Fundamental studies in Design-by-Analogy: A focus on domain-knowledge experts and applications to transactional design problems

2014 ◽  
Vol 35 (3) ◽  
pp. 232-272 ◽  
Author(s):  
Diana P. Moreno ◽  
Alberto A. Hernández ◽  
Maria C. Yang ◽  
Kevin N. Otto ◽  
Katja Hölttä-Otto ◽  
...  
Keyword(s):  
Domain Knowledge ◽  
Design Problems ◽  
Design By Analogy

Modality and representation in analogy

2008 ◽  
Vol 22 (2) ◽  
pp. 85-100 ◽  
Author(s):  
J.S. Linsey ◽  
K.L. Wood ◽  
A.B. Markman
Keyword(s):  
Prior Knowledge ◽  
English Language ◽  
Functional Model ◽  
Cognitive Mechanisms ◽  
Support Design ◽  
Design Problems ◽  
Functional Models ◽  
Current Design ◽  
Design By Analogy ◽  
General Semantic

AbstractDesign by analogy is a powerful part of the design process across the wide variety of modalities used by designers such as linguistic descriptions, sketches, and diagrams. We need tools to support people's ability to find and use analogies. A deeper understanding of the cognitive mechanisms underlying design and analogy is a crucial step in developing these tools. This paper presents an experiment that explores the effects of representation within the modality of sketching, the effects of functional models, and the retrieval and use of analogies. We find that the level of abstraction for the representation of prior knowledge and the representation of a current design problem both affect people's ability to retrieve and use analogous solutions. A general semantic description in memory facilitates retrieval of that prior knowledge. The ability to find and use an analogy is also facilitated by having an appropriate functional model of the problem. These studies result in a number of important implications for the development of tools to support design by analogy. Foremost among these implications is the ability to provide multiple representations of design problems by which designers may reason across, where the verb construct in the English language is a preferred mode for these representations.

Dimensions of Product Similarity in Design by Analogy: An Exploratory Study

2019 ◽  
Author(s):  
Amaninder Singh Gill ◽  
Arnold N. Tsoka ◽  
Chiradeep Sen
Keyword(s):  
Material Flow ◽  
Energy Flow ◽  
User Study ◽  
Design Problems ◽  
Five Dimensions ◽  
Multiple Dimensions ◽  
Computational Support ◽  
Mechanical Products ◽  
Student Volunteers ◽  
Design By Analogy

Abstract This paper explores dimensions of similarity in analogy-based design through a user study. Analogy is used in design to help designers use knowledge that exists between and across domains in order to solve design problems at hand. The five dimensions of similarity that were explored in this paper are: function, form, energy flow, material flow, and motion. Fifty student volunteers, majoring in Mechanical Engineering, were given electro-mechanical products that are to be designed, and were asked to select, from a set of options, other products that they considered could be useful references for their task, if those options were offered by a hypothetical design-by-analogy web-service. In their response, they were also asked to identify the dimensions along which they found their preferred reference products to be similar to the design product. It was observed that participants selected products based on similarity along multiple dimensions of analogy. Function-based similarity was the most dominant trait, followed by energy, motion, material, and form. The results from this study will help to design more elaborate studies that will inform the design of computational support algorithms that will aid designers by recommending analogous solutions to help with solution search and ideation.

Design by Analogy: A Study of the WordTree Method for Problem Re-Representation

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
J. S. Linsey ◽  
A. B. Markman ◽  
K. L. Wood
Keyword(s):  
Design Theory ◽  
Knowledge Bases ◽  
Dump Truck ◽  
Future Research ◽  
Control Group ◽  
Design Problems ◽  
Team Projects ◽  
Novel Approach ◽  
Design By Analogy ◽  
Available Information

