predictive maintenance

Four Battlegrounds

by Paul Scharre  · 18 Jan 2023

system may perform poorly on people of races or ethnicities that are not adequately represented in its training data. A machine learning algorithm used for predictive maintenance on one aircraft won’t work on another aircraft—it would need to be retrained on data for the new aircraft. It may not even

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ForAllSecure were covered in my book Army of None.) When it came to machine learning applications, Brown was most excited about DIU’s work on predictive maintenance. Maintenance is critical to ensuring military forces are ready to conduct operations. When Russia invaded Ukraine in early 2022, the poor state of Russian maintenance

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vehicles and aircraft hampered their effectiveness. Something as simple as poor tire maintenance can leave ground vehicles literally stuck in the mud, unable to advance. Predictive maintenance leverages historical data about a vehicle fleet’s maintenance needs to build an algorithm that can predict when a part will need to be repaired

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or replaced, rather than performing maintenance based on a fixed schedule. To build a predictive maintenance model, DIU turned to C3 AI, a commercial company that builds enterprise AI solutions across a range of industries, from optimizing supply chains to energy

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six months, C3 AI had an initial prototype based on seven to ten years of operational data from U.S. aircraft. Early tests of a predictive maintenance algorithm on the Air Force’s E-3 Sentry airborne warning and control system (AWACS) aircraft and C-5 cargo plane yielded an approximately 30

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on problems that are 10X in terms of the number of variables to develop predictive algorithms.” Following this initial success, DIU expanded C3 AI’s predictive maintenance work to include other aircraft, including Air Force F-16 and F-35A fighter jets and Army Apache and Blackhawk helicopters, covering over 1,200

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over $280 billion annually in operations and maintenance. Even a tiny improvement would net billions in savings. Building on this success, DIU has expanded their predictive maintenance work to Army and Marine Corps ground vehicles and optimizing Navy ship maintenance, which alone costs the Navy $10 billion a year. Michael Brown said

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?” In a congratulatory letter to DIU at the organization’s five-year anniversary, then–Secretary of Defense Mark Esper highlighted “scaling machine learning solutions for predictive maintenance” as one of DIU’s most impactful projects. Recent DoD Innovation Organizations A non-exhaustive list of DoD innovation-oriented organizations established since 2015 Defense

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a spark that ignited the spread of AI across DoD. Following Maven’s success, in 2018 DoD founded the JAIC, which developed AI applications for predictive maintenance, humanitarian assistance, and back-office business processes. More significantly, though, JAIC helped initiate a process of creating institutional resources for AI for other parts of

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Shanahan (no relation to Deputy Secretary Pat Shanahan), who had previously run Project Maven. The JAIC first focused its attention on two “national mission initiatives”: predictive maintenance and humanitarian assistance / disaster relief, which the military abbreviates by the awkward acronym HA/DR (sometimes pronounced “hadder”). Colonel Jason Brown, an Air Force intelligence

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functions as opposed to office functions, I think that we all win as a department overall.” Many of the military applications DoD is focusing on—predictive maintenance, image processing, or process automation—are back-office functions to support military operations, but that doesn’t mean they are unimportant. A common military aphorism

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problem, he argued, was the scale needed to bring AI to DoD. One early JAIC project, in collaboration with researchers from Carnegie Mellon, was a predictive maintenance tool for helicopters from the 160th Special Operations Aviation Regiment. Mulchandani said, “That’s fantastic that we did that for one engine, but how many

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for Army Rangers from the 75th Ranger Regiment during a training mission. Special operations helicopters were one of the first test projects for AI-based predictive maintenance. The DoD spends over $280 billion annually in operations and maintenance. Even a minor improvement in maintenance costs could yield massive savings. (Private First Class

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Readiness for the U.S. Department of Defense.” 196“actually, it was a small problem from their perspective”: Brown, interview. 196DIU expanded C3 AI’s predictive maintenance work: C3.ai, “US Defense Department Awards C3.ai $95M Contract Vehicle to Improve Aircraft Readiness Using AI,” news release, January 15, 2020, https://c3

