Function Modeling: A Study of Sequential Model Completion Based on Count and Chaining of Functions

Function models are widely recognized as a useful tool in mechanical engineering conceptual design as a bridge between problem and solution space. Unlike many other engineering design tools that are collaborative allowing many designers to contribute to the design task, function modeling has not been historically presented as a collaborative tool. This paper presents a controlled experimental study that explores the how different initial function models are completed by novice engineers influence the number of functions added to the model. Eighty-eight senior mechanical engineering students were given partial function models to two similarly complex engineering design problems. Each student was asked to complete the function model to best address the problem presented. The number of added functions was compared considering two variables: percent completed of initial seed model (10%, 40%, and 80%), initial chaining of functions (forward, backward, and nucleation). It was found that models for Backward Chaining and Nucleation at 10% initial seed resulted in the greatest addition of functions by the students. Further, Backward Chaining and Nucleation yielded more added functions than Forward Chaining in all seed configurations. Recognizing that there is a difference between Forward Chaining and Backward Chaining or Nucleation, further study is warranted to understand how individuals create function models and which approach yields more useful models to either understand the problem presented or to explore solution options.

Crowdsourcing the Evaluation of Design Concepts With Empathic Priming

The evaluation of design concepts is a time consuming and resource intensive process. Crowdsourcing evaluations has been examined in previous work as a means to reduce the need for expert raters, while achieving similar evaluation results. This paper examines the impact of empathically priming novice raters on their evaluation of alternative design concepts. The rating system is based on a pairwise comparison method that requires minimal training of novice raters. In a pilot study the pairwise method for crowdsourcing evaluations is compared with crowdsourced evaluations using non-pairwise rating scales and with the evaluations of expert raters. The primary study incorporates written and empathic priming strategies to determine their impact on novice raters’ evaluation of concepts. Raters are asked to consider several criteria, including novelty, feasibility, clarity (of the concept), usefulness, ease of use, and overall worthiness of further development. Results offer insight into the criteria that are most relevant to novice raters and whether empathic priming has a significant effect on those evaluations.

Comparison and Extension of Novelty Metrics for Problem-Solving Tasks

Shah’s metrics for measuring ideation effectiveness have been used extensively by the engineering design community to quantify the value of designed concepts. Shah measures novelty as the infrequency of an idea relative to a set of ideas. Vargas-Hernandez extended this novelty metric using partial genealogy trees to consider the frequency of ideas that share the same working principle. These genealogy trees capture differences between individual ideas organized by the following levels of abstraction: physical principle, working principle, and embodiment. Shah’s and Vargas-Hernandez’s metrics both require that all ideas be described at the lowest level (embodiment). This approach excludes ideas that are described at higher levels of abstraction. This paper proposes a new novelty metric that extends Vargas Hernandez’s metrics by including the higher levels of the genealogy trees, allowing abstract ideas to be properly evaluated. This paper compares the newly proposed novelty metric to Shah’s and Vargas Hernandez’s metrics using data from a previous study. The study required participants to perform problem-solving tasks in which they submitted a textual list of ideas for how to solve general day-to-day problems. The proposed novelty metric addresses limitations of the previous metrics when applied to the abstract ideas in the data set and meets established metric requirements. The proposed metric also broadens Shah’s metric in a similar manner as Vargas Hernandez but extends it to capture the entire genealogy tree rather than a subset of the tree.

Evaluations That Matter: Customer Preferences Using Industry-Based Evaluations and Eye-Gaze Data

This study is the first stage of a research program aimed at understanding differences in how people process 2D and 3D automotive stimuli, using psychophysiological tools such as galvanic skin response (GSR), eye tracking, electroencephalography (EEG), and facial expressions coding, along with respondent ratings. The current study uses just one measure, eye tracking, and one stimulus format, 2D realistic renderings of vehicles, to reveal where people expect to find information about brand and other industry-relevant topics, such as sportiness. The eye-gaze data showed differences in the percentage of fixation time that people spent on different views of cars while evaluating the “Brand” and the degree to which they looked “Sporty/Conservative”, “Calm/Exciting”, and “Basic/Luxurious”. The results of this work can give designers insights on where they can invest their design efforts when considering brand and styling cues.

