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ASME Conference Presenter Attendance Policy and Archival Proceedings

2017;():V007T00A001. doi:10.1115/DETC2017-NS7.
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This online compilation of papers from the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE2017) represents the archival version of the Conference Proceedings. According to ASME’s conference presenter attendance policy, if a paper is not presented at the Conference by an author of the paper, the paper will not be published in the official archival Proceedings, which are registered with the Library of Congress and are submitted for abstracting and indexing. The paper also will not be published in The ASME Digital Collection and may not be cited as a published paper.

Commentary by Dr. Valentin Fuster

29th International Conference on Design Theory and Methodology: Creativity and Ideation

2017;():V007T06A001. doi:10.1115/DETC2017-67228.

As a branch of computational creativity, Creative Knowledge Discovery (CKD) aims to search for valuable, previously unknown, or ignored, relationships between concepts, and create new patterns by taking advantage of existing patterns or by analogy to patterns in other domains. Data mining has been widely used in CKD research. However, most proposed mining algorithms lack a theoretical basis for computational creativity due to their origins in traditional knowledge discovery in databases (KDD), which stymies novelty. In addition, integration of human-computer interaction (HCI) is often overlooked for assisting discovery of creative knowledge despite the human end user possessing problem solving intelligence. To address these issues, a network-based computational model bridging human-computer interaction and data mining is proposed arising from an initial investigation on the theoretical basis of computational creativity. A corresponding creativity evaluation methodology, Multi-dimensional In-depth Long-term Case studies (MILCs) is also introduced. In order to evaluate the proposed model, a web tool called B-Link has been developed. Longitudinal interviews and a questionnaire survey have been conducted by applying the MILCs evaluation method. The success of finding novel items and obtaining inspiration in interviews as well as the positive survey rating results of all five creativity metrics have suggested that B-Link is able to guide thinking processes and aid creative knowledge discovery effectively, which demonstrates the capability of the proposed network-based computational creativity model integrating human-computer interaction and data mining.

Commentary by Dr. Valentin Fuster
2017;():V007T06A002. doi:10.1115/DETC2017-67261.

The external validity of existing creativity tests was examined in the product-design field. To examine the external validity, this study adopted the Consensual Assessment Technique (CAT), by which industry leaders directly rate product ideas for their creativity. A simple correlation analysis showed that among three broadly used creativity tests (Remote Associations Test, Alternative Uses Test, and Torrance Test for Creative Thinking), only the Alternative Uses Test (AUT) was found to predict creativity in the product-design industry. In addition to the correlations analysis, two factors, product familiarity and level of interest, were tested for moderation. The results show that familiarity with the product lessens RAT-CAT (Remote Associations Test - Consensual Assessment Technique) correlation, whereas level of interest strengthens the correlation. Thus, the less familiar and more interested an individual is in the product, the more likely the individual’s divergent thinking skills will translate into an actual creative product idea.

Commentary by Dr. Valentin Fuster
2017;():V007T06A003. doi:10.1115/DETC2017-67307.

Due to a lack of essential knowledge to support functional reasoning from the design requirements of the kinematic compound mechanisms to their constituent mechanisms, the creative conceptual design of kinematic compound mechanisms based on functional synthesis approach is still a challenging task. Through introducing the dynamic partition-matching process between the function layer and the form layer to substitute for the direct function-structure matching in the FBS model, the function-structure matching problem corresponding to deficient functional reasoning knowledge for kinematic compound mechanisms is solved by the authors. The following challenge is how to cluster the divided subset of basic operation actions generated in the form layer during the partition-matching process into a well-organized and complete kinematic behavior that can be matched by the sub-function in the function layer and implemented by a structure in the database. The adopted strategies in this paper are: through defining the correlation indexes between basic operation actions, the basic operation action and its realized function behavior, and its embodied structure, as well as its dynamic behavior characteristics, the clustering possibility for a group of basic operation actions is determined. With the aid of the compatibility conditions between basic operation actions in the form layer and the consistency of the order relations between basic operation actions in the function layer and the form layer respectively, the consistency of the order relations among basic operation actions between the sub-functions in the function layer and the sub-behaviors in the form layer are guaranteed. Then, the optimal matching structures corresponding to the sub-functions in the function layer are determined based on the maximum matching coefficients of basic operation actions. In this way, the subsets of basic operation actions in the form layer are clustered into a number of complete behaviors that can be realized by mechanisms in the structure database and matched by the sub-functions in the function layer. Since multiple functional behaviors of each constituent basic mechanism take part in matching, some novel schemes of compound mechanisms with fewer and simpler constituent mechanisms to implement the overall function may be dug out.

Commentary by Dr. Valentin Fuster
2017;():V007T06A004. doi:10.1115/DETC2017-67502.

This paper focuses on comparing and contrasting methods for assessing the variety of a group of design ideas. Variety is an important attribute of design ideas, because it indicates the extent to which the solution space has been explored. There is a greater likelihood of successfully solving a design problem when a more diverse set of ideas is generated in the early stages of design. While there are three existing metrics for variety, it has not been established how well they correlate with each other, so it is unknown whether they provide similar assessments of variety. This uncertainty inspired our investigation of the three existing metrics and, eventually, the development of a new variety metric — all of which we compared statistically and qualitatively. In particular, 104 design ideas collected from 29 sophomore mechanical engineering students were analyzed using the existing and new variety metrics. We conducted correlation analyses to determine if the four metrics were related and to what degree. We also considered the qualitative differences among these metrics, along with where they might be used most effectively. We found varying levels of statistically significant correlations among the four metrics, indicating that they are dependent. Even so, each metric offers a unique perspective on variety and may be useful in different situations.

