A taxonomy of metrics for human representations in digital engineering

Abstract As humans play a significant role in maintaining, supporting, and operating systems, it is important to include digital engineering models ensure that the sociotechnical system capable of meeting stakeholder requirements. The current research proposes taxonomy metrics taxonomic nomenclature useful for representing systems integration. This intended provide structure considering frameworks such as Objectives Metrics portion human view architecture, well trade studies which may be represented MBSE models. proposed categorizes human‐centered into four categories, including those affecting performance, readiness, interface fitness, occupational health safety. It further recognized many these can affected by mental or physical state human, are commonly captured factors metrics, workload situation awareness. this guide selection affect system's ability meet