19 décembre 2018 | International, Sécurité

TechFlow Gets $968M DHS Contract for Explosive Detection Tech Maintenance Support

TechFlow has received a potential five-year, $967.9M contract from the Department of Homeland Security to maintain and provide logistics support for explosive detection systems.

A FedBizOpps notice posted Thursday says the contract covers preventive maintenance; calibration and test equipment; radiation surveys; tools; parts obsolescence; and supply support for detection platforms deployed at airports and other facilities.

Contract work began on Dec. 1 and will continue through Nov. 30, 2023.

The contract seeks to support TSA's mission to reinforce security at airports across the country through maintenance of EDS used to screen checked baggage for explosives.

https://www.govconwire.com/2018/12/techflow-gets-968m-dhs-contract-for-explosive-detection-tech-maintenance-support/

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  • Royal Thai Air Force expands fleet with additional H225M order

    21 septembre 2018 | International, Aérospatial

    Royal Thai Air Force expands fleet with additional H225M order

    Thailand, – Airbus Helicopters has secured an additional order of four H225M (previously known as EC725) multirole utility helicopters from the Royal Thai Air Force (RTAF), as part of the fleet strengthening programme. This follow-on order will bring the RTAF's H225M fleet to 12 units by 2021. Specially equipped with emergency flotation gear, fast roping, cargo sling, search light and electro-optical systems, these four new multirole H225M helicopters will join RTAF's existing fleet of six H225Ms for combat search and rescue missions, search and rescue flights and troop transport operations. The air force will also be receiving two H225Ms from its earlier order, by end of this year. This latest contract will also cover on-site technical support and continuing airworthiness management organisation services, fully supported by Airbus' Thailand team. “The H225Ms have served the Royal Thai Air Force well since the delivery of its first batch in 2015, and we are truly honoured by this renewed order, underscoring their continued trust and confidence in our helicopters and the committed support to their fleet. With its proven versatility, reliability and endurance, we know that the H225 will continue to capably fulfil the most challenging missions. RTAF can count on our Thailand-based customer centre for continued availability of the fleet,” said Philippe Monteux, Head of Southeast Asia and Pacific region. Featuring state-of-the-art electronic instruments and the renowned 4-axis autopilot system, the 11-ton-catergory twin-turbine H225M offers outstanding endurance and fast cruise speed, and may be fitted with various equipment to suit any role. Close to 90 units are in service, achieving 100,700 flight hours to-date. About Airbus Airbus is a global leader in aeronautics, space and related services. In 2017 it generated revenues of € 59 billion restated for IFRS 15 and employed a workforce of around 129,000. Airbus offers the most comprehensive range of passenger airliners from 100 to more than 600 seats. Airbus is also a European leader providing tanker, combat, transport and mission aircraft, as well as one of the world's leading space companies. In helicopters, Airbus provides the most efficient civil and military rotorcraft solutions worldwide. https://www.airbus.com/newsroom/press-releases/en/2018/09/royal-thai-air-force-expands-fleet-with-additional-h225m-order.html

