Publication

This is the final report of the Systems Engineering Research Center (SERC) research task RT-141 that finalizes the related tasks under RT-48/118. These RTs focused on a Vision held by NAVAIR’s leadership to assess the technical feasibility of a radical transformation through a more holistic model-centric engineering approach. The expected capability of such an approach would enable mission-based analysis and engineering that reduces the typical time by at least 25 percent from what is achieved today for large-scale air vehicle systems. The effort investigates the technical feasibility of moving to a “complete” model-centric lifecycle and includes four overarching and related tasks as shown in Figure 1. These tasks include:

•  Task 1: Surveying Industry, Government and Academia to understand the state-of the-art of a holistic approach to model-centric engineering (“everything digital”)
• Task 2: Develop a common lexicon for things related to models, including model types, levels, uses, representation, visualizations, etc.
• Task 3: Model the “Vision,” but also relate it to the “As Is” and Airworthiness processes
• Task 4: Integrate a Risk Management framework with the Vision

There has been considerable emphasis on understanding the state-of-the-art through discussions with industry, government and academia. We have conducted over 29 discussions, including 21 on site, and 15 working sessions, as well as several follow-up discussions on some of the identified challenge areas. We did not do a survey, but rather had open-ended discussions. We asked the meeting coordinators to in general:

Tell us about the most advanced and holistic approach to model-centric engineering you use or have seen used.

The spectrum of information was very broad; there really is no good way to make a comparison. In addition, we had proprietary information agreements with most industry organizations. The objective was not to single out any specific organization, therefore, we will summarize, in the aggregate, what we heard in this report as it relates to the NAVAIR research objective.

Our research suggests that model-centric engineering is in use and adoption seems to be accelerating. Model-centric engineering can be characterized as an overarching digital engineering approach that integrates different model types with simulations, surrogates, systems and components at different levels of abstraction and fidelity across disciplines throughout the lifecycle. Industry is trending towards more integration of computational capabilities, models, software, hardware, platforms, and humans-in-the-loop. The integrated perspectives provide cross-domain views for rapid system level analysis allowing engineers from various disciplines using dynamic models and surrogates to support continuous and often virtual verification and validation for tradespace decisions in the face of changing mission needs.

Enabling digital technologies are changing how organizations are conceptualizing, architecting, designing, developing, producing, and sustaining systems and systems of systems (SoS). Some use model and simulation environments for customer engagements, as well as design engineering analyses and review sessions. While they do use commercial technologies, most have been innovating and have developed a significant amount of enabling technology – some call it their “secret sauce.” The research findings and recommendations are based on seeing demonstrations and evidence of cross-cutting technologies and methods. Demonstrations have included mission-level simulations that are being integrated with system simulation, digital assets and aircraft products providing cloud-like services enabled by the industrial Internet. There have been demonstrations of 1D, 2D, and 3D modeling and simulations with a wide array of solvers and visualization capabilities. We have also been in an immersive Cave Automated Virtual Environment. We have seen the results of platform-based approaches directly focused on speed-to-market, and more.

The analysis of captured evidence in this research suggests that there is a transition from model-based engineering to model-centric engineering. The advances and availability of high performance computing, capabilities to provide cross-domain and multi-physics model integration, and methods and tools to assess model integrity will support the need for reducing the time to deliver system capabilities. Even sociotechnical computing is enabling new ways to access and more transparently collaborate and share information, and it can be a key contributor to a radical transformation to model-centric engineering.

Findings

The findings conveyed to NAVAIR leadership definitely indicate that it is technically feasible to transform systems engineering at NAVAIR similar to the transformation seen across large organizations in aerospace, automotive, and government. This transformation increases the likelihood of achieving at least 25 percent reduction in acquisition. A summary of the data analysis is presented in a traceability matrix that captured 21 topic-discussion areas summarized in this report. The matrix also provided evidence of traceability to different instances of organizational use and their possible impacts/relationships on characteristics, such as: performance, integrity, affordability, risk, methodologies, and within a single source of technical truth.

