Optimizing Facility Health Using System Digital Twins

This research focuses on NASA STTR research topic T11.05: Model-Based Enterprise and creates digital models or twins of the facility enterprise to enable high-complexity decision-making in support of mission, programmatic development, digital transformation, and institutional activities. This model will be capable of: 1. Identifying an optimal sequence of investments for systems in facilities. 2. Scaling to make enterprise-wide recommendations throughout the entire facility inventory. The primary innovation in this proposal is to extend the detail of the current state of the art in relation to facility management optimization model scope (all facilities in the enterprise), below facility-level to system-level detail (all systems in each facility). Team ITA proposes a model-based systems engineering mathematical optimization to recommend best-value use of funds to maximize condition of facilities across the facility enterprise. This model will support resource planning, budget allocation, and work planning for facility managers at the NASA Office of Strategic Infrastructure, Center, and Site levels. Mission Relevancy Tier will provide a priority lens for evaluating investments, but other priorities can be considered, such as facilities/systems aligned to Mission Directorates or functions like space launch or laboratories. Deliverables: Degradation models to estimate the effect of time on facility and system condition. Investment response and cost estimation models to estimate the effect of investment on facility and system condition. A scalable facilities investment optimization model to recommend investments over time, incorporating Mission Relevancy Tier and other relevant, mission-driven, priority frameworks. An operational facilities investment optimization model to generate complete prioritized recommendations for investment to available maintenance actions for all facilities and systems across the NASA facility enterprise over a long-range time horizon. The primary innovation in this proposal is to extend the detail of the current state of the art in relation to facility management optimization model scope (all facilities in the enterprise), below facility-level to system-level detail (all systems in each facility). Team ITA proposes an enterprise-wide scope, model-based systems engineering digital twin solution to leverage mathematical optimization to recommend best-value use of available funds at system-level detail to maximize condition of facilities across the NASA facility enterprise. This mathematical optimization model will provide decision support for resource planning, budget allocation, and work planning for facility managers at the NASA Office of Strategic Infrastructure, Center, and Site levels. Best-value solutions will consider Mission Relevancy Tier as a primary lens to evaluate priorities for investments. The model will also be able to consider other priority frameworks, such as facilities and systems aligned to NASA Mission Directorates or functions of interest like space launch, laboratories, or fabrication. Objectives. This research is focused on the NASA STTR research subtopic “T11.05: Model-Based Enterprise” and creates digital models or twins of NASA’s facility enterprise to enable high-complexity decision-making in support of NASA’s mission, programmatic development, digital transformation, and institutional activities. This model will be capable of: 1. Identifying an optimal sequence of investments for systems in facilities. 2. Scaling to make enterprise-wide recommendations throughout the entire facility inventory. 3. Identifying macro-level systemic issues throughout the entire facility inventory.   Deliverables: Degradation models to estimate the effect of time on facility and system condition. Investment response and cost estimation models to estimate the effect of investment on facility and system condition. A scalable facilities investment optimization model to recommend investments over time, incorporating Mission Relevancy Tier and other relevant, mission-driven, priority frameworks. An operational facilities investment optimization model to generate complete prioritized recommendations for investment to available maintenance actions for all facilities and systems across the NASA facility enterprise over a long-range time horizon. An appropriate set of indicator metrics, including detailed calculations, to identify macro-level systemic issues.

Facility optimization supports: -optimizing use of funding by recommending maintenance actions (e.g., maintain, renew) over time at system-level in the NASA enterprise to maximize facility condition. -quantifying funding requirements to achieve specified facility condition. -projecting performance measure status over time, given a set of recommended or alternative actions. -generating facility maintenance plans at system-level across the enterprise. -evaluating the effect of changes to funding during NASA-wide budget development. Facility optimization supports: -allocating budget by recommending system-level maintenance actions over time across many facilities to maximize condition. -quantifying budget requirements to meet condition requirements. -projecting performance status, given a set of maintenance actions. -generating facility maintenance plans. -evaluating the effect of changes to funding during budget development.

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