  • Raytheon AI: Fix That Part Before It Breaks

    23 mars 2020 | International, Terrestre, C4ISR

    Raytheon AI: Fix That Part Before It Breaks

    A modern mechanized military lives or dies by maintenance. But what if a computer could warn you when your weapons and vehicles were about to break, so you could fix them before they ever let you down? By SYDNEY J. FREEDBERG JR. WASHINGTON: Raytheon is working with the military on multiple pilot projects for AI-driven predictive maintenance. What's that? Traditionally, military mechanics spend a huge amount of time on what's called preventive maintenance: They carry truckloads of spare parts to war, they consult historical tables of roughly how often certain parts wear out or break down, and they preemptively crack open the access hatches to check those parts on a regular basis. The idea behind predictive maintenance is to feed all that historical data into a machine learning algorithm so it can tell maintainers, vehicle by vehicle and part by part, when something is likely to fail. It's a tremendous technical challenge that requires scanning in years of old handwritten maintenance forms, downloading digital records, and then constantly updating the database. Ideally, you want up-to-the-minute reports on things like engine temperature and suspension stress from diagnostic sensors installed in frontline vehicles. You need to account not only for what kind of equipment you're operating, but how hard it's running for a particular mission and even where in the world it's operating, because environmental conditions like heat, moisture, dust, and sand make a huge difference to wear and tear. And you can't just push out a single software solution and call it done. You have to constantly update your data so the algorithm can continue to learn, evolve, and adapt to different situations. But, Raytheon's Kevin Frazier and Butch Kievenaar told me, artificial intelligence and machine learning have advanced dramatically over just the last five years. Now Raytheon – a long-established defense contractor – is partnered with a flock of niche innovators to make it happen. Currently, they told me, Raytheon is already conducting or about to launch several multi-month pilot projects, seeking to prove the technology's value to the military: For the Army, they're working with a commercial partner on the M2 Bradley Infantry Fighting Vehicle, the mainstay armored troop transport of the heavy combat brigades, and the hulking M88 Hercules, a tracked “armored recovery vehicle” designed to tow broken-down battle tanks back for repair, if necessary under enemy fire. For the V-22 Joint Program Office – which supports the Osprey tiltrotor for the Marines, Air Force Special Operations Command, and now the Navy – they're working on the V-22's collision-avoidance radar, a Raytheon product. And across their customer base, they're looking at ways to do predictive maintenance on the many complex components Raytheon provides for a host of programs. How does this work? Let's hear from Kevin and Butch in their own words (edited for clarity and brevity from a highly technical 50-minute interview): Q: What kinds of problems can this technology help the military solve? Kevin: Right now, maintenance is conducted either on a scheduled timeline or when something breaks. What we are trying to do is replace that one piece because you know it's about to wear out and prevent it from breaking. Butch: One of the biggest things is you've got to understand what mission you're trying to achieve. If I'm trying to answer platform readiness questions, then I have to have certain data that's related to that topic. If I am trying to do supply chain analysis, I'm asking questions about where are critical parts and what size stockages we have to have to reduce turnaround time. So I'm answering a different question, and I'm looking at a different data set. So the key to setting all this up is what you do on the front end with your data to give the data scientists so that we can refine the algorithm appropriately. Q: AI/ML requires a lot of data. Is that data really available for all these different military systems? Kevin: It is. It's in different states. Some vehicles have sensors on them. Some do self-diagnostics. Some of the older equipment, especially the support equipment, doesn't have any sensors on them — but they all have files. They all are in the maintenance system, so the data exists. Data doesn't have to purely digital. It does have to be digitized at some point, but it doesn't necessarily have to start being digital. It could be maintenance logs that are hand-written, or the operator of a particular vehicle does a walk around and does an inspection report, writes that up — that's something that you actually can scan and input. Now we can add so many different types of data that your whole data environment becomes much richer. It helps you get to that algorithm — and then to continue to take in that data and refine that model. You're still recording that data and getting data from both handwritten and digital sources to update your model and tune it, so that you're just that much more accurate. Butch: What we're talking about is discrete algorithms solving for discrete problem sets. You look at the environment, and what the algorithm does is it learns. You keep ingesting data. You can get it a bunch of different ways so your analytical tool continues to learn, continues to refine. I can do a physical download from the vehicle, or scan maintenance records, or get it all fed off of a downloader that automatically feeds to the cloud. It can be as fast as we can automate the process of that piece of equipment feeding information back. For the Army and the Air Force especially, there is sufficient data over the last 15 that pertains to the impacts of combat. And we have it for different environments that you can then use to help train and refine the algorithms that you're using as it learns. Kevin: You have to understand the impacts the environment has on how the vehicle is functioning and what type of a mission you're doing, because that will cause different things to wear out sooner or break sooner. That's what the AI piece does. The small companies that we partner with, who are very good at these algorithms, already do this to some extent in the commercial world. We're trying to bring that to the military. Butch: The really smart data scientists are in a lot of the smaller niche companies that are doing this. We combine their tools with our ability to scale and wrap around the customer's needs. These are not huge challenges that we're talking about trying to solve. It is inside the current technological capability that exists. We have currently several pilot programs right now to demonstrate the use cases, that this capability that actually works. https://breakingdefense.com/2020/03/raytheon-ai-fix-that-part-before-it-breaks

