For N193-A01, Beacon is proposing to develop innovative AI and ML technologies that can predict and prescribe items for resupply within Naval Air Operations. The approach will be to build upon previous successful SBIR transitioned shipboard digital assets. The innovation proposed is to use AI / ML to inform and provide actionable intelligence into the supply chain from the operational point-of-performance; drive logistics from the needs at the flight line not just from acquisition requirements. The intent is to leverage a disparate and innovative data set along with existing products in order to have a more robust AI / ML experience that adds operational visibility to supply chain decision making. The proposed innovative data set embedded in a highly flexible software framework, combining maintenance, equipment, and operating conditions enables more precision in the supply chain.
Benefit: The technology and innovation proposed by Beacon will directly benefit the Navy and other commercial customers by increasing efficiencies throughout the supply chain. Specifically: 1. The need for individual parts, tools and other supply chain elements will be more accurately determined 2. Supply chain and maintainers will be more closely linked, increasing precision of needed materials 3. All parties will have a more holistic view into the drivers of the supply chain because of the more holistic operational data set generated This technology has applicability beyond just Naval Air Operations and the Navy for any industrial customer that has significant operational assets to maintain, such as private shipyards, manufacturing plants, and electric utilities. Beacon also sees a large market in the DoD and Federal government for other areas that have a large, complex and diverse supply chain.
Keywords: Machine Learning, Machine Learning, Logistics, supply chain, Analytics, sustainment, Artificial Intelligence, digital, maintenance