This paper presents a novel approach, referred to as the WordTree design-by-analogy method, for identifying distant-domain analogies as part of the ideation process. The WordTree method derives its effectiveness through a design team’s knowledge and readily available information sources (e.g., patent databases, Google) and does not require specialized computational knowledge bases. A controlled cognitive experiment and an evaluation of the method with redesign projects illustrate the method’s influence in assisting engineers in design-by-analogy. Individuals using the WordTree method identified significantly more analogies and searched outside the problem domain as compared to the control group. The team redesign projects demonstrate the WordTree method’s effectiveness in longer-term, more realistic, higher validity team projects and with a variety of different design problems. Teams successfully identified effective analogies, analogous domains, and analogous patents. Unexpected and unique solutions are identified using the method. For example, one of the teams identified a dump truck and panning for gold as effective analogies for the design of a self-cleaning cat litter box. In the controlled experiment, a cherry pitter was identified and implemented as a solution for designing a machine to shell peanuts. The experimental results also highlight potential improvements for the method and areas for future research in engineering design theory.

Increasing Innovation: A Trilogy of Experiments Towards a Design-by-Analogy Method

2007 ◽  
Author(s):  
J. S. Linsey ◽  
J. P. Laux ◽  
E. Clauss ◽  
K. L. Wood ◽  
A. B. Markman
Keyword(s):  
Design Problem ◽  
Domain Specific Language ◽  
General Representation ◽  
Design Problems ◽  
Analogy Method ◽  
Domain Specific ◽  
Design By Analogy ◽  
Product Description ◽  
Novel Design ◽  
Analogous Product

Design by analogy is a noted approach for conceptual design. This paper seeks to develop a robust design-by-analogy method. This endeavor is sought through a series of three experiments focusing on understanding the influence of representation on the design-by-analogy process. The first two experiments evaluate the effects of analogous product description—presented in either domain-general or domain-specific language—on a designer’s ability to later use the product to solve a novel design problem. Six different design problems with corresponding analogous products are evaluated. The third experiment in the series uses a factorial design to explore the effects of the representation (domain specific or general sentinel descriptions) for both the design problem and the analogous product on the designer’s ability to develop solutions to novel design problems. Results show that a more general representation of the analogous products facilitates later use for a novel design problem. The highest rates of success occur when design problems are presented in domain specific representations and the analogous product is in a domain general representation. Other insights for the development of design by analogy methods and tools are also discussed.

Identifying Trends in Analogy Usage for Innovation: A Cross-Sectional Product Study

2014 ◽  
Vol 136 (11) ◽  
Author(s):  
Peter Ngo ◽  
Cameron J. Turner ◽  
Julie S. Linsey
Keyword(s):  
Product Performance ◽  
Design Teams ◽  
Cross Sectional ◽  
Design Problems ◽  
Support Tool ◽  
Bioinspired Design ◽  
Design By Analogy ◽  
Improved Performance ◽  
Product Study ◽  
Analog Domain

Design-by-analogy, including bioinspired design, is a powerful tool for innovation. Engineers need better tools to enhance ideation. To support tool creation, an exploratory cross-sectional empirical product study of 70 analogy-inspired products is conducted to report trends and associations among factors in the analogy-inspired design process, giving a general account of real-world practices. Products are randomly sampled from three technology magazines and a bioinspired design database. Seven variables are developed and used to classify each example according to design team composition, analogy mapping approach, analogies used, and design outcomes. Results do not suggest significant differences between problem-driven approaches, which start from a design problem and find solutions in analogous domains, and solution-driven approaches, which begin with knowledge in an analog domain and find design problems to solve. For instance, results suggest that both approaches yield products at about the same frequency, and both yield products with improved performance at statistically indistinguishable rates—thus, neither approach can be concluded to be advantageous over the other for improving product performance at this time. Overall, few associations are detected between design outcome variables and other variables, thus precluding recommendations for how to compose design teams, what approaches to promote, and what number and source of analogies to support in order to achieve the outcomes measured in this study.

