Extending the Capabilities of Digital Human Modeling: A Design Framework to Assess Emergencies Early in Design

Abstract

Digital Human Modeling (DHM) brings in the advantages of reducing the time and cost spent on building physical prototypes and minimizing the risk of conducting human-subject data collection in hazardous settings. However, most of the DHM studies focus on evaluating standardized tasks executed in normal or nominal work conditions. There is a limited existing DHM research that focuses on the analysis of high-risk tasks performed during emergencies. This paper introduces a DHM based design framework that focuses on the ergonomics evaluation of high-risk tasks that are required to be performed during an emergency. The research aims to provide a methodology that can be used to measure the effect on the visibility of the controls due to a fire or smoke emergency in a civilian aircraft cockpit. The design framework described in this paper also automates the repetitive task simulations and ergonomic evaluations, which are typically performed manually by the designer. Thus, the automation module saves time and allows the consideration of a large sample set of anthropometries for assessing ergonomic adequacies. The automation framework also brings in the advantage of making the emergency assessments part of the early design ergonomics analysis digitally, which has not been the focus of traditional ergonomics studies.