Commentary by Dr. Valentin Fuster
2017;():V007T06A005. doi:10.1115/DETC2017-67513.

Functional fixedness refers to a cognitive bias that prevents people from using objects in new ways, and more abstractly, perceiving problems in new ways. Supporting people in overcoming functional fixedness could improve creative problem solving and capacities for creative design.

A study was conducted to detect whether a relationship exists between participants’ tendency to reorient objects presented as stimuli in an Alternative Uses Test and their creativity, also measured using the Wallach Kogan pattern meanings test. The Alternative Uses Test measures creativity as a function of identifying alternative uses for traditional objects. The Wallach Kogan pattern-meanings test detects the ability to see an abstract pattern as different possible objects or scenes. Also studied is whether Kruglanski’s Need for Closure scale, a psychological measure, can predict the ability to incorporate reorientation cues when identifying uses.

This study revealed highly significant, high correlations between reorientation and several creativity measures, and a correlation between reorientation and the predictability subscale of the Need for Closure scale. A qualitative exploration of participants’ responses reveals further metrics that may be relevant to assessing creativity in the Alternative Uses Test.

Topics: Creativity , Design
Commentary by Dr. Valentin Fuster
2017;():V007T06A006. doi:10.1115/DETC2017-67604.

This paper studies how engineering education might change divergent thinking skills. We hypothesized that people use a higher amount of divergent thinking when a task is unfamiliar. Our previous work developed an online survey to measure divergent ideation in two ways: with one ideation task, equally familiar to both novice and experienced designers, and a second ideation task, familiar only to experienced designers. We sorted ideas from 40 engineering upperclassmen and 40 freshmen into hierarchical categories and scored fluency, flexibility, and originality. The results did not confirm our hypothesis; rather, we found that originality scores were not significantly different between freshman and upperclassmen. Additionally, both groups produced their most-original ideas in the generally-familiar ideation task.

Limitations in our methods prevented meaningful conclusions about flexibility, and further study will be necessary to confirm our other conclusions. To better explore factors influencing divergent thinking, we will refine our methods for future work and retest the participants from the freshmen group in a longitudinal study.

Commentary by Dr. Valentin Fuster
2017;():V007T06A007. doi:10.1115/DETC2017-67752.

The effect of analogical distance between design stimuli and design problem on novelty and quality of generated concepts is investigated in this research. Data from a design project involving 105 student designers, divided into 21 teams and individually generating 226 concepts of spherical rolling robots, is collected. From this data, 138 concepts generated with patents as stimuli and the patents used as stimuli are analyzed. Analogical distance of a patent is measured in terms of the knowledge distance of the technology classes constituting this patent from the technology classes constituting the design problem domain of spherical rolling robots. The key findings are: (a) technology classes in closer than farther distance from the design problem are used more frequently to generate concepts, (b) as analogical distance increases the novelty of concepts increases, and (c) as analogical distance decreases the quality of concepts increases. These observations have implications on choosing stimuli to generate concepts of desired novelty and quality.

Topics: Robots , Design , Patents , Teams , Students
Commentary by Dr. Valentin Fuster
2017;():V007T06A008. doi:10.1115/DETC2017-68058.

In the present competitive business environment, designers and engineers need to come up with creative, innovative and valuable design ideas. In engineering design, the function (F), behavior (B) and structure (S) of a product are discussed using design theory and methodology. On the other hand, the concept of user experience (UX) is becoming important in product design. In this paper, we first discuss the relationship among F, B, S, UX and the value of a product. Then we propose a delta design map as a framework for a systematic method and computational tool for design ideation support. A delta design map does not describe F, B, S and UX for design examples but describes their differences (delta) between design examples. This approach makes the descriptions efficient and gives clear criteria on what needs to be described and what need not be described. By preparing a delta design map, we can systematically and exhaustively analyze the potential similarity among all design examples from the viewpoint of F, B, S and UX and obtain triggers for ideation. The results of a simple trial of the proposed method are presented and discussed in this paper.

Topics: Design
Commentary by Dr. Valentin Fuster
2017;():V007T06A009. doi:10.1115/DETC2017-68239.

This paper investigates the relationship between interaction behaviors and the cognitive characteristics of participating individuals in engineering design teams engaged in concept generation. Individual characteristics were measured using the Kirton Adaption-Innovation inventory (KAI), which assesses an individual’s cognitive preference for structure in seeking and responding to change. Team interactions were measured using the Interaction Dynamics Notation (IDN), which allows interaction behaviors to be quantitatively analyzed. A correlation analysis revealed statistically significant correlations between individual characteristics and specific interaction behaviors, and ideation utterances. An interaction sequence analysis of the team data also revealed specific interaction sequences associated with greater probabilities of idea occurrence within the team. These findings serve as a first step towards building a cognitive-behavioral model of engineering design team performance.

Commentary by Dr. Valentin Fuster
2017;():V007T06A010. doi:10.1115/DETC2017-68304.

The emergence of ideation methods that generate large volumes of early-phase ideas has led to a need for reliable and efficient metrics for measuring the creativity of these ideas. However, existing methods of human judgment-based creativity assessments, as well as numeric model-based creativity assessment approaches suffer from low reliability and prohibitive computational burdens on human raters due to the high level of human input needed to calculate creativity scores. In addition, there is a need for an efficient method of computing the creativity of large sets of design ideas typically generated during the design process. This paper focuses on developing and empirically testing a machine learning approach for computing design creativity of large sets of design ideas to increase the efficiency and reliability of creativity evaluation methods in design research. The results of this study show that machine learning techniques can predict creativity of ideas with relatively high accuracy and sensitivity. These findings show that machine learning has the potential to be used for rating the creativity of ideas generated based on their descriptions.