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-department-awards-c3-ai-95m-contract-vehicle-to-improve-aircraft-readiness-using-ai/; Philong Duong, “AI-Based Predictive Maintenance to Enhance Readiness, Reduce In-Flight Failures,” C3.ai blog, July 21, 2020, https://c3.ai/blog/predictive-maintenance-to-enhance-readiness-reduce-in-flight-failures/. 196over $280 billion annually in operations and maintenance: Office

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Defense Strategy (US Department of Defense, 2020), 2, https://comptroller.defense.gov/Portals/45/Documents/defbudget/fy2021/fy2021_OM_Overview.pdf. 196DIU has expanded their predictive maintenance work: Artificial Intelligence Initiatives; “DIU Making Transformative Impact Five Years In.” 197Navy ship maintenance: Office of the Under Secretary of Defense (Comptroller), National Defense Budget

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.gov, May 7, 2020, https://www.armed-services.senate.gov/imo/media/doc/Brown_APQs_05-07-20.pdf. 197“scaling machine learning solutions for predictive maintenance”: Mark Esper, “Congratulations to the Defense Innovation Unit on Your Fifth Anniversary,” memorandum to Defense Innovation Unit, August 25, 2020, https://media.defense.gov/2020

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.ri.cmu.edu/carnegie-mellon-ai-collaborates-with-pentagon-to-improve-reliability-of-armys-black-hawk-helicopters/; “JAIC Partners with USSOCOM to Deliver AI-Enabled Predictive Maintenance Capabilities,” Joint Artificial Intelligence Center, December 17, 2020, https://www.ai.mil/news_12_17_20-jaic_partners_with_ussocom_to_deliver_ai-enabled

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_predictive_maintenance_capabilities.html; Sydney J. Freedberg Jr, “Fix It Before It Breaks: SOCOM, JAIC Pioneer Predictive Maintenance AI,” Breaking Defense, February 19, 2019, https://breakingdefense.com/2019/02/fix-it-before-it-breaks-socom-jaic

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-pioneer-predictive-maintenance-ai/; Shanahan, interview. 207“That’s fantastic that we did that for one engine”: Nand Mulchandani, interview by author, May 12, 2020. 207“We empower

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, 121, 130 Portman, Rob, 37 Poseidon, 289; See also Status-6 post-disaster assessment, 204 power metrics, 13 Prabhakar, Arati, 210 prediction systems, 287–88 predictive maintenance, 196–97, 201 Price, Colin “Farva,” 3 Primer (company), 224 Princeton University, 156, 157 Project Maven, 35–36, 52–53, 56–59, 194, 202, 205

Strong Towns: A Bottom-Up Revolution to Rebuild American Prosperity

by Charles L. Marohn, Jr.  · 24 Sep 2019  · 242pp  · 71,943 words

two or three decades, the city was receiving cash from this new development that they were free to spend elsewhere, despite the looming, and easily predictable, maintenance obligation. For cities in need of cash, new growth provides it. In the pattern of development we’re experimenting with today – one that is government

Theory and Practice of Group Psychotherapy

by Irvin D. Yalom and Molyn Leszcz  · 1 Jan 1967

. Yalom and K. Rand, “Compatibility and Cohesiveness in Therapy Groups,” Archives of General Psychiatry 13 (1966): 267–76. P. Sagi, D. Olmstead, and F. Atalsek, “Predicting Maintenance of Membership in Small Groups,” Journal of Abnormal Social Psychology 51 (1955): 308–11. In this study of twenty-three college student organizations, a significant

Subscribed: Why the Subscription Model Will Be Your Company's Future - and What to Do About It

by Tien Tzuo and Gabe Weisert  · 4 Jun 2018  · 244pp  · 66,977 words

like “smart” or “connected” to describe the physical objects in their environment. IoT will be the water they swim in. Everything we make will have predictive maintenance, improved efficiency, better safety, better usability. And everything will be made to order. We won’t be cranking out millions of identical widgets and stacking

Industry 4.0: The Industrial Internet of Things

by Alasdair Gilchrist  · 27 Jun 2016

is actually happening inside a machine or a process. Combined with these new breed of self-aware and self-predicting components analytics can provide accurate predictive maintenance schedules for machinery and assets, keeping them in productive service longer and reducing the inefficiencies and costs of unnecessary maintenance. This has been accelerated by

