Sustainable product design addresses sustainability challenges through product development processes and tools. The number of sustainable design methods has been increasing rapidly in recent years. Still, their adoption is limited, and many of these methods exclusively focus on the environmental impacts of products rather than taking a holistic perspective that includes social and economic sustainability. This research provides a holistic sustainable design framework by integrating change propagation methods and sustainable design tools to enable simultaneous consideration of design parameters’ impacts on the three dimensions of sustainability. A reusable water bottle is used to demonstrate the application of the proposed holistic sustainable design (HSD) framework. A multi-domain matrix (MDM) is used to capture the interdependencies among these design parameters of the product, and then equations are defined to quantify them. Life cycle assessment (LCA) is then automated to evaluate the product’s environmental impacts, and the investigation of its results provides details to identify critical unit processes contributing to the environmental categories. Sensitivity analyses reveal how changes to individual design parameters propagate through the model to influence the three dimensions of sustainability. Ultimately, the designer can select optimal design parameter values to balance environmental, social, and economic sustainability.

As electricity systems evolve, accurately modeling consumer behavior is crucial for policy design and system planning. This study examines how different approaches to initializing consumer agents in electricity market simulations impact sustainability outcomes. We compare three strategies: (1) aggregate public data distributions, (2) aggregate survey data distributions, and (3) individual-level survey data from 839 respondents. Using New Jersey's electricity market as a case study, we simulate household decisions on solar investments, clean-energy participation, and consumption over 40 years (2010-2050) with an agent-based model, running 500 Monte Carlo simulations per approach, validated against 2010-2020 historical data. Results reveal important trade-offs between modeling approaches. Aggregate public data models most accurately track historical consumption and energy burden, while survey-based models, particularly individual-level, predict higher renewable adoption and program participation rates. The individual survey methodology captures greater behavioral heterogeneity and socioeconomic disparities, revealing potential energy justice concerns that remain hidden in aggregate models. Despite these differences, all approaches maintain comparable accuracy in predicting system-level metrics like total electricity consumption. These findings demonstrate that modeling outcomes are very sensitive to initialization highlighting the importance of aligning model design with the intended research question and available data.

Generally, the focus of undergraduate engineering programs is on the development of technical skills and how they can be applied to design and problem solving. However, research has shown that there is also a need to expose students to business and society factors that influence design in context. This technical bias is reinforced by the available tools for use in engineering education, which are highly focused on ensuring technical feasibility, and a corresponding lack of tools for engineers to explore other design needs. One important contextual area is market systems, where design decisions are made while considering factors such as consumer choice, competitor behavior, and pricing. This study examines student learning throughout a third-year design course that emphasizes market-driven design through project-based activities and assignments, including a custom-made, interactive market simulation tool. To bridge the gap between market-driven design and engineering education research, this paper explores how students think about and internally organize design concepts before and after learning and practicing market-driven design approaches and tools in the context of an engineering design course. The central research question is: In what ways do student conceptions of product design change after introducing a market-driven design curriculum? In line with the constructivism framework of learning, it is expected that student conceptions of design should evolve to include more market considerations as they learn about and apply market-driven design concepts and techniques to their term projects. Four different types of data instruments are included in the analysis: Concept maps generated by the students before and after the course, open-ended written reflection assignments at various points in the semester, surveys administered after learning the market simulation tool and at the end of the course, and final project reports in which student teams listed their top 3-5 lessons learned in the course. Using the changes between the pre- and post-course concept maps as the primary metric to represent evolving design conceptions, data from the reflections, surveys, and reports are evaluated to assess their influence on such learning. Because market-driven design is a multi-faceted topic, a market-driven design is hierarchically decomposed into specific sub-topics for these evaluations. These include profitability (which itself encompasses pricing and costs), modeling and simulation, and market research (which encompasses consumers and competition). For each topic, correlation analyses are performed and regression models are fit to assess the significance of different factors on learning. The findings provide evidence regarding the effectiveness of the course's market-driven design curriculum and activities on influencing student conceptions of design.