Commentary by Dr. Valentin Fuster
2017;():V007T06A011. doi:10.1115/DETC2017-68380.

Past work has demonstrated that simulating an extraordinary user scenario could have an impact on increasing designer empathy and creativity. It is likely, however, that an individual’s background could make a difference on how such simulated scenarios influence designers and how well the design method works. In this paper, we study the impact of demography and personal connection of the participants to any given simulated scenario versus their response to different empathic simulation workshops. With a variety of design tools and techniques available, understanding such influencing factors could help designers decide on the appropriate design tool for effective ideation. In this study, we investigated the effect of 81 (49 female and 32 male) users from three different workshops that simulated three different extraordinary user scenarios. Results of the study show that personal connection to a population being simulated significantly affects the impact a simulated scenario has on evoking creativity and empathy. And, for the given set of participants, gender did not show significant impact on the participants’ response.

Topics: Creativity
Commentary by Dr. Valentin Fuster
2017;():V007T06A012. doi:10.1115/DETC2017-68428.

Design problems are used to evaluate students’ abilities, the impact of various teaching approaches and of design methods. Design problems greatly vary in style and subject area in order to accommodate for a wide distribution of disciplines, cultures, and expertise. While design problems are occasionally reused between studies, new design problems are continuously created in order to account for the fact that a design problem cannot be used multiple times on an individual in order to effectively measure one’s abilities to perform design. More specifically, in repeated measures testing, students cannot receive the same design problem multiple times, for this would cause bias; therefore, multiple design problems are needed to allow for repeated measures testing. The nature and structure of these multiple design problems need to be similar or “equivalent” in order to accurately measure students’ abilities to perform in design. In this study, we examine four design problems: peanut shelling, corn husking, coconut harvesting, and a personal alarm clock. We determine whether these problems could be deemed equivalent for the purposes of evaluating student design performance through repeated measures testing. We implemented idea generation sessions using both between-subject and within-subjects approaches. Solutions were evaluated on quantity, quality, novelty, variety, and completeness metrics. The data implies that the Peanut and Corn problems are similar in nature and the Alarm and Coconut problems are also similar in nature; as such, these problem pairings may be used to test differences based on group means.

Commentary by Dr. Valentin Fuster

29th International Conference on Design Theory and Methodology: Design of Complex Systems

2017;():V007T06A013. doi:10.1115/DETC2017-67042.

This paper introduces a framework to design and manage flexibility in engineering systems based on the concept of decision rules. A decision rule can be described as a heuristic triggering mechanism that is used to determine when it is appropriate to exercise flexibility in systems operations. The proposed framework differs from existing real options analysis (ROA) approaches used in a design and management setting by focusing on the practicability in the implementation phase of engineering systems. By incorporating decision rules in the design process, this framework not only helps generate better performing designs, it also provides intuitive guidance for decision makers (DMs) to manage the system in operations. The proposed framework is applied as demonstration to the design and management of an anaerobic digestion (AD) waste-to-energy (WTE) plant. It demonstrates significant lifecycle performance improvement as compared to a standard design analysis. A comparison with existing ROA approaches shows that another advantage of the proposed framework is the ability to analyze systems facing multiple uncertainty sources and relying on multiple flexibility strategies as a way to improve expected lifecycle performance.

Commentary by Dr. Valentin Fuster
2017;():V007T06A014. doi:10.1115/DETC2017-67369.

During the development planning of a new product, designers rely on the prediction of the product performance to make business investments and frame design strategy. The S-curve model is commonly used for this purpose, but it has several drawbacks. A significant volume of product performance data doesn’t fit well with an S-curve. An S-curve model is also not capable of showing what factors shape the future performance of a product and how designers can change it. In this paper, Lotka-Volterra equations, which subsume both the logistic S-curve model and Moore’s Law, are used to describe the interaction between a product (system technology) and the components and elements (component technologies) that are combined to form the product. The equations are simplified by a relationship table and a maturation evaluation process as a two-step simplification. The historical performance data of the system and its components are fitted by the simplified Lotka-Volterra equations. The methods developed here allow designers to predict the performances of a product and its components quantitatively by the simplified Lotka-Volterra equations. The methods also shed light on the extent of performance impact from a specific module on a product, which is valuable for identifying the key features of a product and thus making outsourcing decisions. Smart phones are used as an example to demonstrate the two-step simplification. The data fitting method is validated by the time history performance data of airliners and turbofan aero-engines.

Commentary by Dr. Valentin Fuster
2017;():V007T06A015. doi:10.1115/DETC2017-67453.

The design of complex engineered systems is challenging, especially in early design stages due to the complex emergent behavior that often results in unforeseen failures. Emergent behavior is a distinctive aspect of systems in which the exhibited behavior of the system is more complex than the behavior of the individual components that shape the system. Understanding the emergent behavior is critical to perform an accurate assessment of the designed system. The objective of this paper is to explore the different existing concepts, methods, and approaches used by researchers to understand and manage emergent behavior in complex systems. We provide a critical review of the emergence concept to discern what characteristics about the causal process it reflects, so it can be used or implemented in further research in complex engineered systems. Specifically, this research explores the current state of-the-art on emergence, and identifies possible gaps in the research literature. We present different approaches used by engineers to deal with emergent behavior in different research areas such as Multiagent Systems (MAS), System of Systems (SOS), and Emergence Engineering.

Commentary by Dr. Valentin Fuster
2017;():V007T06A016. doi:10.1115/DETC2017-67467.

