The newest wave of Naval aircraft carriers are implementing novel systems that require fewer Sailors to man, with the goal of improving readiness and reducing operating costs. One new system to the USS Gerald R. Ford is the Machinery Control Monitoring System (MCMS). MCMS is operated by the Combat Systems (CS) Department; specifically, CS 5 – Combat Data System and Tactical Networks Division. MCMS is the Command’s largest and most complex system. MCMS controls over 5,600 field devices from a centralized computer system. Some of the systems controlled by MCMS include all the air conditioning systems throughout the ship. MCMS allows for a modern approach to system monitoring; instead of individual Sailors monitoring individual systems, MCMS can monitor and control thousands of systems and sub-systems, which allows for fewer required Sailors to man the CVN 78. This automated approach provides an opportunity to reduce crews and increase readiness. However, as this system is novel and expansive, Sailors receive little-to-no formalized training in A and C schools (training programs specific to a Sailor’s intended role, or rating) specifically on MCMS systems prior to boarding the CVN 78. Additionally, there are very few MCMS experts onboard the CVN 78. A unique challenge for the reduced-crew environments of the new Ford-class carriers is that with fewer Sailors to man dozens of new systems, journeymen Sailors may be underprepared and lack operational support via on-the-job training for systems with which they have little-to-no previous experience or training. Moreover, expert Sailors have less time available to mentor and coach journeymen Sailors. Thus, there is a need to preserve and disseminate expert knowledge so that journeyman Sailors have access to point-of-need support, even if experts are unavailable or have transitioned. Previous research has used knowledge elicitation, or KE, methodologies to capture subject matter expert (SME) knowledge; however, there are currently few widely adopted tools to support knowledge extraction. The present paper discusses the conceptual design and development of an augmented reality (AR)-based KE tool to capture and disseminate expert knowledge. An overview of AR and a discussion of why this medium was selected to capture subject matter expertise is provided. Additionally, the processes by which the AR KE tool was conceptually designed and developed are discussed. Specifically, the partnership with MCMS Sailors from CS 5 during the agile-development process is described, as is the numerous iterations of prototype testing with these Sailors. Finally, the paper concludes with an overview of the resulting AR-based KE tool and how it can be used to capture and disseminate MCMS expertise, and ultimately all Combat System expertise, to improve overall efficiency and readiness of Combat Systems.

The current challenge is leveraging the terabytes of data generated by deployed, monitored systems to provide actionable information for commanders, maintainers, logisticians, and program managers. The benefits of a cloud-based application performing data transactions, learning and predicting future states from current and past states in real-time, and communicating anticipated states is an appropriate solution to reduce latency and improve confidence in decisions. Decisions made from deep learning and artificial intelligence (AI) application will improve mission success and operational readiness, improving overall cost/effectiveness of any program. These improvements will accelerate process improvements at the Depot Level by filling the information gap between unit-level maintenance and depot-level maintenance efforts for each inducted vehicle or aircraft.
Systecon leverages automation to shorten the time associated with data ingestion and cleansing. Our team offers a flexible ingestion framework leveraging direct upload, Java Script Object Notation (JSON) code, or application programming interface (API) endpoints to analyze, cleanse, and train machine learning (ML) models. The AI consumes multiple data types, structured or unstructured, from any platform without interrupting existing applications, adding hardware to platforms, or requiring complex integration across multiple “silos”.
Systecon’s solution utilizes proprietary, deep ML algorithms, created with the Defense Advanced Research Projects Agency, and leverages Topological Data Analysis to automatically present actionable information via a customized, user-friendly dashboard display. Views are designed to quickly provide the user with critical decision-making information necessary to maintain individual platforms and fleets on a day-to-day basis and through major maintenance events at the Depot level.
The vehicle agnostic algorithms correlate state variables such as kinematic data, system sensor data, external condition variables, and digital behavioral data to infer a system’s current state and digital maintenance information. Systecon’s AI optimizes both sensor-supported equipment and legacy systems absent supporting sensors or the capability to move data off platform. Systecon’s solution identifies the prevailing trends, enabling state prediction at the system/component level. Our platform automates ongoing model tuning, reducing the cost and risk of running ML models long-term, while simultaneously improving their accuracy and performance.
The Systecon team constructs model-based, serialized digital twins across a system’s lifecycle and across logical/operational groupings of systems. This bi-directional data coupling enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations.