Despite the efforts to increase the pace of sustainable design adaptation in industries, several systemic barriers currently hinder this shift. The design for sustainability methods has been utilized in product design and development phases in many industries. However, they do not have a holistic approach that can capture these systemic drivers and barriers while considering all three pillars of sustainability: environmental, social, and economic. This research proposes a systems thinking approach toward sustainable design that can collectively consider different aspects of the production system in an attempt to resolve the multidimensional challenges within the design for sustainability. A reusable water bottle is selected as the case study to illustrate the applications and limitations of this approach. In addition, this case study also helped to define the boundaries and stakeholders involved in the system and reduce the abstractions. The results from this analysis are demonstrated as a causal loop diagram that could be implemented in a system dynamics model to quantitively identify the systematic forces and leverage points driving sustainable design in product development. The comprehensive understanding provided by this analysis revealed many improvement possibilities, trade-offs, and feedback loops within the system that can assist in realizing sustainable product design proliferation and associated positive sustainability outcomes.

Occupant safety is a top priority of military vehicle designers. Recent trends have shifted safety emphasis from the threats of ballistics and missiles toward those of underbody explosives. For example, the MRAP vehicle is increasingly replacing the HMMWV, but it is much heavier and consumes twice as much fuel as its predecessor. Recent reports have shown that fuel consumption directly impacts personnel safety; a significant percentage of fuel convoys that supply current field operations experience casualties en route. While heavier vehicles tend to fare better for safety in blast situations, they contribute to casualties elsewhere by requiring more fuel convoys. This study develops an optimization framework that uses physics-based simulations of vehicle blast events and empirical fuel consumption data to calculate and minimize combined total expected injuries from blast events and fuel convoys. Results are presented by means of two parametric studies, and the utility of the framework is discussed in a dynamic context and for evaluating casualty-reduction strategies.

To achieve triple bottom line sustainability, a system requires a balance of its social, economic, and environmental axioms. This multi-dimensional system has multiple stakeholders with different objectives acting within the system, leading to an increased level of complexity. Product design is an area with significant potential to achieve sustainable development, which is also influenced by policies. Product designers/managers and policymakers have been identified as critical stakeholders within this complex system, and their decisions directly affect the transition toward sustainable product design. However, these stakeholders have different perspectives on sustainability, and there is a lack of understanding of the main characteristics of a sustainable design system and its requirements. This research aims to find a detailed and unified understanding of these stakeholder’s perspectives, practices, and requirements. An online survey investigated the views of engineers/managers and policymakers in the United States to find their definitions of sustainability, their assessment methods, drivers, and barriers of sustainability. Finally, the participants were asked to identify their requirements for a sustainable design tool that can assist them effectively in designing a sustainable product. Considering the exploratory nature of this study, a targeted sample of 50 participants was selected to capture in-depth, qualitative insights, enabling a nuanced understanding of this complex system. The open-ended questions were designed to obtain detailed responses, which were analyzed qualitatively to develop a comprehensive view of the current state and future requirements for sustainable design tools. This targeted approach allowed the study to probe deeply into each stakeholder’s frame of reference, facilitating the identification of critical factors for a successful transition to sustainable design in both industry and policy. The results identified the critical factors that contribute to a successful transition toward sustainable product design in industry and policies while the requirements found in this study provided a road map to meet the diverse needs of these stakeholders.

AbstractThe sustainable design transition has proven to be a challenging process, in part due to the diverse set of stakeholders, which includes the general public, policymakers, scientific researchers, and businesses. In prior work, the interconnected relationships among systematic drivers and barriers for sustainable design were identified and mapped using a causal loop diagram at a relatively abstract level. To further understand and characterize this complex system, this research aims to identify the relationship strength levels among the variables in the system, as indicated by previous research identified in the literature. In addition, the knowledge maturity levels of these identified relationships are specified to illustrate strengths and gaps in the literature. The findings are used to create a refined system representation that illustrates the power dynamics between systemic driving forces to sustainable design transitions. The results of this work reveal valuable insights about the linkages among the driving forces of sustainable design transitions that can be used as a foundation for further investigation, such as experiments and data analytics that can better quantify these relationships.

In undergraduate engineering programs, recent emphasis has been placed on a more holistic, interdisciplinary approach to engineering education. Some programs now teach product design within the context of the market, extending the curriculum to topics outside of scientific labs and computational analysis. This study analyzes survey and concept map data collected from 154 students in a third-year engineering design course. The aim is to evaluate the impacts of student backgrounds and experiences on their mental models of product design. Data were gathered from surveys on student backgrounds and experiences, along with concept maps that were generated by the students on the first day of a product design class. The concept maps were analyzed in a quantitative manner for structural and thematic elements. The findings show that several background attributes influence student conceptions of product design. Academic major appeared to have the largest impact on a variety of variables. Additionally, prior work experience, enrollment in a master’s program, and the presence of an engineering role model at home all showed significant impacts on design conceptions. By analyzing and understanding unique backgrounds of students, educators can adjust their curricula to more effectively teach design concepts to students of various backgrounds and experiences.

