AN ABSTRACT OF THE DISSERTATION OF Ryan M. Arlitt for the degree of Doctor of Philosophy in Mechanical Engineering presented on September 11, 2015. Title: Understanding Designer Mental Models to Support Computer Directed Analogical Design. Abstract approved: ______________________________________________________ Robert B. Stone Analysis of alternative concepts has a significant impact on design project outcomes, and yet many design teams fail to consider a significantly broad range of conceptual solutions. Within the realm of conceptual design exists a technique called design by analogy (DBA) – the practice of reapplying old solutions to new problems. DBA mitigates the effort required to generate a large field of candidate concepts by leveraging existing knowledge from a wide variety of domains, making it an attractive approach toward improving design outcomes. Unfortunately, DBA is challenging in the absence of expert knowledge. Designers need computational support in order to effectively identify a large number of high-quality analogical connections across a wide variety of domains. With this challenge in mind, the goal of this dissertation is to improve the body of knowledge regarding computational support for design by analogy. More specifically, this body of work includes five manuscripts. Manuscript 0 presents a review of several function-related design abstractions, including their impacts on education and industry. Manuscript 1 studies analogy retrieval in a novel design context and catalogs the types of abstract similarity (including function) commonly used to form analogies. Manuscript 2 examines a scalable approach to capturing analogy-relevant design knowledge to support large-scale analogy searching. Manuscripts 3 and 4 examine and modify a technique from de novo drug design for quickly indexing and retrieving design analogies. Manuscript 3 examines the domain independence of the technique, and manuscript 4 develops it as a large-scale design analogy search method. The body of work contributes to a greater understanding of (1) the abstractions used by designers during conceptual design, (2) the use of human computation to support conceptual design activities, and (3) large scale solution screening using a variety of mixed design abstractions. This understanding advances the creation of tools that enable designers to consider a wide range of conceptual solutions in spite of lacking domain expertise. ©Copyright by Ryan M. Arlitt September 11, 2015 All Rights Reserved Understanding Designer Mental Models to Support Computer Directed Analogical Design by Ryan M. Arlitt A DISSERTATION submitted to Oregon State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Presented September 11, 2015 Commencement June 2016 Doctor of Philosophy dissertation of Ryan M. Arlitt presented on September 11, 2015 APPROVED: Major Professor, representing Mechanical Engineering Head of the School of Mechanical, Industrial, and Manufacturing Engineering Dean of the Graduate School I understand that my dissertation will become part of the permanent collection of Oregon State University libraries. My signature below authorizes release of my dissertation to any reader upon request. Ryan M. Arlitt, Author ACKNOWLEDGEMENTS The author wishes to express sincere appreciation to all those who provided him with the opportunities and support that contributed to his successes during his graduate studies. You know who you are. CONTRIBUTION OF AUTHORS Dr. Tumer wrote the description of the Function Failure Identification and Propagation framework in manuscript 0. Dr. Sen assisted with experimental design and data collection for manuscript 1. Anthony Nix assisted with data analysis and writing of manuscript 1. Tim Foglesong assisted with an alternate method of analysis for the research presented in manuscript 1, though these efforts did not lead to a publication. Sebastian Immel assisted with programming, task design, data collection, and writing for manuscript 2. Friederich Berthelsdorf assisted with task design, data collection, and writing for manuscript 2. Charlie Manion assisted with graph fragment mining for manuscript 3. Dr. Tumer and Dr. Campbell assisted with planning and writing for manuscript 3. TABLE OF CONTENTS Page Introduction ................................................................................................................... 1 Analogy ..................................................................................................................... 1 Analogy and Abstraction ........................................................................................... 3 How to Read this Dissertation ................................................................................... 4 Manuscript Descriptions by Contribution ................................................................. 5 Relationships Between Manuscripts .......................................................................... 8 Impacts of Function Related Research on Education and Industry ............................ 10 Abstract .................................................................................................................... 11 Historical Context .................................................................................................... 11 Research Outcome: A Design Repository Information Schema ............................. 14 The Functional Basis ............................................................................................ 15 The Component Taxonomy .................................................................................. 21 Matrix Representations ........................................................................................ 23 Impacts of Design Repository Information Schema ............................................ 24 Guidelines and Platform behind transfer to Practice ............................................ 28 Research Outcome: Function Failure Relationship ................................................. 31 Component Level Failures ................................................................................... 31 System Level Failures .......................................................................................... 34 Impacts of Function Failure Research .................................................................. 35 Conclusions ............................................................................................................. 38 Summary .................................................................................................................. 39 TABLE OF CONTENTS (Continued) Page Discovery of Mental Metadata Used for Analogy Formation in Function-Based Design ......................................................................................................................... 41 Abstract .................................................................................................................... 42 Introduction ............................................................................................................. 43 Background .............................................................................................................. 44 Function-Based Design ........................................................................................ 44 Case-Based Reasoning and Design by Analogy .................................................. 45 Representations of Design Knowledge ................................................................ 47 Repositories of Design Knowledge ...................................................................... 48 Research Approach .................................................................................................. 49 Data Collection ..................................................................................................... 50 Interview Transcription ........................................................................................ 52 Chunking .............................................................................................................. 53 Identification of Premises, Questions, and Answers in Interview Transcripts .... 54 Coding of Questions ............................................................................................. 56 Results and Discussion ............................................................................................ 60 Summary of Questions ......................................................................................... 60 Categorizing Types of Analogy ........................................................................... 62 Direction of Reasoning......................................................................................... 64 First Concept ........................................................................................................ 65 Types of Similarity ............................................................................................... 67 Conclusions and Future Work ................................................................................. 69 TABLE OF CONTENTS (Continued) Page The Biology Phenomenon Categorizer: A Human Computation Framework in Support of Biologically Inspired Design .................................................................... 72 Abstract .................................................................................................................... 73 Introduction ............................................................................................................