In designing complex systems, systems engineers strive to turn an existing situation into a situation that is most preferred. A rational decision maker would choose the alternative that maximizes the expected utility of the existing situation, but there are significant computational challenges to this approach. To overcome these challenges, most decision makers revert to heuristics. In this paper, we propose a conceptual framework for heuristics in design. A preliminary empirical study of designers for a robotics design problem was conducted to observe how participants apply heuristics. Participants having at least 2 years of experience designing robots were recruited to partake in a robotics design session in which participant were given 45 minutes to work on a design problem. A preliminary heuristics extraction method was developed, and the identified heuristics were studied to find trends within the overall set. These trends were the basis of a taxonomy of heuristics consisting of three initial classification methods: design phase, field of study, and action intent. The heuristics and classifications are presented, along with the challenges from extracting heuristics and recommendations for future work to further research design heuristics and to improve the method for extraction.

Topics: Design
Commentary by Dr. Valentin Fuster
2017;():V007T06A017. doi:10.1115/DETC2017-67592.

In this paper, we present a method for identifying conflicts (Dilemmas) that have zero-sum solutions among the three aspects (Drivers) of sustainability, namely, social (people), environment (planet), and economic (profit) values. We develop the value proposition that is anchored in sustainable rural development by converting these zero-sum solutions to positive-sum solutions. Rural development is difficult, and it must be initiated from within the communities with the involvement of local people. We hypothesize that social entrepreneurs can serve as the proverbial lynchpin between the rural population and other agencies (government, non-government, banks, and industry). Hence in this paper, we use the constructs of a dilemma triangle and spheres of sustainability to propose a method to identify and manage dilemmas associated with creating a sustainable eco-system. We use example of a village in India to illustrate the method and to develop the value proposition for the village. The focus in this paper is on the method, rather than the results per se.

Commentary by Dr. Valentin Fuster
2017;():V007T06A018. doi:10.1115/DETC2017-67701.

The major goal of customer requirement formulation is to achieve a common understanding between the project stakeholders and the engineering requirements. Many times, this process can be ambiguous, incomplete, and time consuming especially when more than one engineering discipline is involved. Therefore, adequate requirement formulation tools can be a major contributor to solving these challenges. The use of ontologies provides a standardized way of describing concepts in a domain of interest and the relationships between these concepts to better understand the domain as a whole. This paper describes the methodology used to create an ontology derived from twenty customer requirements of a mid-size, twin-engine, commercial transport-class aircraft provided by NASA Ames Research Center. One key stipulation that NASA had was that this ontology effectively captures the relationships that exist between the hardware and software level of each customer requirement. The final ontology was created using Protégé OWL, an open source ontology editor, which will be used by NASA in order to improve the customer requirement creation phase of future NASA products. The ontology and requirements were further generalized into a set of common patterns for describing requirements in this domain. These pattern templates provide a tool to ensure that common styles of requirements have been considered, and that these common styles are uniform. This research paper fills a gap in the customer requirement research field by introducing the use of ontologies and common patterns to reduce ambiguity and repetition.

Commentary by Dr. Valentin Fuster
2017;():V007T06A019. doi:10.1115/DETC2017-67866.

All methods associated with failure analysis attempt to identify critical design variables and parameters such that appropriate process controls can be implemented to detect problems before they occur. This paper introduces a new approach to the identification of critical design variables and parameters through the concept of bridging nodes. Using a network-based perspective in which design parameters and variables are modeled as nodes, results show that vulnerable parameters tend to be bridging nodes, which are nodes that connect two or more groups of nodes that are organized together in order to perform an intended function. This paper extends existing modeling capabilities based upon a behavioral network analysis (BNA) approach and presents empirical results identifying the relationship between bridging nodes and parameter vulnerability as determined by existing, network metric-based methods. These topological network robustness metrics were used to analyze a large number of engineering systems. Bridging nodes are associated with significantly larger changes in network degradation, as measured by these metrics, than non-bridging nodes when subject to attack (p < 0.001). The results indicate the structural role of vulnerable design parameters in a behavioral network.

Commentary by Dr. Valentin Fuster

29th International Conference on Design Theory and Methodology: Entrepreneurship and Teams in Design

2017;():V007T06A020. doi:10.1115/DETC2017-67430.

The performance of a team is highly dependent on how the team is structured, how individuals in the team communicate with one another, and the properties exhibited by the problem being solved. It is generally assumed that teams are a superior approach in problem-solving and design. However, this work shows that for a configuration design problem of moderate size, the optimal approach for a homogenous team is in fact for members of the team to work independently, with the best solution from the individuals chosen at the end. Moreover, this work demonstrates that this surprising strategy can be predicted from knowledge of the problem’s properties through a computationally-derived set of response surfaces. First, a novel design problem is defined that requires solvers to create a system of internet-connected products to maintain the temperature within a home. Next, the characteristics of this new design problem are measured, and a computationally-derived response surface yields the untraditional prediction that teams should not interact while solving the problem. Finally, this prediction is tested and shown correct through a cognitive study. This work makes two contributions to the state of the art. First, it provides verification of a methodology that allows optimal team characteristics to be predicted based on knowledge of a design problem. Second, it demonstrates an additional problem instance for which interacting teams are inferior to nominal teams (adding to a growing literature to that effect).

Topics: Teams
Commentary by Dr. Valentin Fuster
2017;():V007T06A021. doi:10.1115/DETC2017-67922.