Interactive dashboards are decision support tools that enable users to explore the relationships between their decisions and the consequences of those decisions. These dashboards in previous research have been proven to be most effective when customized to the specific context of the decision scenario. The objective of this project is to design an interactive dashboard using best practices in optimization and strategic decision-making, for the application of an artillery system derived from publicly available sources. Using Python's dash library, the resulting dashboard enables users to explore design decisions, model mission success likelihood, optimize the design, explore Pareto-optimal trade-offs, trace performance improvement goals back to design parameters, and compare designs with existing systems. The dashboard is described in detail, and several use cases are put forward to illustrate the functionality and implementation scenarios for such an interactive dashboard for complex decision analysis.

Residential electricity consumption is responsible for a significant portion of greenhouse gas emissions each year in the United States. Conserving energy and increasing demand for renewable energy sources are two ways individuals can help reduce the negative impacts of electricity consumption. Research on monetary incentives and fees has demonstrated their potential to encourage pro-environmental behaviors, but knowledge of their effects on sustainable energy behaviors in particular is incomplete. In this chapter, an investigation of three levels of incentives and fees framed to encourage either energy conservation or investment in renewable energy is conducted to determine their effect on consumer energy behavioral intentions. Through a survey that exposed participants to incentives and fees on bill graphics, participants' perceptions and intended future behaviors were measured. Data were collected about consumers' willingness to pay to participate in clean energy programs, invest in solar panels, and upgrade to efficient appliances. Results of the survey experiment show that exposure to low levels of incentives and fees significantly increased participants' intentions to participate in pro-environmental behaviors and willingness to pay for solar panels when compared to a control group, while high incentive and fee values were no longer effective. Moderate and high incentive and fee levels were, however, effective in increasing participants' perceived costs and benefits from participating in energy-efficient behaviors. Finally, the framing of the incentives and fees was not found to be significantly influential with respect to participant perceptions and intended energy behaviors.

Challenges posed by climate change are increasing, and residential electricity use is a major contributor. Two ways for individuals to help mitigate this issue are reducing electricity consumption and investing in renewable energy sources. A large body of research has shown that social norms are effective in encouraging various pro-environmental behaviors such as energy use conservation, but less information is available about their ability to encourage investment in renewable energies. Research on incentives and fees has also demonstrated their potential impacts on pro-environmental behaviors in general, but it is less comprehensive regarding sustainable energy behaviors specifically. The combined influence of social norms with incentives or fees on pro-environmental energy behaviors has yet to be explored in the literature. In this study, three experiments are conducted to investigate norms, incentives and fees, and their combined effect on pro-environmental energy decisions. Through surveys that exposed participants to each of these stimuli, participants' attitudes, perceptions, and intended behaviors were measured. Data were collected about various consumer energy decisions along with the consumers' willingness to pay for renewable energy. Results of the survey experiments show that exposure to incentives and fees framed to reduce consumption significantly increased participants’ perceptions of norms and willingness to pay for solar panels when compared to a control group, whereas other manipulations such as social norms and incentives and fees framed to motivate clean energy investments were not impactful on perceptions and intended behaviors. These results uncover the potential to decrease emissions resulting from residential electricity use by introducing incentives and fees on electricity bills and motivating individuals to reduce their consumption and invest in solar panel systems. These behavior changes will contribute to the sustainable development of electricity markets, reducing emissions and costs for individuals while increasing the adoption of renewable energy.

This study investigates how interactive dashboards influence decision making by exploring how specific dashboard features impact design task performance, efficiency, understanding, and confidence. An experiment was conducted in which undergraduate student participants were given a design activity and randomly assigned to one of five dashboards, each using the same underlying functions but varying in the visualization features employed. These features include different graphical representations of the design decision inputs and performance outputs. Participants were first asked to use their assigned dashboard to design a catapult system that maximizes launch distance while meeting requirements related to height, weight, and cost. Following the design task, they were asked a series of questions about their experiences with the dashboard and their understanding of the catapult model. A between-subjects analysis then evaluated how the dashboard design influenced various outcomes of interest. The results show that students who used the most feature-rich dashboard did not perform objectively better than those with the most feature-sparse dashboard, though their self-reported performance was higher. The performance of female versus male participants was also compared, with no significant differences found. The findings support the notion that dashboards should be designed with minimal features to convey the necessary information, and they also point out the disconnect between objective performance and user-assessed performance with interactive dashboards.

