Uncovering Human Errors Associated With System-User Interactions Using Functional Modeling

Abstract

Abstract Designers should adequately develop user considerations such as usability, safety, and comfort during the design process of new systems. Nevertheless, incorporating human factors engineering principles during early design phases is not simple. The objective of this work is to assist designers in implementing human factors engineering principles during early design phases using a functional model framework. This effort expands our previous work on automating the function-human error design method (FHEDM) implementation. In this work, we use data mining techniques in a design repository to explore the construction of association rules between components, functions, flows, and user interactions. Such association rules can support designers assessing user-system interactions during the early design stages. To validate this approach, we compare the associations generated by expert designers using the FHEDM while designing a new product to those generated by an algorithm using the repository data. The results show notable similarities between the associations extracted by the algorithm and the associations identified by designers. Thus, the overall results show that association rules extracted from a rich dataset can be used to distinguish user-product interactions, demonstrating the potential of automating the identification of user-product interactions from a functional model.