BAE Systems teams with AMS to reinforce support of artillery systems in Ukraine

Sur le même sujet

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  28 avril 2023 | International, C4ISR

  Connectivity will ‘make or break’ US military use of AI, official says

  The Pentagon is pursuing seamless networking through a connect-everything campaign known as Joint All-Domain Command and Control, or JADC2.

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  14 juillet 2020 | International, Aérospatial

  Air Force to Add 12 Weapons Systems for AI/ML-Informed Predictive Maintenance This Year

  The U.S. Air Force is to add a dozen weapons systems to its Enhanced Reliability Centered Maintenance (ERCM) model that employs artificial intelligence/machine learning (AI/ML) for predictive maintenance. Those systems are the Boeing [BA] F-15 fighter, B-52 bomber, RC-135 reconnaissance plane, C-17 transport, and A-10 Thunderbolt II close air support aircraft, the Lockheed Martin [LMT] AC/MC-130 gunships, F-16 fighter, and HH-60 helicopter, the Bell [TXT] and Boeing CV-22 tiltrotor, the Northrop Grumman [NOC] RQ-4 Global Hawk and the General Atomics‘ MQ-9 Reaper. “We have a couple of different initiatives under what we would call the umbrella of predictive maintenance,” Air Force Lt. Gen. Warren Berry, the service's deputy chief of staff for logistics, engineering and force protection, said during a July 9 Mitchell Institute for Aerospace Studies' Aerospace Nation virtual discussion. “One is Condition Based Maintenance Plus [CBM+]. We have three weapons systems in there right now: the C-5, the KC-135, and the B-1. They've been doing it for about 18 to 24 months now, and we're starting to get some real return on what it is that the CBM+ is offering us. The other element is called Enhanced Reliability Centered Maintenance [ERCM], which is really laying that artificial intelligence and machine learning on top of the maintenance information system data that we have today and understanding failure rates and understanding mission characteristics of the aircraft and how they fail, and then laying that into the algorithms that then tell us when parts are likely to fail based on failure rates and the algorithms we plug in.” “We're in the process of adding another 12 weapons systems under the ERCM umbrella this calendar year,” Berry said. Defense Daily has asked Air Force Materiel Command (AFMC) for the names of the 12 systems. AI/ML is to assume a significant role in predictive maintenance for the 11 combatant commands (COCOMs). In April last year, the Pentagon said that the new Joint Artificial Intelligence Center (JAIC) had delivered its first product, a predictive Engine Health Model (EHM) maintenance tool for Sikorsky [LMT] Black Hawk helicopters, to U.S. Special Operations Command's 160th Special Operations Regiment (SOAR) for use with SOAR's MH-60 helicopters. JAIC said that its Joint Logistics Mission Initiative (MI), one of six JAIC AI projects, is working “to develop a repeatable, end-to-end AI ecosystem” to bring EHM to scale across the Black Hawk fleet. EHM, developed in partnership with Carnegie Mellon University, “predicts the probability of an engine hot start so decision-makers can consider next steps,” including replacing the engine or holding it back for training missions instead of deployments in high-risk missions, Army Col. Kenneth Kliethermes, JAIC's Joint Logistics MI lead, said in a recent JAIC blog post. Another JAIC mission initiative, the Joint Warfighting MI, “is working with several COCOMs to build, test, and expand its Smart Sensor, a video processing AI prototype that rides on unmanned aerial vehicles and is trained to identify threats and immediately transmit the video of those threats back to manned computer stations for real-time analysis,” according to the JAIC blog post. Army Col. Bradley Boyd, the lead for the Joint Warfighting MI, said that the Smart Sensor could lead to “a dramatic reduction in the amount of data that has to be pushed back for a human to cull through.” “Instead of staring at one video feed and hours and hours of trees and rocks and nothing happening, that person can instead be monitoring 10 video feeds because they are only seeing the stuff that really matters,” Boyd said in the JAIC blog post. https://www.defensedaily.com/air-force-add-12-weapons-systems-ai-ml-informed-predictive-maintenance-year/army/

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  2 juin 2020 | International, Naval

  All aboard the Sea Train!

  Imagine the following scenario. Four medium-sized U.S. Navy vessels depart from a port along the United States' coast. There's no crew aboard any of them. About 15 nautical miles off the coast, the four vessels rendezvous, autonomously arranging themselves in a line. Using custom mechanisms, they attach to each other to form a train, except they're in the water and there's no railroad to guide them. In this configuration the vessels travel 6,500 nautical miles across the open ocean to Southeast Asia. But as they approach their destination, they disconnect, splitting up as each unmanned ship goes its own way to conduct independent operations, such as collecting data with a variety of onboard sensors. Once those operations are complete, the four reunite, form a train and make the return journey home. This is the Sea Train, and it may not be as far-fetched as it sounds. The Defense Advanced Research Projects Agency is investing in several technologies to make it a reality. “The goal of the Sea Train program is to be able to develop and demonstrate long-range deployment capabilities for a distributed fleet of medium-sized tactical unmanned vessels,” said Andrew Nuss, DARPA's program manager for Sea Train. “So we're really focusing on ways to enable extended transoceanic transit and long-range naval operations, and the way that we're looking to do that is by taking advantage of some of the efficiencies that we can gain in a system of connected vessels — that's where the name ‘Sea Train' comes from.” According to DARPA, the current security environment has incentivized the Navy and the Marine Corps to move from a small number of exquisite, large manned platforms to a more distributed fleet structure comprised of smaller vessels, including unmanned platforms that can conduct surveillance and engage in electronic warfare and offensive operations. While these unmanned vessels are smaller and more agile than their large, manned companions, they are limited by the increased wave-making resistance that plagues smaller vessels. And due to their size, they simply can't carry enough fuel to make the long-range journeys envisioned by DARPA without refueling. By connecting the vessels — physically or in a formation — the agency hopes the Sea Train can reduce that wave resistance and enable long-range missions. In February, the agency released a broad agency announcement to find possible vendors. Citing agency practice, Nuss declined to share how many proposals were submitted, although he did say there was significant interest in the announcement. The agency completed its review of any submissions and expects to issue contracts by the end of the fiscal year. Sea Train is expected to consist of two 18-month periods, where contractors will work to develop and test technologies that could enable the Sea Train concept. The program will culminate with model testing in scaled ocean conditions. If successful, DARPA hopes to see the technologies adopted by the Navy for its unmanned platforms. “What we're looking to do is be able to reduce the risk in this unique deployment approach,” Ness said. “And then be able to just deliver that set of solutions to the Navy in the future, to be able to demonstrate to them that there is, potentially, a new way to deploy these vessels, to be able to provide far more operational range without the risk of relying on actual refueling or in-port refueling.” And while DARPA's effort is focused on medium-sized unmanned vessels — anywhere from 12 to 50 meters in length — the lessons learned could be applied to larger or smaller vessels, manned or unmanned. https://www.c4isrnet.com/unmanned/2020/06/01/all-aboard-the-sea-train/