  • Use existing and planned craft for unmanned logistical resupply

    10 juin 2020 | International, Aérospatial

    Use existing and planned craft for unmanned logistical resupply

    By: Wayne Prender and David Phillips To counter expected adversary anti-access/area denial strategies, U.S. naval forces will face significant challenges resupplying dispersed units under emerging distributed operations concepts, particularly in the large geographical distances of the Western Pacific. Future Marine littoral regiments, for example, will require layers of manned and unmanned vessels capable of moving personnel and materiel in decentralized operations to complicate enemy decision-making and targeting. Naval leaders have made clear such decentralized resupply of small, but lethal, expeditionary teams is key to defeating anti-access/area denial threats. With the Department of the Navy already challenged to affordably build and sustain a larger combat fleet, designing, buying and commissioning significant numbers of purpose-built craft solely for this purpose is not ideal. Rather, the Navy should look to adapt fleets of scaled derivative versions of existing or planned naval craft types — particularly those which can be unmanned or optionally manned for specific missions. This option provides the Navy with a greater breadth of capabilities at a more affordable cost. A future fleet of unmanned logistical connectors can leverage existing and planned programs of record. The technology already exists to optionally man or unman such vessels. Appropriately scaled and tailored derivatives of these vessels would conduct logistical cargo missions when required, in addition to performing the existing vital functions the craft already carry out for the fleet. The unmanned logistics fleet would be a necessary adjunct to larger planned manned assets, such as a next-generation light amphibious warship. Naval planners will have to strike a balance between size, capability and affordability. However, even with a lower cost, the vessels must still be large and flexible enough to be capable of performing multiple missions with different payloads. The resulting craft should also be able to reliably operate autonomously over a wide range of environmental conditions at significant distances, have a light logistics footprint and possess sufficient cargo-carrying capacity. Rather than a homogeneous unmanned cargo fleet, the Navy could instead utilize several derivatives of existing vessels it already operates or has planned, which will ease any additional maintenance or training burden. Marines operating in the wide-open spaces of the Western Pacific might, for example, use larger variants capable of hauling cargo over greater distances, while units in other geographic locations are equipped with smaller versions more appropriate for their specific environments. The ability to repurpose multiple craft types would allow a more diverse fleet composition of manned and unmanned vessels teamed for mission-tailored flexibility. Moreover, craft that can accommodate interchangeable payloads would also be available to naval planners for additional missions. For example, the vessels could be equipped with a variety of intelligence, surveillance and reconnaissance sensors to improve fleet situational awareness while also performing the cargo resupply missions. Buying scaled derivatives of existing program craft will bring additional benefits, including cost savings through economies of scale for acquisition, while minimizing any upfront developmental costs, as hull forms, key components and systems largely already exist. Moreover, because much of the basic systems and components will be common, training, maintenance and repair functions can be streamlined, adding yet more savings over the vessels' life cycles. Likewise, the technologies for unmanning and optionally manning are well along in their development, while autonomous behaviors and autonomy technologies developed for other programs can be reused rather than having to be created anew. For example, autonomous behaviors and control technologies developed for unmanned aircraft systems can be leveraged for naval applications, while similar autonomy technologies for unmanned ground vehicles are also progressing. Within the naval domain, experimentation such as Advanced Naval Technology Exercise 2019 and Exercise Citadel Shield-Solid Curtain earlier this year have already demonstrated that unmanned surface vessels can autonomously station keep, navigate around obstacles, protect high-value assets and conduct other necessary core functions. As autonomy technologies further develop, unmanned naval craft of the size and complexity envisioned for logistics and cargo hauling will be able to add new missions and functionality. Longer term, delivery of logistical payloads to Marines on a beachhead can be done completely with unmanned platforms. For example, small to medium robotic ground vehicles loaded with supplies could be carried by one of these unmanned logistical craft. Rather than Marines exposing themselves to hostile fire while unloading supplies on the beach, robotic ground vehicles or aerial drones disembark from the vessels and deliver cargo directly to the Marines in a more secure location. Such vehicles need not be fully autonomous, but rather could be partially autonomous or remotely operated from the security of the protected location. While many details of this concept require further exploration and refinement, conducting experimentation to bring truly multidomain capabilities to bear on the resupply challenge is a worthy endeavor. Getting these and related technologies into the hands of sailors, Marines and other U.S. forces to test and refine will be the quickest and most fruitful way to develop the new concepts and field the necessary capabilities. Wayne Prender and David Phillips are senior vice presidents at Textron Systems. https://www.defensenews.com/opinion/commentary/2020/06/09/use-existing-and-planned-craft-for-unmanned-logistical-resupply/

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