Building credibility for human systems integration in model‐based systems engineering

Abstract Robust and trusted digital human representations are necessary to successfully account for human considerations in model‐based systems engineering (MBSE). Multiple domains and modeling frameworks leverage verification, validation, and accreditation (VV&A) processes to characterize when and under what conditions a model is valid to establish credibility. A literature review was completed on mathematical, physics‐based, software development, discrete event simulation, agent‐based, system dynamics, and MBSE models with the goal of proposing a process for performing VV&A on digital engineering (DE) and MBSE models for sociotechnical systems. However, this research also revealed the need for a broader framework to characterize the risk associated with using these models for making high‐consequence decisions. While accomplishing the literature review, another approach to building credibility was identified that is used heavily in the financial industry, namely model risk management (MRM). This process is extended by leveraging MRM approaches from within the financial community to propose a framework for sociotechnical model users to characterize the risk of using MBSE models to make programmatic decisions. The primary contribution of this work is to document a meta‐analysis of model VV&A while proposing an alternative approach to characterizing and communicating credibility that was discovered during this analysis. This approach could be a viable option for ensuring the credibility of human systems integration in MBSE models.

Authors

Institutions

Publication Details

Journal
Systems Engineering
Published
2024-10-28
DOI
https://doi.org/10.1002/sys.21790
Citations
1
Primary Topic
Systems Engineering Methodologies and Applications
Type
article
Field-Weighted Citation Impact
0.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Building credibility for human systems integration in model‐based systems engineering

Michael E. Miller, Rachel A. Heffner
1 citations
Systems Engineering
Systems Engineering Methodologies and Applications
0.33
article

Building credibility for human systems integration in model‐based systems engineering

Michael E. Miller, Rachel A. Heffner
article en
1 citations

Abstract

Abstract Robust and trusted digital human representations are necessary to successfully account for human considerations in model‐based systems engineering (MBSE). Multiple domains and modeling frameworks leverage verification, validation, and accreditation (VV&A) processes to characterize when and under what conditions a model is valid to establish credibility. A literature review was completed on mathematical, physics‐based, software development, discrete event simulation, agent‐based, system dynamics, and MBSE models with the goal of proposing a process for performing VV&A on digital engineering (DE) and MBSE models for sociotechnical systems. However, this research also revealed the need for a broader framework to characterize the risk associated with using these models for making high‐consequence decisions. While accomplishing the literature review, another approach to building credibility was identified that is used heavily in the financial industry, namely model risk management (MRM). This process is extended by leveraging MRM approaches from within the financial community to propose a framework for sociotechnical model users to characterize the risk of using MBSE models to make programmatic decisions. The primary contribution of this work is to document a meta‐analysis of model VV&A while proposing an alternative approach to characterizing and communicating credibility that was discovered during this analysis. This approach could be a viable option for ensuring the credibility of human systems integration in MBSE models.

Systems EngineeringVol. 28(2)
Wright-Patterson Air Force Base (US), U.S. Air Force Life Cycle Management Center, U.S. Air Force Institute of Technology (US)
Air Force Institute of Technology
Industry, innovation and infrastructure
Openalex Percentile: Top 40%
Systems Engineering Methodologies and Applications
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Building credibility for human systems integration in model‐based systems engineering — Michael E. Miller, Rachel A. Heffner · Systems Engineering (2024) | TGRS Research Map | TGRS