Entrepreneurial teams are generally interdisciplinary in nature; they tend to combine business, design, and engineering disciplines/expertise. The effectiveness of interdisciplinary design teams has become more important for both start-ups and companies that want to innovate; however, it is often troublesome to determine the group composition that delivers a good product/business idea. The purpose of this study is to investigate the traits in personalities that are needed in a successful entrepreneurial student design team. A study was conducted in which 40 students were divided into seven groups to deliver a technology-based product using design thinking techniques, and consumer behavior theories and research. The personality for each team member was evaluated utilizing the Big Five Test and analyzed jointly as a team, denoted as Team’s Overall Personality (TOP); and by the variability of their personalities in the group, referred as Team Personality Distribution (TPD). The teams’ performances were accounted, ranking them in Best of Best (BOB) and Worst of Worst (WOW) by taking into consideration their performance in: interview collection, idea generation, prototyping, and final presentation. The results demonstrated that the teams with best performance had high variability in Neuroticism and Extraversion when analyzed by TPD and average personality traits in Extraversion and Agreeableness when analyzed with TOP. Therefore, analysis supported that each member’s personality affects his or her team’s performance. It is recommended that the relationship is further investigated for a better representation of efficient group compositions. Recommendations on how to compose entrepreneurial design teams are provided.

Topics: Teams , Students
Commentary by Dr. Valentin Fuster
2017;():V007T06A022. doi:10.1115/DETC2017-67974.

Prior work has shown that individual MBTI personality type influences the creative output of concept ideation methods [1,2]. In this paper, we present a pilot study that investigates the concept of team personality (defined as the average personality of the team along each MBTI spectrum) and the effect it has on ideation results, as measured by three creativity metrics; quantity, quality, and variety. We find evidence suggesting that a team whose average personality falls near the extremes of the Thinking-Feeling spectrum will produce more creative results, a team that is neutral along the Introversion-Extraversion spectrum can choose their method based on which creativity metric they wish to maximize, and that a team with high personality variance can choose to create either more variety or higher quantity of ideas based on their selected method.

Topics: Creativity , Teams
Commentary by Dr. Valentin Fuster
2017;():V007T06A023. doi:10.1115/DETC2017-68127.

The potential for mass collaboration and concurrent engineering among individuals working on a design project allows for increased innovation in idea generation while also supporting the parallelization of project development. The former of these two benefits is highlighted by recent corporate initiatives to incorporate crowdsourcing in their design process. This is done in an effort to garner new and unique perspectives while also driving designs that carry greater acceptance from the community and/or intended market. The latter benefit is emphasized by the pronounced success of concurrent engineering projects which tend to reduce production costs, all while enhancing overall product performance. This work aims to exploit these two concepts in a structured and methodical crowd centered design framework. A simulated pool of individuals, representing the crowd, are used to form design groups using game-theoretic principles. The outcome of each sub-game aims to increase the overall improvement to the designed system by maximizing what each individual can potentially add to the project. The optimization of resource allocation is then performed where time spent on individual or collaborative efforts is determined. The proposed framework is applied to simplified design projects at their initial conception, before detailed mathematical design models are determined.

Topics: Design , Collaboration
Commentary by Dr. Valentin Fuster
2017;():V007T06A024. doi:10.1115/DETC2017-68183.

Engineering organizations around the word are increasingly becoming team-based due to a teams’ ability to generate solutions to complex problems. This is thought to be attributed to the “wisdom of the collectives” where teams outperform the sum of their individual members. Despite heavy emphasis of teamwork in engineering design, our understanding of how to cultivate teamwork skills is poorly understood. This is due in part to the fact that research on engineering design teams is often based on ‘snap-shot’ ethnographic methods that do not account for the dynamic changes that happen over the course of a project. Research that does account for these interactions are hindered by the human processing required to code and analyze the immense amounts of video data acquired through team studies. Recent technological advances in the way of sociometric badges provide a potential avenue to explore intricate communication patterns and help researchers identify when and how team interventions should be developed. However, these technologies have not been validated for use in the dynamic context of engineering design teams. Thus, the current study was developed to examine sociometric badges for their accuracy, precision, and ability to determine speech dominance in engineering design teams. Our results show that sociometric badges can accurately capture total speaking time. However, the results also show that environmental conditions can impact their accuracy. In addition, we found that sociometric badges did not capture speech precisely and often overestimated when a team member was speaking. These results support the use of sociometric badges for capturing high level team interactions (e.g. participation and total speaking time) in engineering design research.

Commentary by Dr. Valentin Fuster

29th International Conference on Design Theory and Methodology: Human Behavior in Design

2017;():V007T06A025. doi:10.1115/DETC2017-67172.

We present a theoretical framework about how designers learn new ways of thinking and doing named the reframing theory. The theory underlines why some designers’ creative behaviors endure and some not in face of a conflicting social belief system. In this paper, we first describe the problems that designers and educators face when the cultures that designers attach to and the social logics that they invoke to make sense of their practices are constantly changing. Second, we decode the phenomenon and unpack the problems by drawing on an extensive body of research on cognitive processes, learning theories, and social influences. Third, we propose a theoretical framework to denote that the key to develop and maintain enduring creative behaviors is through reconstruction of one’s perceptions. This theory-oriented paper ends by discussing future directions for educators and researchers, with the aim to advance the research and academic discussions about how to improve design ability.

Topics: Design
Commentary by Dr. Valentin Fuster
2017;():V007T06A026. doi:10.1115/DETC2017-67207.

An eye-tracking experiment aimed at testing the claim that individuals understand how to use artifacts through the visual perception of their intended affordances was conducted. Sixty-one participants were asked to state the manner in which they would interact with an artifact after looking at their screen-based images for ten seconds with their gaze captured. The participants’ responses to perceived affordance were compared to their gaze data. Although individuals identified plausible affordances, a binary logistic regression analysis was inconclusive as to which eye-tracking variable is likely to entail a successful identification of the intended affordance. That said, there was a strong relationship between perception of the intended affordance and mention of either the artifact’s function or semantic category. The results suggest that affordances may not have a significant impact in the usability of products and interfaces. Extrapolating from the findings, we postulate that analogical priming may be a better explanation for the way individuals understand what to do with the artifact.