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improve operational processes appears to be akin to picking the low hanging fruit; it’s easily obtainable. Typically, most industrial companies head straight for the predictive maintenance tactic as this ploy returns the quickest results and return on investment. Some examples of this are the success experienced by Thames Water, the largest

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fresh-drinking water and water-waste recycler in the UK. It uses the IIoT for remote asset management and predictive maintenance. By using a strategy of sensors, remote communication, and Big Data analytics, Thames Water can anticipate equipment failures and respond quicker to any critical situation

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and enterprise business systems such as ERP (enterprise resource management), CRM (customer relationship management), WSM (warehouse stock management), and many others. As an example, a predictive maintenance service for a fabrication yard may have historical and predictive analytics on past and probable failure rates on welding equipment, which allows them to forecast

Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage

by Douglas B. Laney  · 4 Sep 2017  · 374pp  · 94,508 words

and potential information valuations. This gap appraises how much (or little) vision the organization has concerning how its data is leveraged. For example, even after predictive maintenance systems are put in place, there are identified opportunities to license this data to component suppliers in return for favorable pricing, plus a range of

Autonomous Driving: How the Driverless Revolution Will Change the World

by Andreas Herrmann, Walter Brenner and Rupert Stadler  · 25 Mar 2018

mileage, condition of the tires and fan belt, oil levels (in combustion engines) or battery levels (in electric cars), and thus be able to schedule predictive maintenance appointments. This greatly reduces the risk of the car breaking Time, Cost and Safety 303 Box 29.2. Statement by Carol Flannagan Carol A. Flannagan

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needed to destination because of travel management, lower traffic volume and route selection Time spent in car used for other activities instead of driving Convenience Predictive maintenance Fewer breakdowns Relief from routine trips Elderly, ill or disabled people can become more mobile Electric cars The technology of autonomous driving improves the efficiency

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. These data can be used for a number of applications, such as the development of V-to-home and V-to-business applications, preventive and predictive maintenance, and concierge and entertainment services. In addition, the data resulting from V-to-V and V-to-I communication will allow traffic flows in cities

Human + Machine: Reimagining Work in the Age of AI

by Paul R. Daugherty and H. James Wilson  · 15 Jan 2018  · 523pp  · 61,179 words

database, and AI technology is deployed to analyze that information for valuable insights. Data on the braking patterns of dump trucks, for example, might help predict maintenance problems. But this is hardly an example of pure automation that has replaced humans. The Rio Tinto command center employs a host of data analysts

Demystifying Smart Cities

by Anders Lisdorf

flows and is utilized is therefore an important way to improve mobility. Since breakdowns in the transit system are often a prime cause of delays, predictive maintenance is another application that improves mobility. Private transit – The personal vehicle has still not died since it is unique in providing the greatest flexibility in

Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations

by Thomas L. Friedman  · 22 Nov 2016  · 602pp  · 177,874 words

, wash it,” explained Ruh. “Preventive maintenance was: change the oil every six thousand miles, whether you drive it hard or not.” The new approach is “predictive maintenance” and “prescriptive maintenance.” We can now predict nearly the exact moment when a tire, engine, car or truck battery, turbine fan, or widget needs to

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now also knows that if you have to run your engine at 120 percent on a hot day, certain parts will need to have their predictive maintenance moved up. “We are constantly enriching and training our nervous system, and everyone benefits from the data,” said Ruh. But it’s not only the

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their performance, we just do it with software. I take a dumb locomotive and throw sensors and software into it, and suddenly I can do predictive maintenance, I can make it operate up and down the tracks at the optimal speeds to save gasoline, I schedule all the trains more efficiently and

Bikenomics: How Bicycling Can Save the Economy (Bicycle)

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Lessons from the Titans: What Companies in the New Economy Can Learn from the Great Industrial Giants to Drive Sustainable Success

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The Economic Singularity: Artificial Intelligence and the Death of Capitalism

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by Viktor Mayer-Schönberger and Thomas Ramge  · 27 Feb 2018  · 267pp  · 72,552 words

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by Fareed Zakaria  · 5 Oct 2020  · 289pp  · 86,165 words

Super Continent: The Logic of Eurasian Integration

by Kent E. Calder  · 28 Apr 2019