Abstract
Model-based systems engineering (MBSE) plays an increasingly important role in the development of complex systems. Currently, systems architecture models (e.g., descriptive SysML models) have focused more on depicting machine interactions with little consideration for human characteristics that are needed to make holistic architectural decisions. This chapter describes a human system integration (HSI) extension which facilitates integration of system architecture models with human task models. This integration allows tighter coupling between system architecture and analysis with a human agent. It also presents an ontology broker for tool integration. The ontology broker supports information scalability captured in the modeling ecosystem when making architectural decisions. A case study of an unmanned aerial system and an image analyst assesses whether architectural decisions resulting from tighter integration can improve the human-system performance. The results of the study show that architectural changes made and subsequent analysis of the human-system performance produce superior analysis by reducing analyst workload, eliminating bottlenecks, and achieving overall improvement in how the human analyst interacts with the system.
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Orellana, D.W. (2022). Improving System Architecture Decisions by Integrating Human System Integration Extensions into Model-Based Systems Engineering. In: Madni, A.M., Augustine, N., Sievers, M. (eds) Handbook of Model-Based Systems Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-27486-3_27-1
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