Commentary by Dr. Valentin Fuster
2017;():V007T06A027. doi:10.1115/DETC2017-67382.

The objective of this user study is to evaluate the effect of sequencing of unit cell design guidelines. The unit cell design guidelines support engineers in intentionally redesigning the topology and shape of unit cells for a desired structural behavior. In this study, four different unit cell design guidelines are selected to enable designers in increasing the shear flexure in meso-scale periodic cellular materials. These guidelines are not necessarily objective and may result in different modified unit cells when applied by different designers. Therefore, this user study was designed to evaluate the effect of sequencing the guidelines on the subjectivity and the modified unit cells. Twelve different sequencing sets are tested and it is found that certain sequencing of guidelines resulted in more novel ideas than other cases with less subjective guidelines.

Topics: Design
Commentary by Dr. Valentin Fuster
2017;():V007T06A028. doi:10.1115/DETC2017-67799.

Designing breakthrough products comes at a great cost to the design industry due to the risk and uncertainties associated with creative ideas. However, without creative ideas, there is no potential for innovation. As such, companies need to appropriately embrace the risk associated with creative concepts in the fuzzy front end of the design process in order to build their value. While previous research has linked risk taking attitudes to creative idea generation and selection in engineering design education, there has been limited research focused on engineering design professionals’ creative risk taking attitude and the corresponding driving factors. This is problematic because without this knowledge we do not know what factors inhibit or promote the flow of creative ideas in engineering design industry. In order to address this gap, a preliminary online survey was conducted with 46 design professionals from a global manufacturing company to understand the potential driving factors of creative risk taking, including educational training, job type (R&D, applied engineering, or management), and years of experience. The results suggest that there is a relationship between employee education level and years of experience and an engineering employee’s willingness to take risks on creative ideas in the fuzzy front end of the design process. Interestingly, the results also show that those individuals primarily responsible for the development (R&D) and selection (management) of creative ideas tend to be more financially risk averse than individuals in traditional engineering positions. These results contribute to the prediction of professionals’ design behaviors and have implications for the management of creative ideas in the early conceptual design stages of engineering design industry.

Commentary by Dr. Valentin Fuster
2017;():V007T06A029. doi:10.1115/DETC2017-68307.

Exploring design options for additively manufactured parts generally requires separate, sequentially applied software for design, analysis, and optimization. To evaluate the effect of integrating these capabilities within a single tool we conducted a controlled human subjects study. Three tools with different degrees of integration were created for two test cases of structural trusses, and it was found that increased integration improved quality, speed, and efficiency of the design process. After a quarter of their total time with the problems, 50% of designers with a fully integrated tool had a better design than 75% of other designers ever would. After that point, the top 50% of designers went on to explore a design space unreached with other tools. It appears that integration, and in particular the integration of optimization, leads to better performance by making it possible to explore complex designs and achieve outcomes which would be inaccessible to conventional tools.

Topics: Design , Optimization
Commentary by Dr. Valentin Fuster
2017;():V007T06A030. doi:10.1115/DETC2017-68335.

Successful design processes and tools are vital for the success of any design project, particularly when developing aerospace, automotive and other complex systems that can entail imposing design constraints to meet desired objectives. These constraints, coupled with a lack of uniform strategies to define, acquire and process the interaction between designers and tools, add new challenges to the design process. So appropriate processes and tools that allow problem designers to assist in framing and resolving complex design problems can extend the power of the individual working memory, according to previous research. This current research investigates the behavior of engineers working on a parameter design experiment. In the study, 30 subjects solved parameter design problems with both coupled and uncoupled variables. Results showed a relationship among designers’ actions and other features such as gender, recorded error, problem complexity, and performance. These findings can guide future research into engineering design and can inform ideas for better strategies for various aspects of parameter designing.

Topics: Design
Commentary by Dr. Valentin Fuster
2017;():V007T06A031. doi:10.1115/DETC2017-68382.

Design is a ubiquitous human activity. Design is valued by individuals, teams, organizations, and cultures. There are patterns and recurrent phenomena across the diverse set of approaches to design and also variances. Designers can benefit from leveraging conceptual tools like process models, methods, and design principles to amplify design phenomena. There are many variant process models, methods, and principles for design. Likewise, usage of these conceptual tools differentiates in industrial contexts. We present an integrated process model, with exemplar methods and design principles that is synthesized from a review of several case studies in client based industrial design projects for product, service, and system development, professional education courses, and literature review. Concepts from several branches of design practice: (1) design thinking, (2) business design, (3) systems engineering, and (4) design engineering are integrated. A design process model, method set, and set of abstracted design principles are porposed.

Topics: Design , Innovation
Commentary by Dr. Valentin Fuster
2017;():V007T06A032. doi:10.1115/DETC2017-68420.

Data was collected from a designer study and a protocol study where participants were asked to create function structure models using a seed model provided to them. This seed model was generated using three chaining methods: forward chaining, backward chaining, or nucleation; and the models were also created to a certain level of completion (10%, 40% or 80%). The resulting models will be analyzed using a count of functions and flows in the model as well as a previously developed scoring method. The aim of this comparison is to investigate whether the different chaining methods yield different results, as well as identify if the participants are more inclined to use a specific chaining method.

Commentary by Dr. Valentin Fuster

29th International Conference on Design Theory and Methodology: Prototyping and Design Representation

2017;():V007T06A033. doi:10.1115/DETC2017-67173.

This paper explores the nature of prototypes from three diverse companies in the fields of consumer electronics, footwear, and medical devices. It is part of a larger qualitative research study developing a prototyping framework grounded in the emergent findings from practice and detailed inductive inquiry. In this paper, we describe the methods for setting up an appropriate research design, highlighting the conceptual framework, means for data collection and analysis, and validity. Then, we describe the emergent findings, introducing a modified definition of a prototype and the three roles of prototypes.