Effects of Abstraction on Selecting Relevant Biological Phenomena for Biomimetic Design

2014 ◽  
Author(s):  
Tao Feng ◽  
Hyunmin Cheong ◽  
L. H. Shu
Keyword(s):  
Natural Language ◽  
Biological Knowledge ◽  
Design Problems ◽  
Biomimetic Design ◽  
Search Results ◽  
Biological Phenomena ◽  
Design By Analogy ◽  
Novice Designers

The natural-language approach to identifying biological analogies exploits the existing format of much biological knowledge, beyond databases created for biomimetic design. However, designers may need to select analogies from search results, during which biases may exist towards: specific words in descriptions of biological phenomena, familiar organisms and scales, and strategies that match preconceived solutions. Therefore, we conducted two experiments to study the effect of abstraction on overcoming these biases and selecting biological phenomena based on analogical similarities. Abstraction in our experiments involved replacing biological nouns with hypernyms. The first experiment asked novice designers to choose between a phenomenon suggesting a highly useful strategy for solving a given problem, and another suggesting a less-useful strategy, but featuring bias elements. The second experiment asked novice designers to evaluate the relevance of two biological phenomena that suggest similarly useful strategies to solve a given problem. Neither experiment demonstrated the anticipated benefits of abstraction. Instead, our abstraction led to: 1) novice designers associating non-abstracted words to design problems and 2) increased difficulty in understanding descriptions of biological phenomena. We recommend investigating other ways in which abstraction can be implemented when designing similar tools or techniques that aim to support biomimetic design and other design-by-analogy work.

Enhanced Targeted Initial Populations for Multiobjective Product Line Optimization

2013 ◽  
Author(s):  
Garrett Foster ◽  
Scott Ferguson
Keyword(s):  
Domain Knowledge ◽  
Computational Cost ◽  
Product Line ◽  
Initial Product ◽  
Design Problems ◽  
Product Line Design ◽  
Product Level ◽  
Expensive Problems ◽  
Simple Product ◽  
Line Design

Initial populations for genetic algorithms are often created using randomly generated designs in an effort to maximize the genetic diversity in the design space. However, research indicates that the inclusion of solutions generated based on domain knowledge (i.e. non-random solutions) can notably improve the performance of the genetic algorithm with respect to solution performance and/or computational cost for convergence. This performance increase is extremely valuable for computationally expensive problems, such as product line optimization. In prior research, the authors demonstrated these improvements for product line design problems where market share of preference was the performance objective. Initial product line solutions were constructed from products that had the largest product-level utility for individual respondents. However, this simple product identification strategy did not adequately scale to accommodate the richer design problem associated with multiple objectives. This paper extends the creation of targeted initial populations to multiobjective product line design problems by using the objectives of the problem, instead of product level utility, to identify candidate designs. A MP3 player and vehicle feature packaging product line design problems are used to demonstrate this approach and assess the improvement of this modification.

scholarly journals Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design

2021 ◽  
pp. 1-21
Author(s):  
Ayush Raina ◽  
Lucas Puentes ◽  
Jonathan Cagan ◽  
Christopher McComb
Keyword(s):  
Design Problem ◽  
Domain Knowledge ◽  
Search Space ◽  
Design Strategies ◽  
Design Problems ◽  
Engineering Design Problems ◽  
One Step ◽  
Convolutional Encoder ◽  
Action Spaces ◽  
Relevant Domain

