N221-031 TITLE: DIGITAL ENGINEERING - Distributed Mission Effectiveness and Readiness Management System

OUSD (R&E) MODERNIZATION PRIORITY: General Warfighting Requirements (GWR)

TECHNOLOGY AREA(S): Information Systems

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.

OBJECTIVE: Develop a distributed mission effectiveness and readiness management system data analytics tool to integrate FFG 62 Model Based Systems Engineering (MBSE) and Model Based Product Support (MBPS) artifacts and/or data to present a mission effectiveness viewpoint of a single FFG 62 ship based on system readiness data.

DESCRIPTION: Within the framework of MBSE, models are developed to support system requirements, design, analysis, verification, and validation activities throughout the lifecycle. MBPS uses the same information along with information on support providers to optimize a platform�s product support footprint, including supply chain, training, and maintenance strategy. MBSE can be leveraged to model fleet-wide effectiveness for performing missions based on technical performance characteristics, and MBPS can be leveraged to model the effectiveness of the product support footprint in supporting these missions, but the two are not often linked to optimize the decision space for the fleet. The Navy is modernizing its MBSE and MBPS toolkits, but current MBSE models do not accurately correlate product suitability data, system architecture, and Condition Based Maintenance (CBM+) data with overall mission effectiveness.

PEO USC platforms are built as an integrated System of Systems (SoS), usually comprising both Contractor Furnished Equipment (CFE) and Government Furnished Equipment (GFE) systems to deliver a complete platform architecture. PEO USC seeks to develop a methodology and a data analytics tool for analyzing, modeling, and optimizing our mission support capabilities in a proactive and predictive manner that could extend to unmanned integration or strike group operations. The solutions will facilitate performance predictions against platform mission needs of this diverse SoS architecture from an end-to-end perspective. The solution would result in a data-driven decision-making tool for FFG 62 sustainment and readiness planning, linking reliability, maintainability, and availability data with overall platform mission effectiveness and informing program Sustainment Key Performance Parameters (KPPs). The data analytics tool will aggregate MBSE data from disparate models and ontological structures to provide a platform-level view of the FFG 62�s ability to meet its required missions in context of both own-ship and strike group ops.

Proposed concepts should address the ability to perform multi-platform-level and multi-mission analysis based on operational data, platform design, architecture, reliability, maintainability, and supply chain inputs. The tool should be able to handle complex functional redundancies at the platform and strike group level and provide outputs that support Program Office sustainment decisions for product support footprint, including maintenance and supply across multiple programs. Effective solutions would analyze data associated with individual systems and generate a model to predict overall performance. This would inform Program Offices early in the acquisition cycle regarding potential performance of the platform design, and also support the decision-making process to evaluate proposed system changes. Approaches could be based on commercial SoS and Quality of Service algorithms to predict system performance, human factors analysis for usability, and dynamic systems modeling techniques. Additionally, the tool should provide information on algorithms to analyze resource decisions across multiple platforms. The tool should also interface with existing Navy CBM+ suites to perform real-time tracking and analysis of platform effectiveness. The algorithms and tools would be verified and tested at the end of each phase of the project by Government Subject Matter Experts for adequate SoS modeling through failure modeling, probability of successful mission estimation, and Monte Carlo simulation.

Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. Owned and Operated with no Foreign Influence as defined by DOD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Counterintelligence Security Agency (DCSA), formerly the Defense Security Service (DSS). The selected contractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances, in order to perform on advanced phases of this contract as set forth by DCSA and NAVSEA in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advance phases of this contract.

All DoD Information Systems (IS) and Platform Information Technology (PIT) systems will be categorized in accordance with Committee on National Security Systems Instruction (CNSSI) 1253, implemented using a corresponding set of security controls from National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53, and evaluated using assessment procedures from NIST SP 800-53A and DoD-specific (KS) at https://rmfks.osd.mil (Information Assurance Technical Authority (IATA) Standards and Tools at https://software.forge.mil/sf/projects/navy-iata).