Integrating Model-Based Engineering and Agile DevSecOps: An Approach to Modeling and Modernizing Legacy Software Architectures Introduction: The U.S. Government relies on increasingly dated data and Information Technology (IT) systems. The average age of a U.S. military platform is over 25 years. The typical U.S. Federal data system is over 50 years old. These legacy systems are often written in obsolete or unsupported programming languages (e.g., JOVIAL, Ada, CMS-2) for similarly obsolete and/or unsupported platforms (e.g., VAX, MIL-STD-1750A, UYK-44). Moreover, legacy systems are generally developed using immature software development practices that fail to account for current or future cyber vulnerabilities. Despite the challenges identified above, legacy data and IT systems must be maintained to extend their service lives; modernized to satisfy new operational requirements; and transformed into extensible open architectures by exploiting 1) advanced digital and Model Based Engineering (MBE) methods and 2) agile DevSecOps software development and delivery processes.
The Navy is embarked on this journey today as it migrates from a monolithic Aegis code-base to a loosely-coupled, modular and scalable Integrated Combat System (ICS) software architecture. The service’s ability to successfully modernize its Surface Fleet combat system and accelerate development and deployment of new warfighting capabilities is contingent upon successfully integrating MBE and Agile DevSecOps methodologies and practices. This abstract outlines a general approach to IT and data system modernization that the Navy could apply to modernize its combat system software architecture and more rapidly deliver capability to the warfighter.

The Distributed Maritime Operations (DMO) concept will require surface forces to take on new missions and tactics for anti-surface warfare (ASUW) and strike warfare (STW) against targets in ways that reduce the ability of an adversary to quickly target surface combatants or understand the effects kill webs and tactics U.S. forces are executing. The DMO concept is now a focused development effort with the Chief of Naval Operations standing up Project Overmatch ; “goal is to enable a Navy that swarms the sea, delivering synchronized lethal and non-lethal effect from near-and-far, every axis, and every domain”. Significant advancements in Information Technology (e.g. Cloud computing, 5G), speed of Combat Systems development (e.g. DevSecOps) and DARPA project investments (e.g. Mosaic Warfare ) provide the means necessary to achieve these objectives. This is the backdrop to develop disruptive DMO warfighting capabilities to achieve overmatch in a near-peer competition. The U.S. Navy (USN), via the Surface Capability Evolution Plan, has identified the need to attain an Integrated Combat System (ICS) within the coming decades. Lockheed Martin (LM) is partnered with the USN to evolve the ICS to support DMO, JADC2, and continuously deliver increased lethality across the Fleet. Achieving the tenets of the ICS model requires bridging the gaps between land, maritime, and air components of the common operational picture and the ability for rapid coordination of offensive and defensive kill webs. In support of the USN ICS model, the LM team has leveraged proven Aegis software architecture to minimize traditional combat system hardware to a single-server, virtualized C2 node, or Virtualized Aegis Weapon System (VAWS). Aegis is a true multi-domain combat system that will have a central role in the evolution of an integrated force and enabling Joint All Domain Operations (JADO). U.S. INDOPACOM invited LM to demonstrate technological developments towards an ICS during Valiant Shield 2020 (VS20), a biennial, joint-force exercise that takes place in the Indo-Pacific theater. VS20 focused on designing, building and experimenting a distributed, joint-force architecture to maintain maritime superiority in the Indo-Pacific theater as part of the “Regain the Advantage” strategy. From September 14-23, a cross-functional LM team of engineers, operations analysts, and strategists participated from the Multi-Domain Task Force (Andersen Air Force Base, Guam) and the Multi-Domain Operations Center (Joint Base Pearl Harbor-Hickam, Honolulu, HI). This paper describes the modernization efforts and lessons learned from participating in U.S. INDOPACOM’s VS20 exercise as it relates to the following topics:

• Building a distributed network of VAWS C2 nodes to assist the warfighter in coordinating digital force orders
• Leveraging existing Aegis Common Source Library (CSL) software architecture to integrate platforms and enable cross-domain kill webs – making in-stride SW fixes via DevSecOps
• Analyzing the benefit of JADO on operational agility and resource planning In conclusion, Aegis is a multi-domain weapon system enabling joint all domain operations (JADO). Experiments such as Valiant Shield are an effective way to integrate and test JADO across services.