This research is a contribution to the field of design theory and methodology by adding new knowledge about prototypes from companies. Prototyping is an essential part of product development, and yet it is one of the least formally explored areas of design. The significance of this work lies in its ability to gain insights into the role of prototyping in the natural work environment, which has not been holistically documented. By using diverse industries, we will build and test our framework across them all to ensure validity.

Commentary by Dr. Valentin Fuster
2017;():V007T06A034. doi:10.1115/DETC2017-67816.

Approximately half of new product development projects fail in the market place. Within the product development process, prototyping represents the largest sunk cost; it also remains the least researched and understood. While researchers have recently started to evaluate the impact of formalized prototyping methods and frameworks on end designs, these studies have typically evaluated the success or failure of these methods using binary metrics, and they often evaluate only the design’s technical feasibility. Intuitively, we know that a product’s success or failure in the marketplace is determined by far more than just the product’s technical quality; and yet, we have no clear way of evaluating the design changes and pivots that occur during concept development and prototyping activities, as an explicit set of rigorous and informative metrics to evaluate ideas after concept selection does not exist. The purpose of the current study was to investigate the discriminatory value and reliability of ideation metrics originally developed for concept generation as metrics to evaluate functional prototypes and related concepts developed throughout prototyping activities. Our investigation revealed that new metrics are needed in order to understand the translation of product characteristics, such as originality, novelty, and quality, from original concept through concept development and prototyping to finalized product.

Topics: Reliability
Commentary by Dr. Valentin Fuster
2017;():V007T06A035. doi:10.1115/DETC2017-68077.

This paper first presents a protocol study and its software realization for visualizing cognitive chunks as they form in real time during freehand sketching of design concepts, and then illustrates a method and metrics for measuring the information content of freehand sketches based on those chunks. A manual protocol for detecting cognitive chunks during sketching was reported earlier. In this research, the said protocol was automated into a software program and validated in a new protocol study, using new participants. The chunks detected by the program, by definitions in cognitive science literature, serve as entities or units of information conceived at once by the designer. The relations between these entities, esp. spatial relations, are then computed using a new method, which represents the sketch as an entity-relation (ER) model. An established protocol for measuring information of ER models is then applied to compute the information content of the sketches.

Commentary by Dr. Valentin Fuster
2017;():V007T06A036. doi:10.1115/DETC2017-68281.

Prototyping is an important part of the product development process, especially for the design of the manufacturing systems in small-to-medium enterprises (SMEs). Practitioners in resource-constrained settings face unique challenges when prototyping in these contexts. This work examines the methods, constraints, and impacts on design outcome of prototypes in manufacturing SMEs in resource-constrained settings through a case study. Observations and information were gathered through a site visit and interviews with the engineers at the partner organization. One of the important findings of this case study is that the main intent of prototyping is to develop high-fidelity, functional prototypes through simple prototyping, iteration, and the emphasis on physical prototypes. The overarching resource constraints on achieving this prototyping intent were found to be a variance in prototyping inputs, limited access to appropriate manufacturing capabilities, and limitations of modeling predictions.

Topics: Manufacturing
Commentary by Dr. Valentin Fuster
2017;():V007T06A037. doi:10.1115/DETC2017-68403.

In the early stages of design, designers may use a variety of tools to represent their ideas, including sketches, physical prototypes, and digital models. Prior research suggests that the choice of tool and design representation can influence user opinions of the concept. In this paper, we explore how aware designers and users are of the ways different design tools can influence a design. Specifically, we investigate the question “How is a design influenced by the tool used to create it?” Designs that had originally been created as either a sketch, foam prototype, or CAD model were sketched into a consistent visual style. Designers experienced with these tools exhibited a better-than-random likelihood of identifying the original tool used to create the design, despite viewing only the re-sketch. This suggests artifacts of a design tool persist in a design representation despite the design being translated from one medium to another.

Commentary by Dr. Valentin Fuster

29th International Conference on Design Theory and Methodology: Sustainability in Design

2017;():V007T06A038. doi:10.1115/DETC2017-67437.

Through a cross-sectional study of reactor design projects, this work explores the origins of design principles. The analysis of in-depth, open ended interviews with reactor designers reveals that there are design principles of which practitioners are aware (self-aware principles), and those principles recurring across projects which designers implicitly use in their work (naive principles). This analysis suggests that the ability of practitioners to generate principles is a function of the development of the domain of design and of its particular technologies. Larger the menu of prior designs, greater is the ability of practitioners to generate principles on which to base future work. In closing, and based on the analysis of interviews with reactor designers, I propose a set of criteria for use by design researchers developing design principles for practitioners.

Commentary by Dr. Valentin Fuster
2017;():V007T06A039. doi:10.1115/DETC2017-67494.

In recent years, the electricity industry has seen a drive towards the integration of renewable and environmentally friendly generation resources to power grids. These resources have highly variable availabilities. This work proposes a stochastic programming approach to optimize generation expansion planning (GEP) under generator supply capacity uncertainty. To better capture upside opportunities and reduce exposure to downside risks, flexibility is added to the GEP problem through real options on generator addition, which are to be exercised after uncertainty realizations. In addition, with the end goal of providing decision makers with easy-to-use guidelines, a conditional-go decision rule, akin to an if-then-else statement in programming, is proposed whereby the decision maker is provided with a threshold of excess total generator capacity from the previous time period, below which a predetermined generator addition plan (the option) is exercised. The proposed methodology and its decision rule are implemented in a real-world study of Midwest U.S. Comparisons are made to quantify the value of flexibility and to showcase the usefulness of the proposed approach.

