Graduate Thesis Or Dissertation


The Function-Human Error Design Method (FHEDM) Public Deposited

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  • This research presents a methodology to identify and analyze human-system interactions, and their potential failure modes using a functional decomposition approach during the early system design stage. The fundamental research contribution of this work is the development of a framework to identify associations between physical user-product interactions, generic human errors using a functional model framework. Providing designers with such associations will allow the integration of Human Factors Engineering (HFE) principles early in the design process to assess user-system interactions by identifying possible human error scenarios and component failures. This methodology can also be used to improve design engineering methods, by explicitly refining the user considerations and providing design guidelines to enhance the usability, safety, and comfort of the user while operating the engineered system. This dissertation begins by examining the current state of design methodologies and HFE approaches, highlighting the research opportunities that exist to include human factors engineering assessment of user-system interactions during the concept generation stage. The dissertation is composed of three manuscripts which aim to develop such opportunities to support designers by identifying and mitigating failure modes caused by physical user-system interactions. The first manuscript introduces the components of Function-Human Error Design Method (FHEDM). First, we build the human error database, which categorizes human errors associated with user-system physical interactions — allowing designers to identify user errors while completing tasks within the system. Additionally, we present a method capable of mapping user-system physical interactions and their possible human errors within a functional model framework. The second manuscript explores the FHEDM associations between the Functional Basis and User Tasks, and the inherent associations between Human Error and physical User Tasks. It also provides a validation study by examining the associations established by Subject Matter Experts (SME) using the FHEDM. The differences found in this study allowed us to develop a preliminary set of associations that support and expand our perspective of physical user-system interactions. Finally, the third manuscript examines the use of data mining techniques to develop relationships between component, functions, flows, and user interactions using design data extracted from a Design Repository. The preliminary results of the case study suggest that design information from a rich dataset can be used for extracting association rules between functions, flows, components, and user interactions. This work contributes to the design community by automating the identification of user interactions and potential human errors from a single functional model. The research presented in this dissertation constructs a human-centered design methodology, validates the methodology, and builds the first steps towards automating a design tool to guide designers to new insights into the integration of Human Factors Engineering (HFE) principles early in the design process.
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