior pilot might have 10,000 to 20,000 hours of flying experience, a pilotless aircraft operating system might log hundreds of thousands of hours in just a year, with each of many planes transmitting anoma lies back to a universal learningalgorithm.4. http:/astrotel

45、/5. /cleanenergy/documents/suca/ee_and_dr.pdfU.S. manufacturing productivity grew by 69% in real terms between 1977 and 20116, in part because machines automated many low-level human tasks. In health care, similar gains have been elusive: produc tivity grew by just 26% in rea

46、l terms over the same period as spending nearly quadrupled (and productivity economic output divided by number of employees is itself an imperfect measure for what we want from our health care system).The kind of automation that has revolutionized manufacturing has so far failed to revolutionize hea

47、lth care. Doctors and nurses spend much of their time reading machine data from sensors (everything from blood-pressure cuffs to MRI machines), matching patterns of symp toms to likely diagnoses, and prescribing medication within formal guidelines. As routinized as that work is, it still requires a

48、great deal of human judgment and discretion that automation tools have so far not been able to provide.The industrial internet will make the health care sector more efficient by providing intelligence on top of machine data. Software will ingest sensor readings and perform real-time analysis, freein

49、g doctors and nurses to do work that requires more sophisticated and nuanced pa tient interaction. Progress is already well underway in home moni toring, which lets patients who just a few years ago would have needed constant monitoring in a hospital bed recover at home instead.As automation did to

50、factory workers, the industrial internet will un doubtedly obviate the need for certain types of jobs. If information is seamlessly captured from machines as well as people, well need fewer low-level data shepherds like medical transcriptionists (ironically, the demand for these types of jobs has in

51、creased with the introduction of electronic medical records, though thats largely due to the persistence of poor user interfaces and interoperability barriers). The industrial internet will automate certain repetitive jobs that have so far resisted automation because they require some degree of huma

52、n judgment and spatial understanding driving a truck, perhaps, or recognizing a marred paint job on an assembly line.6. See /industry/xls/GDPbyInd_VA_NAICS_1998-2011.xls and /industry/xls/GDPbyInd_VA_NAICS_1947-1997.xls for output by industry and employment from 199

53、8 to 2011; see /industry/xls/ GDPbyInd_FTPT_1948-1997.xls for employment before 1998. The health care statis tics here refer to combined ambulatory, hospital, and residential care, NAICS codes 621, 622, and 623.In fast-growing fields like health care, displaced workers might be ab s

54、orbed into other low- or medium-skill roles, but in others, the eco nomic tradeoffs will be similar to those in factory automation: higher productivity, lower prices for consumers, continued feasibility of manufacturing in high-cost countries like the United States but also fewer jobs for people wit

55、hout high-demand technicalskills.Everything becomes a sensorAny machine that registers state data can become a valuable sensor when its connected to a network, regardless of whether its built for the express purpose of logging data. A cars windshield-wiper switch, for example, can be a valuable huma

56、n-actuated rain sensor if its con nected to the vehicles internal network.Software operating across several machines can draw from aggregate data conclusions that cant be drawn from local data. One car running its windshield wipers doesnt necessarily indicate rain, but a dozen cars running their win

57、dshield wipers in close proximity strongly suggests that its raining.Software operating across several types of machine data can also draw out useful systemic insights. Combined with steering-wheel, speed, GPS, and accelerator-pedal readings, a sensor-driven rain indication could warn a driver that

58、hes moving too fast for road conditions, or help him improve his fuel economy by moderating his acceleration habits.Machines built nightlyThe Web brought about the end of the annual software release cycle.7 Provided as a loosely-coupled service on the Internet, software can be improved and updated c