The number of sustainable design methods emerging in recent years has increased due to global environmental concerns. Several proposed methods focus exclusively on the environmental impacts of products rather than taking a holistic perspective that includes social and economic sustainability. Despite the advancements in tools for incorporating sustainability in the product design phase, designers are not universally adopting these tools mainly due to their fragmented or underdeveloped characteristics. This research aims to integrate change propagation and sustainable design tools within a holistic framework that can enable simultaneous consideration of design parameters’ impacts on the three dimensions of sustainability. A reusable water bottle is used to demonstrate the application of the proposed holistic, sustainable design framework. The interdependencies among these design parameters are captured using a multi-domain matrix (MDM), and then equations are defined to quantify these dependencies. Life cycle assessment (LCA) is then performed in an automated way to evaluate the product’s environmental impacts, and the investigation of its results provides details to identify critical unit processes contributing to the environmental categories. Using this framework, sensitivity analyses are able to reveal how changes to individual design parameters propagate through the model to influence the three dimensions of sustainability.

Education researchers have observed a disconnect between the goals of the current educational system and the practical application of professional skills outside the classroom. Skills such as creative thinking, knowledge of engineering science, global thinking, and cross-cultural communication should be honed in addition to technical engineering skills. These skills are often taught in engineering design courses. The purpose of this study is to evaluate student learning of market concepts in a design course, with an emphasis on the use of a market simulation tool to forecast consumer choice among competing products, by analyzing written reflections, course surveys, and project reports. Specifically, we assess the self-reported learning value of using an interactive market simulation tool in the classroom. The study employed a descriptive case study to understand the value of a market simulator in an engineering design course. Several sources of data from student reflection assignments, the "lessons learned"segment of the final report, and class surveys were collected at multiple points in the semester and analyzed through a combination of qualitative and quantitative approaches. Based on Kember's level of reflection framework, we found that students' levels of reflection changed from mostly level 2 (understanding) to level 3 (reflection) between the fifth and thirteenth weeks of the course. We did observe a decrease in mentions of the value of the market simulator and an increase in acknowledging difficulties, which may show how students' response to the market simulator changes as they reflect again and become more aware of the complexity of the design process as it relates to the market. The key takeaways in the teams' final reports showed parallels with the course objectives. Our results show reflective practice is an effective instructional strategy for students to develop holistic self-regulated learning and professional skills. Themes that pertain to the concepts in the design course emerged and became significant indicators of understanding and critical reflection of the design process as a whole. Team reports on "lessons learned"signify that prior reflective practice encourages students to be more aware of their learning outcomes and the importance of the use of learning tools to achieve these goals.

Improving engineering design in the context of market systems requires a deep understanding of the decision-making processes of multiple interacting stakeholders and how they affect the success of new products. One key group of stakeholders in this system is consumers, who make purchase choices that directly influence each product’s market share and profits. Since real-world individual decisions are influenced by social communications, supporting product development efforts with social network analysis can enable producers to predict demand much more accurately.This article presents an agent-based modeling (ABM) framework for design for market systems analysis that incorporates social network word-of-mouth (WOM) recommendations. To investigate influences of homophily-driven WOM and network structures on consumer preferences and the prediction of market demand, the random and small-world networks are generated based on the concept of homophily to study the differences in the emergent system-level behaviors. We compare the output of the models against a similar model that excludes WOM influences, using a case study of the top-selling midsize sedans in the US automobile industry. The results show that the addition of WOM improves the ability to accurately forecast consumer demand in a statistically significant way. This suggests that producers who invest in supporting their product development efforts with design for market systems analyses that account for social networks may be able to better optimize their decision-making and increase their market success.

