The maintenance strategy of the Navy and Marine Corps is transforming from time-based and reactive maintenance to condition-based maintenance. The goals of this transition are to achieve increased asset availability and to lower maintenance costs by decreasing unplanned downtime through optimally planned condition-based scheduling. Recent advances in artificial intelligence and machine learning (AI/ML) have conclusively demonstrated in laboratory testing and field deployments that AI/ML methods of statistical reasoning on machine parameters of vibration, temperature, and current can predict machine maintenance requirements. Current deployment of these predictive capabilities requires significant investments in powerful computational infrastructure, precision sensing, and advanced software analyzing the sensor readings. Todays technology options for each layer in this system are prohibitively expensive for broad deployment of the capability. Given that maintenance cost increases are the fundamental challenge to readiness cited by CNO and other leaders, the path to achieving broadly available machine health, usage, and monitoring (HUM) cannot be implemented on prohibitively expensive hardware that is currently available. The Navy and Marine Corps need a technology integration program that delivers a low-cost, rugged device that allows for precision placement on the physical part of the system most likely to give failure mode indicative readings in order to achieve these HUM outcomes at a fraction of the current market price. The desired technology described in the governments solicitation is a complex integration of four disciplines: Software technology Artificial intelligence/machine learning tailored to provide predictive analytics and structured to host native analytics with easy integration of third-party analytics Hardware technology Low cost and highly miniaturized form factor that is electromagnetically and structurally capable of enduring the stresses of an under-hood vehicle environment Communications technology Compliant with industrial standards for communication (i.e., CAN bus and IEEE 1451) yet carrying data beyond the protocols included fields to now include the results of edge computed health and performance Cybersecurity technology Systematically mounting computation and analytics onto machinery dramatically increases the number processors in a tactical system and will require the extension of a cybersecurity framework to ensure the resultant information can be trusted and verified. Fathom5 proposes that the Phase 1 Base and Phase 1 Option efforts outlined in the following Technical Volume are critical steps to move the Navy and Marine Corps towards an affordable device that can support the maintenance optimization the naval services so urgently need .
Benefit: Fathom5 specializes in Maritime Digital Integration (MDI), a unique blend of operational technology and information technology systems integration coupled with cybersecurity solution development tailored to the challenges of the maritime industry. We provide this capability to the U.S. Navy, the Royal Australian Navy and many commercial shipping customers. The device considered in this program of activity is a merger of the industrial internet of things, maritime systems, cybersecurity, and AI/ML design patterns that aligns perfectly with Fathom5s specialty engineering talent. Therefore, the device and its alignment to Fathom5s existing customer relationships in the commercial market will enable transition of the capability down existing sales and account channels. Specifically, Fathom5 is the MDI partner for over 25% of the worlds commercial container ships. Our industry partners are eagerly and actively looking for solutions that reduce maintenance costs which drops these savings directly to their bottom line. More broadly, Fathom5s commercial shipping customers are not unique in their pursuit of maritime digitization. DNV, one of the leading standards organizations in industry reports, The transition towards digitalization and automation is speeding up in the maritime industry. Digital technologies and solutions are being used to increase competitiveness and enhance operational efficiency. They are also being implemented to spur the industry along the decarbonization path to realize zero emissions from international shipping by mid-century. Due to the many drivers of maritime digitalization the maritime analytics market and the demand for products that feed data into this market will grow from $894.28 million in 2019 to reach $1,833.50 million by 2027. This billion-dollar growth in the macro economy of digital shipping provides a quantitative opportunity for commercialization of the intended device.
Keywords: edge analytics, edge analytics, Artificial Intelligence/Machine Learning, cybersecurity, HUMS, Condition-based maintenance
