Naval aviation continues to experience issues with Cartridge Activated Device/ Propellant Activated Device (CAD/PAD) shortages, obsolescence, lot failures, Diminishing Manufacturing Sources and Material Shortages (DMSMS) and production and shipping delays. Reliability Centered Maintenance (RCM) has proven inefficient for effectively managing the service life of the estimated 2M+ CAD/PAD assets in the existing inventory. Because no as installed health monitoring capability currently exists to indicate performance/useful life, an estimated 70,000 CAD/PAD components are replaced annually to increase the likelihood that these critical safety items will be effective when needed by aircrew and to avoid inadvertent actuations. Understandably, conservative service life limits are established to address substantial uncertainty. A bi product of the conservatism is that many of the components removed prior to expiration are done so with significant effective useful life remaining. The vision of the SBIR proposal is to establish a non-intrusive system of automated analysis tools (digital twins) that deliver near real-time performance/useful life projections (by device serial number) and associated maintenance intervention metrics for the entire CAD/PAD inventory. The Direct to Phase II effort leverages some preliminary F/A-18 ejection seat work already conducted by Lone Star Analysis and focuses on operationalizing the capability through delivery of a secure, web based, enhanced Condition Based Maintenance (CBM) capability that is accessible via the Navys network and is authorized to connect to authoritative Government data sources as required to monitor and predict CAD/PAD service life and performance. The tools developed will facilitate service life adjustment decisions and support optimized inventory management. The following research and development questions will be addressed: - Can a CAD/PAD digital twin be automated that provides accurate measurements and predictions of remaining useful life? - Is the current RCM approach to removing and replacing target CAD/PADs on established service life timelines impacting safety and/or readiness? - Can an automated CAD/PAD digital twin be achieved without adding additional sensors to the aircraft? - How is a CAD/PAD digital twin most effectively integrated with Government authoritative databases? - What protections are required to ensure the web-based digital twins are safe from cyber threats and are authorized to interface with the Government network of record? - How will the Fleet most effectively employ the CAD/PAD digital twin technology to maximize cost avoidances, improve readiness and eliminate unnecessary risk exposure?
Benefit: Preliminary work suggests that adopting a digital twin CBM approach to managing the CAD/PAD program will result in a 58 percent cost savings/avoidance per year ($803,512/year as compared to $1,908,039/year) for the F/A-18A/C MT29 (Parachute Deployment Rocket Motor) and WB15 (Cartridge Actuated Initiator) components. Broadening the scope for those components to the entire F/A-18 fleet (F/A-18D/E/F and EA-18G) results in a 59 percent cost savings/avoidance ($3,638,100/year as compared to $8,858,141/year). The cost comparisons are inclusive of all real-time monitoring costs plus a 30 percent markup to account for unknown costs. It is estimated by NAVAIR CAD/PAD system experts that of the total population of CAD/PADs within the NAVAIR inventory (2,500+), at least 676 device types deserve consideration for the development of digital representations. Direct and indirect costs, operational impacts, safety concerns and inventory status for each of those device types will vary, but expected cost avoidance/savings can be extrapolated using a factor of approximately 50 percent to be more indicative of the real value the US Navy will realize upon full-scale digital twin adoption. Potential Commercial Applications of the Research and Development: Lone Star Analysis is currently delivering digital twins in a web-based environment for a wide variety of asset intensive commercial clients including manufacturing lines, transportation fleets, and oil production platforms. Current major corporation partners for digital twin projects include Accenture, HP, Trinity Industries, and Wipro.
Keywords: cad/pad, cloud, Prescriptive Analytics, Artificial Intelligence, Digital twin, Stochastic modeling, Predictive Analytics, Condition Based Maintenance
