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