A rule of thumb is that the effort/time to get from Milestone A to Critical Design Review (CDR) is about 30 percent of the total time, where the time from CDR to Initial Operating Capability (IOC) is about 70 percent of the total time. With some of the new approaches to produce digital information, which considers modeling and simulation analysis of manufacturability prior to CDR, the digital information at CDR could significantly reduce the 70 percent effort from CDR to IOC, which also builds to the argument for being able to reduce the acquisition time by 25 percent with MCE.

The feasibility of Systems Engineering transformation through MCE has three key critical technical items: 1) cross-domain and multi-physics model integration, 2) ensuring model integrity (trust in the model predictions), and 3) high performance computing, which is an enabler for 1 and 2, but critical due to the scale and complexity of next generation systems.

There are a number of examples that span various domains across aerospace, automotive, and involving commercial, government and academic organizations. Many have lessons learned and examples covering a number of themes spanning technologies, methods, and usage at various stages of the lifecycle, even taking into consideration constraints for manufacturability in design-space exploration. Therefore MCE is not necessarily the catalyst; rather it is enabled by approaches that support data-driven decision-making that will subsume processes through:

• Single Source of Technical Truth (SSTT) – one source of information
• Views and viewpoints for the multidisciplinary stakeholders into the SSTT
• Multidisciplinary Design, Analysis and Optimization (MDAO) in both tradespace exploration and analysis of the problem and design space
• Workflow orchestration – by having the data dependencies being semantically linked within the SSTT
• Enabled by High Performance Computing (HPC)

Recommendation

NAVAIR senior leadership confirmed that the research finding and analysis have validated their vision hypothesis stated at the System Engineering Transformation kickoff meeting of RT-48. They conclude that NAVAIR must move quickly to keep pace with the other organizations that have adopted MCE and who continue to evolve at an accelerating pace enabled by the advances in technologies and improved methods. NAVAIR must also transform in order to continue to perform effective oversight of weapon system development by primes that are using modern modeling methods for system development. The risks of not moving forward include making acquisition decisions with progressively less technical-truth insight and the proliferation of disparate, redundant and stove-piped data and models, and lacking MCE capabilities and knowledge needed to understand an increasingly complex problem and design space.

The path forward has challenges but also many opportunities, both technical and sociotechnical. It must include a modeling framework with HPC that enables SSTT, integration of multi-domain and multi-physics models, and provides for a method for model integrity. The modeling and infrastructure for a digital engineering environment is a critical step to enable a SSTT. While there are literally thousands of tools, they are often federated and there is no one single solution that can be purchased. Every organization providing inputs to this research has had to architect and engineer their model-centric engineering environment, most have selected commercial tools and have developed the integrating fabric between the different tools, models, and data. This approach often uniquely positions them with some advantages among the rest. Some organizations have encoded historical knowledge in reference models, model patterns to embed methodological guidance to support continuous orchestration of analysis through new modeling metrics, automated workflow, and more. The items to investigate further include but are not limited to:

• Cross-domain integration of models to address the heterogeneity of the various tools and environments
• Model integrity to ensure trust in the model predictions by understanding and quantifying margins and uncertainty
• Modeling methodologies that can embed demonstrated best practices and provide computational technologies for real-time training within digital engineering environments
• Multidisciplinary System Engineering transformation roadmap that looks across:
• Technologies and their evolution
• How people interact through digitally enabled technologies and new needed competencies
• How methodologies enabled by technologies change and subsume processes
• How acquisition organizations and industry operate in a digital engineering environment throughout the phases of the lifecycle (including operations and sustainment)
• Governance within this new digital and continually adapting environment

This report aggregates information contained in the final technical reports of RT-48 and RT-118 so that readers can get the key information from this report. The report is structured so that the key findings and next steps are described in the first section. The report then provides updated clarification on the scope given by our NAVAIR sponsor. Part II section provide additional detail to summarize the efforts that are aligned with tasks 1 through 4.