Characterizing Competencies for Human-Centered Design

Employees and employers alike increasingly value human-centered design, as it can drive innovation across a wide range of industries. With the growing interest in understanding human-centered design processes as they apply in different professions, there is a rising need to recognize the specific competencies necessary to perform these jobs well. Though there is a body of research on how people discover, create, and use design methods, there is a lack of understanding of what core competencies are necessary for people to apply these methods. Previous interactions with target users of theDesignExchange, an interactive community-driven portal to support design researchers and practitioners, have demonstrated a desire for increased awareness of the competencies required for employability and for successful design practice. This paper reports on a portion of an expansive competency-finding project aimed at identifying the core set of competencies that human-centered design practitioners need and employers seek. In this paper, we present our lists of cultivated mindsets, specialized disciplinary skills, contextualized tasks, and basic skills in human-centered design. These lists represent a first pass at identifying the essential and underlying competencies a practicing or aspiring human-centered designer must have in order to perform their current or future design tasks. The work we present in this paper serves as a preliminary starting point for future research interviews with design practitioners and employers, as we seek to understand human-centered design competencies.

Bioinspired Materials Design: An Assessment of Methods to Improve a Text Mining Algorithm for Identifying Biological Material Structural Design Principles

Natural materials are able to achieve a wide range and combination of properties through the arrangement of the material’s components. These biological materials are often more effective and better suited to their function than engineered materials, even with the use of a limited set of components. By mimicking a biological material’s component arrangement, or structure, man-made bioinspired materials can achieve improved properties as well. While considerable research has been conducted on biological materials, identifying the beneficial structural design principles can be time-intensive for a materials designer. Previously, a text mining algorithm and tool were developed to quickly extract passages describing property-specific structural design principles from a corpus of materials journals. Although the tool identified over 90% of the principles (recall), many irrelevant passages were returned as well with approximately 32% of the passages being useful (precision). This paper discusses approaches to refine the program in order to improve precision. The text classification techniques of machine learning classifiers, statistical features, and part-of-speech analyses, are evaluated for effectiveness in sorting passages into relevant and irrelevant classes. Manual identification of patterns in the returned passages is also employed to create a rule-based method, resulting in an updated algorithm. An evaluation comparing the revised algorithm to the previously developed algorithm is completed using a new set of journal articles. Although the revised algorithm’s recall was reduced to 80%, the precision increased to 45% and the number of returned passages was reduced by 22%, allowing a materials designer to more quickly identify potentially useful structures. The paper concludes with suggestions to improve the program’s usefulness and scope for future work.

Model-Based Hazard an Propagation Assessment of Product Changes

The current markets are characterized by an increasing demand for individual products, increasing product complexity and stricter safety regulations. This results in large hazard and safety analysis efforts for each individual product variant. One possible solution to reduce these efforts is the automation of analyses and a preliminary assessment of individual changes. Therefore, several approaches are published to e.g. model safety aspects or evaluate change propagations. However, the approaches fail to directly establish the connection between product changes and safety aspects by a common model. This paper develops a method to identify and assess the potential hazard impact of product changes through a common static model. It builds on a graph-based product model and graph-rewriting. From the state of the art, suitable methods tools and principles are identified and evaluated. Based on this, requirements are derived. The capabilities of existing methods are assessed and the most suitable ones adapted and integrated to the method to assess the potential hazard impact of product changes (MBHPA). The MBHPA reduces the complexity by providing two independent interconnected analyses. To evaluate the product changes, a static propagation analysis is provided. It uses defined graph-rewriting patterns to trace propagations and extract a propagation tree. The affected components in a second step can then be evaluated on their hazard potential. Again graph-rewriting patterns are applied to identify the connected hazards which are visualized in a hazard potential portfolio. The MBHPA is implemented and evaluated with the industrial case of an automated coffee machine. The evaluation underlines that the MBHPA successfully identifies possible propagations and their effect on hazards from a static perspective. It helps to improve safety awareness and traceability and reduces the required experience.