Topics: Design , Power grids
Commentary by Dr. Valentin Fuster
2017;():V007T06A040. doi:10.1115/DETC2017-68393.

This paper presents a sustainable design method for wind turbines. Sustainable design recognizes three main pillars; economic growth, social equity, and environmental protection. A framework is developed to observe the tradeoffs among these areas of sustainable design. Each pillar of sustainability is mapped to a design variable, and normalized objective functions are defined. For the economic component, the objective function is based on costs and power production. The societal objective function focuses on noise and aesthetics impacts. These are represented by risk averse utility functions. Carbon dioxide emissions and noise pollution are the environmental objectives. A multi-objective genetic algorithm is also used with Pareto optimality to identify tradeoffs between these three sustainability factors. Wind speed data from three sites is used to simulate the performance of the system. The sets of data are unique and represent low, medium, and high wind speed areas. In all three cases, the results indicate that the economic and environmental objectives can both be met with a relatively small tradeoff. However, a greater amount of tradeoff is necessary when considering societal impacts.

Commentary by Dr. Valentin Fuster

29th International Conference on Design Theory and Methodology: User Preferences

2017;():V007T06A041. doi:10.1115/DETC2017-67150.

Multipurpose products are the artifacts with more than one intended or realized purposes. Abundance of multipurpose products in the market raises interesting questions about the desired customer preferences that lead to success or failure of such products in the market. This study aims to set the premise for developing design guidelines for multipurpose products. The study described in this paper is a qualitative content analysis of reviews of multi-purpose products available from online vendors. A traditional content analysis method is followed, where each sentence from the reviews is coded and categorized by three reviewers. Each category is then carefully analyzed and any redundancies are resolved. Finally, an interrater agreement is achieved between the three coders. The obtained categories shed light on customer expectations from multi-purpose products, their concerns, comments and experiences and their advice from the customer’s viewpoint for the design of such products. Each category identified here shows a potential research direction and a foundation for developing new guidelines for the development of such products.

Topics: Design
Commentary by Dr. Valentin Fuster
2017;():V007T06A042. doi:10.1115/DETC2017-67690.

Conjoint analysis has proven to be a useful method for decomposing and estimating consumer preference for each attribute of a product or service through evaluations of sets of different versions of the product with varying attribute levels. The predictive value of conjoint analysis is confounded, however, by increasing market uncertainties and changes in user expectations. We explore the use of scenario-based conjoint analysis in order to complement qualitative design research methods in the early stages of concept development. The proposed methodology focuses on quantitatively assessing user experiences rather than product features to create experience-driven products, especially in cases in which the technology is advancing beyond consumer familiarity. Rather than replace conventional conjoint analysis for feature selection near the end of the product development cycle, our method broadens the scope of conjoint analysis so that this powerful measurement technique can be applied in the early stage of design to complement qualitative research and drive strategic directions for developing product experiences. We illustrate on a new product development case study of a flexible wearable for parent-child communication and tracking as an example of scenario-based conjoint analysis implementation. The results, limitations, and findings are discussed in more depth followed by future research directions.

Topics: Design , Preferences
Commentary by Dr. Valentin Fuster
2017;():V007T06A043. doi:10.1115/DETC2017-67882.

Customer needs are one of the first items gathered and examined in the design process. Currently there are few methods of examining the collected customer needs to help designers track how much of the customer need space has been explored. None of the current prominent design texts provide an universally accepted categorization scheme to help categorize and examine collected customer needs. This paper ventures into the process of building an ontology that can be used to categorize and examine customer needs. The finalized ontology presented here went through 11 iterations and multiple inter-rater reliability tests throughout the creation process. The paper then discusses the possible uses of this scheme and how it can be utilized early in the design process to ensure that a thorough exploration of the customer need space is represented in the designers’ list of customer needs.

Topics: Ontologies
Commentary by Dr. Valentin Fuster
2017;():V007T06A044. doi:10.1115/DETC2017-68349.

The potential of smart home devices for improving the comfort, energy efficiency, and security of its residents has been noted by researchers and early adopters of these technologies. Despite these advantages and advances in home automation technology, their adoption has not been as widespread as anticipated by experts. Existing research has shown that the lack of trust in home devices is a significant deterrent to widespread adoption. There is little data on how this perceived trustworthiness of the system might be impacted by the location that the device operates in, and the perceived gender of the automated agent within the device. Therefore, this exploratory study addresses this knowledge gap by exploring the role of agent location (office / home) and gender of the agent’s voice (female / male) on perceptions of trustworthiness in a controlled laboratory setting with a simulated smart lock system. Preliminary results following quantitative and qualitative analysis of this pilot study show that users trust stereotype-congruent automated agents (male voice in office, female voice in home) more than stereotype-incongruent automated agents. These results shed light on users’ perceptions of trust with home automation devices, and provide directions for future research and development of trustworthy home automation devices.

Commentary by Dr. Valentin Fuster
2017;():V007T06A045. doi:10.1115/DETC2017-68366.

Design preference models are used widely in product planning and design development. Their prediction accuracy requires large amounts of personal user data including purchase and other personal choice records. With increased Internet and smart device use, sources of personal data are becoming more varied and their capture more ubiquitous. This situation leads to questioning whether there is a trade off between improving products and compromising individual user privacy. To advance this conversation, we analyze how privacy safeguards may affect design preference modeling. We conduct an experiment using real user data to study the performance of design preference models under different levels of privacy. Results indicate there is a tradeoff between accuracy and privacy. However, with enough data, models with privacy safeguards can still be sufficiently accurate to answer population-level design questions.

Topics: Design , Preferences
Commentary by Dr. Valentin Fuster

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