Background Engineering education traditionally emphasizes technical skills, sometimes at the cost of under-preparing graduates for the real-world engineering context. In recent decades, attempts to address this issue include increasing project-based assignments and engineering design courses in curricula; however, a skills gap between education and industry remains. Purpose/Hypothesis This study aims to understand how undergraduate engineering students perceive product design before and after an upper-level project-based design course, as measured through concept maps. The purpose is to measure whether and how students account for the technical and nontechnical elements of design, as well as how a third-year design course influences these design perceptions. Design/Method Concept maps about product design were collected from 105 third-year engineering students at the beginning and end of a design course. Each concept map's content and structure were quantitatively analyzed to evaluate the students' conceptual understandings and compare them across disciplines in the before and after conditions. Results The analyses report on how student conceptions differ by discipline at the outset and how they changed after taking the course. Mechanical Engineering students showed a decrease in business-related content and an increased focus on societal content, while students in the Engineering Management and Industrial and Systems Engineering programs showed an increase in business topics, specifically market-related content. Conclusion This study reveals how undergraduate students conceptualize product design, and specifically to what extent they consider engineering, business, and societal factors. The design courses were shown to significantly shape student conceptualizations of product design, and they did so in a way that mirrored the topics in the course syllabi. The findings offer insights into the education-practice skills gap and may help future educators to better prepare engineering students to meet industry needs.

One of the many challenges that engineering designers face today is a deficiency in practical and value-adding design methodologies that consider sustainability. Typically, design for sustainability (DfS) principles that address environmental and social impacts are not prioritized at the same level as economic, physical, and functional needs. Additionally, many newly-introduced DfS methodologies are fragmented and underdeveloped. Furthermore, many methods are catered towards specific niche product domains or corporate workflows, making the application of these methods across a wide range of problems and products a challenge. By investigating the tools and methods available for DfS and identifying their application and limitations, this study explores the integration of design structure matrices (DSMs) and Life Cycle Assessment (LCA) tools to improve DfS. The expectation is that an integrated DSM and LCA will allow designers to explore how a single design change may propagate through to specific changes in environmental and social impacts. The initial development of a full DSM and LCA is demonstrated through two case studies of a reusable water bottle and a micro-pump, showing which components, materials, and processes have the most significant environmental impacts. The results illustrate the value in applying this approach, which may be suitable across a wide range of existing products in an effort to improve DfS.

As electricity consumption significantly contributes to carbon dioxide emissions in the U.S., increased renewable energy utilization and individual behavior changes could combine to substantially decrease the carbon footprint of the sector. This study proposes an agent-based modelling (ABM) framework of the New Jersey electricity market that features consumer and producer agents, each defined by a unique set of attributes. The consumer agents are capable of making decisions about energy use, opting into a clean energy program, and investing in solar panels, while the producer agents decide when to retire and introduce power plants of each type. The model is used to simulate agent behavior and to thereby explore the resulting system outcomes. The results show how ABM is an effective modeling technique for energy markets, upon which we may introduce more market complexities such as compound and dynamic policy scenarios as well as social network analysis.

In product design, there is often a disconnect between the engineers creating the product and the marketing team determining the best characteristics for the product. The research areas of “design for market systems” and “decision-based design” seek to bridge that disconnect through quantitative approaches that facilitate simultaneous technical design and marketing decisions. However, these market driven design frameworks have been primarily evaluated in the context of industry case studies, with limited integration into engineering education. This article presents the development and implementation of a simulation tool for teaching market-driven design in undergraduate engineering design courses. This classroom tool demonstrates the basic relationships between product design decisions, pricing and marketing choices, and predicted market success, by simulating the interactions among producers and consumers in a market system. The product attributes influence the cost and consumer utility of the product, which, along with price, affect market dynamics. The simulator was implemented in a third-year undergraduate design course to introduce the concept of market-driven product design, allowing student design teams to assess the impacts of different design variables on the market success of their design projects. Surveys and written reflections by the students were used to evaluate the simulator’s value in contributing to self-reported learning. The results showed that a majority of students expressed that the simulator provides a meaningful and engaging way to learn about market-driven design concepts.

The design of autonomous vessels is associated with unique opportunities and challenges. As naval architects, we rely on 10,000+ years of collective experience in the design of manned boats. However, with the emergence of unmanned surface vessels, there may be benefits in modifying early design phase procedures, as these vessels will have fundamentally different requirements. The aim of this study is to devise and test a system optimization approach particularly aimed at autonomous vessels. A small-scale autonomous sailing surface vessel (Maribot Vane) has been used as a case study. This paper details the process of applying a multidisciplinary, multi objective, reliability-based design optimization (RBDO) approach at the conceptual design stage of the Maribot Vane, in order to minimize the system cost and the probability failure under anticipated operational conditions. The results will inform the designers of the new platform about the trade-offs between cost and reliability, as well as the optimal selection of main particulars for the detailed design stage and finalization of the hull design. Additionally, future autonomous ship design will benefit from the multidisciplinary approach put forward in this paper, as it allows designers to rigorously explore optimal design concepts and tradeoffs and support key early-stage design decisions.