The Contractor shall support the Assessment and Authorization (A&A) of the system. The Contractor shall support the government�s efforts to obtain an Authorization to Operate (ATO) in accordance with DoDI 8500.01 Cybersecurity, DoDI 8510.01 Risk Management Framework (RMF) for DoD Information Technology (IT), NIST SP 800-53, NAVSEA 9400.2-M (October 2016), and business rules set by the NAVSEA Echelon II and the Functional Authorizing Official (FAO). The Contractor shall design the tool to their proposed RMF Security Controls necessary to obtain A&A. The Contractor shall provide technical support and design material for RMF assessment and authorization in accordance with NAVSEA Instruction 9400.2-M by delivering OQE and documentation to support assessment and authorization package development.

Contractor Information Systems Security Requirements. The Contractor shall implement the security requirements set forth in the clause entitled DFARS 252.204-7012, "Safeguarding Covered Defense Information and Cyber Incident Reporting," and National Institute of Standards and Technology (NIST) Special Publication 800-171.

PHASE I: Develop a concept that can meet the design constraints listed in the Description section. Establish feasibility by developing models that show the system architecture and operational concept of the tool. Feasibility will also be established by computer-based simulations that show the tool�s capabilities are suitable for the project needs. Example inputs for Phase I include system-of-systems diagrams in XML, reliability, maintainability, and cost information associated with the systems, and notional mission profiles as they apply to the systems. The output concept should link the inputs in an architecture that displays platform systems design characteristics and information on required functionality for mission effectiveness. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II.

PHASE II: Based on the results of Phase I and the Phase II Statement of Work (SOW), the company will develop, demonstrate, and deliver a comprehensive modeling tool prototype that can perform platform-level mission analysis based on system design, system architecture, and mission engineering concepts linking reliability, maintainability, and supply chain inputs. The tool should provide outputs that support program acquisition and sustainment decisions for product support logistics footprint, including maintenance and supply. The prototype solution shall be based on a data architecture that establishes relationships between individual systems, associated design characteristics, acquisition cost, and sustainment footprint. Evaluate the tool�s effectiveness in linking disjointed and disparate data sources into a cohesive model for evaluation and its ability of the model to support decision-making and �what-if� analysis to determine whether the models meet performance goals as defined. Demonstrate the tool�s performance through prototype testing and detailed analysis, including mission thread analysis and failure mode analysis with verification through Monte Carlo simulations. Prepare a Phase III development plan to transition the technology to Navy use.

It is probable that the work under this effort will be classified under Phase II (see Description section for details).

PHASE III DUAL USE APPLICATIONS: Support the Navy to transition the multi-platform, multi-mission modeling capability tool from stand-alone application to application integrated with Department of Navy and PMS 515 MBSE and MBPS efforts, including CBM+ systems. Assist with integration aboard fielded platforms for real time analysis of mission effectiveness to support decision makers in the fleet. Program offices and Navy Type Commanders (TYCOMs) can use the tool to better understand impacts of lack of resources or to support reallocation of resources, or resources or assess to probability of mission success in a highly complex environment. Commercial applications of the tool would include other multi-use and/or multi-nodal systems, including air, ground, and maritime vehicles, computing infrastructure, and other uses where optimizing operational time across a wide array of assets is beneficial.

REFERENCES:

1. Madni, A.M., Madni, C.C., and Lucero, S.D. "Leveraging Digital Twin Technology in Model-Based Systems Engineering." Systems 2019, 7, 7. https://doi.org/10.3390/systems7010007.
2. Bickford, Jason, et al. "Operationalizing digital twins through model-based systems engineering methods." Systems Engineering 23.6 (2020): 724-750. https://onlinelibrary.wiley.com/doi/abs/10.1002/sys.21559.
3. Crane, Jeremiah, et al. "MBSE for sustainment: A case study of the air force launch and test range system (LTRS)." AIAA SPACE and Astronautics Forum and Exposition. 2017. https://arc.aiaa.org/doi/pdf/10.2514/6.2017-5302.
4. Beery, Paul, and Eugene Paulo. "Application of model-based systems engineering concepts to support mission engineering." Systems 7.3 (2019): 44. https://www.mdpi.com/2079-8954/7/3/44.

KEYWORDS: Model Based Systems Engineering; Model Based Product Support; Mission Engineering; Operational Availability; Readiness, Sustainment; Product Support; Distributed; Mission Effectiveness; System Optimization