Informing System Design Using Human Performance Modeling

Michael Watson, Christina Rusnock, Michael Miller and John Colombi

Systems Engineering, 2017, vol. 20, issue 2, 173-187

Abstract: Humans play a key role in the operation and support of most systems and model‐based systems engineering (MBSE) offers new opportunities to properly consider human capabilities and involvement. This research presents an approach for systems engineers to integrate system models with human performance modeling for early and more effective system design. Unlike analyses using traditional physics‐based models found in most extant MBSE literature, adjusting system parameters for human‐based analyses can greatly impact the design of the system itself. Adjusting a human‐system parameter can lead to design implications including adjustments to task allocation, process and workflow, and interface design. To demonstrate this, a quantitative case‐study approach is used. Starting with a set of Systems Modeling Language (SysML) diagrams, a task analysis is performed to inform an “as is” model of human performance in the Improved Performance Research Integration Tool (IMPRINT). An alternative IMPRINT model is created with varying design parameters and utilized to perform a trade study. Through the analysis, constraints and assumptions placed on the human are verified and the results of varying automation estimated. With current design emphasis in MBSE and model‐based engineering (MBE), there is great opportunity to emphasize human considerations and integrate human performance analysis.

Date: 2017
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https://doi.org/10.1002/sys.21388

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Persistent link: https://EconPapers.repec.org/RePEc:wly:syseng:v:20:y:2017:i:2:p:173-187

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