Quantification of Symmetry, Parallelism, and Continuity as Continuous Design Variables for Three-Dimensional Product Representations

This work introduces a methodology to quantify the form of a three-dimensional (3D) product representation using the Gestalt principles of symmetry, parallelism, and continuity, and how they can be used as descriptive parameters in product design. First, consistent quantifications of these three Gestalt principles for parametrized 3D representations in a zero-one scale are presented. Then, a generalized methodology applicable to any product form is discussed. It starts with the identification of important aesthetic forms of the product shape and the Gestalt principles that best related to those forms, and ends with the quantification of these Gestalt principles of a 3D product representation. The expressions to quantify the Gestalt principles in question are validated through an online survey in which subjects indicated how much they recognize symmetry, parallelism, or continuity from irregular shapes. Finally, random-effects ordered logit regression is used to determine if the expressions effectively describe the level of recognition of each Gestalt principle. Results show that the proposed quantifications for symmetry, parallelism, and continuity are congruent with subjects perception of these Gestalt principles, and the implications for designers and future work are discussed. Further implications in the design process of these quantifications include the optimization of the product shape for aesthetic, semantic, and functional goals.

Design Roadmapping: A Framework and Case Study of Planning Development of High-Tech Products in Silicon Valley

We propose a framework for Design Roadmapping that parallels existing product roadmapping and technology roadmapping processes. It leverages three needs we have observed in organizations as they use existing roadmapping processes: (1) to focus on development of customer and user experiences, not just on features; (2) to increase engagement of designers early in the planning process; and (3) to provide a means for rapidly responding to changes in the environment. Design Roadmapping is an attempt to reconcile differences that arise when customer/user needs are not considered simultaneously with technology choices. The proposed Design Roadmapping process assists project prioritization and selection. The process aggregates design experience elements along a timeline that associates key user needs with the products, services and/or systems the organization wishes to deliver. To illustrate the Design Roadmapping process, we conducted a case study in which we applied the Design Roadmapping process to projects undertaken by a large corporation’s innovation lab located in research centers in San Francisco and Mountain View, California, in partnership with corporate stakeholders located in Asia. The five-step Design Roadmapping procedure is provided along with detailed information. The decisions from the Design Roadmapping process have been incorporated into the company’s commercial plans. Key findings in this corporate case study bolster the positive impact of the Design Roadmapping in moving strategic thinking from a technology/feature-driven process to one that is design/experience-driven. It shows how firms might weigh choices between user needs, design principles and technological innovation.

Eco-Feedback Designs: A Balance Between the Quantitative and the Emotional

Eco-feedback design is a strategy for encouraging sustainable behavior by making users aware of the resources they consume. Reminding users of their resource usage can help them understand the environmental impacts of their actions and evoke feelings such as sympathy or responsibility for the environment. This study investigated two aspects of presenting resource usage information in eco-feedback designs: the quantitative clarity of the information, and the strength of emotion evoked by the designs. This paper examines how these two aspects of eco-feedback influence users’ perception and preference for the designs. Four design prompts with different levels of quantitative clarity and emotion were used to generate 16 designs. An online survey with these designs was distributed among students at four universities in two countries. Results from 216 valid responses showed evidence that both the quantitative and emotional aspects are important to the eco-feedback designs. The survey also gathered data about respondents’ knowledge about resource consumption. Results suggested that students in technical majors were generally better at estimating resource consumption, and tended to prefer designs with more quantitative data. In contrast, students in non-technical majors generally made less accurate estimates and tended to prefer designs that evoke stronger emotions. These findings could inform designers on how to make more effective eco-feedback designs to promote sustainable behaviors.