{"id":1144585,"date":"2021-10-10T02:23:20","date_gmt":"2021-10-10T06:23:20","guid":{"rendered":"https:\/\/www.smart-industry.net\/?p=11553"},"modified":"2021-10-10T02:23:20","modified_gmt":"2021-10-10T06:23:20","slug":"arc-is-pioneering-predictive-maintenance-sensors-for-u-s-marines","status":"publish","type":"station","link":"https:\/\/platodata.io\/plato-data\/arc-is-pioneering-predictive-maintenance-sensors-for-u-s-marines\/","title":{"rendered":"ARC is Pioneering Predictive Maintenance Sensors for U.S. Marines"},"content":{"rendered":"\n
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Armaments Research Company, Inc.<\/a> (ARC) has announced its plans to develop a predictive maintenance platform for crew-served weapons for the U.S. Marine Corps.Maintenance Sensors for U.S. Marines<\/span><\/p>\n

This project is part of ARC\u2019s recently awarded 5-year, $60-million Small Business Innovative Research (SBIR) Phase III contract with the U.S. Department of Defense (DoD) and General Services Administration (GSA) to develop systems for the military\u2019s \u2018Joint All-Domain Command and Control\u2019 (JADC2) project portfolio. JADC2\u2019s goal is to connect sensors from each military service into one, integrated network.
Last month, ARC introduced Task Orders 1 and 3, the first projects to be delivered under the \u2018Indefinite Delivery, Indefinite Quantity\u2019 (IDIQ) contract. These projects focus on fusing data from ARC\u2019s miniaturized AI-enabled edge computing sensors with other battlefield data sources, transmitting decision-quality information to tactical forces through mobile and extended reality (XR) platforms.
Given the importance of functioning, well-maintained weapons systems on the battlefield, ARC\u2019s latest project expands the development of its AI\/ML-powered weapons sensor\u2014the ARC-Response (ARC-R)\u2014from small- to medium-caliber weapons platforms. This capability enables predictive maintenance and optimizes unit readiness. The project empowers units to predict, plan, and take proactive steps for events such as parts repair or failure before they occur, ensuring reliability and safety during training and operations.
ARC will adapt its state-of-the art, Internet-of-Things (IoT) sensor to transparently embed into crew-served weapons platforms to collect, synthesize, and communicate diagnostics for units to assess the overall health of their platforms. The data will be used to develop machine-learning<\/a> (ML) algorithms that detect when a component of the weapon may fail or when the weapon system requires maintenance.
These insights allow commanders to take decisive action with timely, accurate information about the utilization rates of their weapons systems, 1) significantly reducing unscheduled weapons maintenance, 2) extending the lifetime of the weapon and 3) creating cost saving through supply chain optimization.
Michael Canty, Chief Executive Officer of ARC, said: <\/p>\n

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Supporting the Marines\u2019 leap forward from time- to conditions-based maintenance for their medium-caliber weapons creates extraordinary potential for efficiencies. This project is particularly exciting because we have the opportunity to understand and help better predict non-age-related equipment issues, which typically comprise 80% of total failures. Ultimately, a properly functioning weapon can be a Marine or Soldier\u2019s lifeline in combat and reliability matters; our team is thrilled to contribute.<\/p>\n<\/blockquote>\n

Author: Tim ColeMaintenance Sensors for U.S. Marines<\/span>
Image Credit: PixabayMaintenance Sensors for U.S. Marines<\/span><\/p>\n<\/p><\/div>\n

Source: https:\/\/www.smart-industry.net\/arc-is-pioneering-predictive-maintenance-sensors-for-u-s-marines\/<\/a><\/p>\n","protected":false},"author":1,"featured_media":1144586,"template":"","meta":{"_eb_attr":"","type":"","auto_type":false,"post":"","stream":"","stream_url":"","waveform_data":[],"duration":0,"start":0,"end":0,"bpm":0,"downloadable":false,"download_url":"","purchase_title":"","purchase_url":"","post-count-all":0,"like_count":0,"download_count":0,"editor_note":"","copyright":"","captions":[],"sources":[]},"genre":[42484],"station_tag":[4042,4044,4722,4838,6337,4053,3688,4607,3830,5619,5256,4376,4152,3892,3642,5791,5621,6316,4248,3938,44527,5404,7460,5503,3796,4171,5659,15333,4308,3772,4068,4614,4072,5318,3650,3908,9771,4080,4194,3701,3703,4202,5203,4093,3961,3742,3707,4100,3661,4355,3663,3861,3862,3968,4020,3743,4217,7525,4546,3710,4828,4624,28137,3975,4548,5305,4226,4227,4124,4125,43835,7291,3981,14481],"artist":[45681],"mood":[],"activity":[],"_links":{"self":[{"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/station\/1144585"}],"collection":[{"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/station"}],"about":[{"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/types\/station"}],"author":[{"embeddable":true,"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/users\/1"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/platodata.io\/wp-json\/"}],"wp:attachment":[{"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/media?parent=1144585"}],"wp:term":[{"taxonomy":"genre","embeddable":true,"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/genre?post=1144585"},{"taxonomy":"station_tag","embeddable":true,"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/station_tag?post=1144585"},{"taxonomy":"artist","embeddable":true,"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/artist?post=1144585"},{"taxonomy":"mood","embeddable":true,"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/mood?post=1144585"},{"taxonomy":"activity","embeddable":true,"href":"https:\/\/platodata.io\/wp-json\/wp\/v2\/activity?post=1144585"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}