Abstract Engineering design problems often involve large state and action spaces along with highly sparse rewards. Since an exhaustive search of those spaces is not feasible, humans utilize relevant domain knowledge to condense the search space. Deep learning agents (DLAgents) were previously introduced to use visual imitation learning to model design domain knowledge. This note builds on DLAgents and integrates them with one-step lookahead search to develop goal-directed agents capable of enhancing learned strategies for sequentially generating designs. Goal-directed DLAgents can employ human strategies learned from data along with optimizing an objective function. The visual imitation network from DLAgents is composed of a convolutional encoder-decoder network, acting as a rough planning step that is agnostic to feedback. Meanwhile, the lookahead search identifies the fine-tuned design action guided by an objective. These design agents are trained on an unconstrained truss design problem modeled as a sequential, action-based configuration design problem. The agents are then evaluated on two versions of the problem: the original version used for training and an unseen constrained version with an obstructed construction space. The goal-directed agents outperform the human designers used to train the network as well as the previous feedback-agnostic versions of the agent in both scenarios. This illustrates a design agent framework that can efficiently use feedback to not only enhance learned design strategies but also adapt to unseen design problems.

Identifying Trends in Analogy Usage for Innovation: A Cross-Sectional Product Study

2014 ◽  
Author(s):  
Peter Ngo ◽  
Cameron J. Turner ◽  
Julie Linsey
Keyword(s):  
Product Performance ◽  
Design Teams ◽  
Cross Sectional ◽  
Design Problems ◽  
Support Tool ◽  
Design Database ◽  
Design By Analogy ◽  
Improved Performance ◽  
Product Study ◽  
Analog Domain

Design-by-analogy, including bio-inspired design, is a powerful tool for innovation and engineers need better tools to enhance ideation. To support tool creation, an exploratory cross-sectional empirical product study of 70 analogy-inspired products is conducted to report trends and associations among factors in the analogy-inspired design process, giving a general account of real-world practices. Products are randomly sampled from three technology magazines and a bioinspired design database. Seven variables are developed and used to classify each example according to design team composition, analogy mapping approach, analogies used, and design outcomes. Results suggest few differences between problem-driven approaches, which start from a design problem and find solutions in analogous domains, and solution-driven approaches, which begin with knowledge in an analog domain and find design problems to solve. For instance, results suggest that both approaches yield products at about the same frequency, and both yield products with improved performance at statistically-indistinguishable rates — thus, neither approach can be presently concluded to be advantageous over the other for improving product performance. Overall, few associations are detected between design outcome variables and other variables, thus precluding recommendations for how to compose design teams, what approaches to promote, and what number and source of analogies to support in order to achieve the outcomes measured in this study.

Overcoming design fixation: Design by analogy studies and nonintuitive findings

2016 ◽  
Vol 30 (2) ◽  
pp. 185-199 ◽  
Author(s):  
Diana P. Moreno ◽  
Luciënne T. Blessing ◽  
Maria C. Yang ◽  
Alberto A. Hernández ◽  
Kristin L. Wood
Keyword(s):  
Idea Generation ◽  
Knowledge Domain ◽  
Design Problems ◽  
Domain Experts ◽  
Design Fixation ◽  
Wide Range ◽  
Common Framework ◽  
Design By Analogy ◽  
Negative Impacts ◽  
Important Significance

AbstractDesign fixation is a phenomenon with important significance to many fields of design due to the potential negative impacts it may have in design outcomes, especially during the ideation stage of the design process. The present study aims to provide a framework for understanding, or at least probing, design fixation by presenting a review of existing defixation approaches, as well as metrics that have been employed to understand and account for design fixation. This study also describes the results of two design by analogy (DbA) methods, WordTree and SCAMPER, to overcome design fixation in an experiment that involved 97 knowledge-domain experts. The study outcomes are at least twofold: a common framework of metrics and approaches to overcome design fixation in a wide range of design problems and nonintuitive results for DbA approaches in design fixation and other related creativity metrics. The application of WordTree and SCAMPER shows that both methods yield increased novelty compared to a control, where the SCAMPER results are significantly higher than WordTree. It is also found that WordTree mitigates design fixation whereas SCAMPER appears to be ineffective for this purpose but effective to generate an increased quantity of novel ideas. These results demonstrate that both DbA methods provide de-fixation capabilities and enhance designers’ creativity during idea generation.

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