Journal of Integrated Design and Process Science

As sustainability becomes increasingly important, product design is taking a proactive role in producing products that are both useful and sustainable. This paper introduces and discusses a tool named Environment-based life cycle decomposition (eLCD) to adapt the Environment-based Design (EBD) methodology to sustainable design. The eLCD brings to EBD three major features: 1) a holistic environment structure for sustainable conceptual design, 2) an effective and efficient tool for collecting information for sustainability decision-making, and 3) an analysis tool that takes sustainability as an integral part of the design rather than as a burden. The environment of a product is everything except the product itself, which can be defined in three dimensions, namely, environment types, life cycle events, and life cycle time. The environment types are designated as natural, built (including physical artifact and digital artifact), economic, and social environment. The eLCD provides an effective template for information collection to support the design decision-making process. The effectiveness of eLCD is demonstrated by its application to the upscaling of a wind turbine, where an energy storage system is introduced to make full use of wind energy with the least waste in serving the electricity demand.

Current appropriate technology promoting social sustainability for rural, underprivileged populations is often plagued by lack of affordability, maintenance, and personal training, and is also empathetically disconnected from local people and culture. This study proposes criteria for balancing design thinking processes and appropriate technology for social sustainability. In this study, we concretized five assumptions for design thinking processes: user-oriented design with mass productivity; reiterative nature through user satisfaction surveys; affordability for purchase, maintenance, and repair services; local appropriateness; and eco-friendliness with environmental sustainability. Next, we applied the criteria to 28 representative cases from the water, energy, health, shelter, and transportation fields. The cases were evaluated using qualitative content analysis. Findings show that the criteria are necessary for setting economic, social, and environmental development goals for underprivileged regions after considering local contexts. Cultural empathy and collaboration with locals are key for finding practical solutions and co-creating options iteratively. Further, the cases were compared quantitatively using radar diagrams, histograms, and graphs showing average values and standard deviations, providing an objective measure for appropriate technology. Notably, both qualitative and quantitative approaches can serve as useful guidelines for designers, developers, and local users when developing appropriate technology for social sustainability in underprivileged regions.

The paper aims at presenting 4D printing as a research-intensive technology from a critical external perspective. It provides a comprehensive discussion on the possible future of this emerging domain and also highlights weaknesses and strengths of applying a disruptive or incremental research strategy. Most scientific research efforts in 4D printing contribute to developing the spectrum of possible changes by investigating stimulus/smart materials combinations with additive manufacturing technologies. Although the current results are spectacular, the performances are still far from the basic requirements expected in the industry. The paper highlights the current limitations and trends towards incremental research strategies and argues in favor of risk-taking and the disruptive nature of research to make leaps that benefit society. Even if transgressive promises are associated with this technology with high growth potential in academic research, where creativity is involved and related invention derived, targeted applications are far from being achieved leading to a risk of the slow death of the field and unsatisfactory innovation. Based on this assessment, it appears that close fields in a situation of possible disciplinary porosity can – with a little openness and some creativity – move away from the current highly self-centered work to try to rekindle 4D printing, provided that risk-taking in interdisciplinary research is better supported. If creativity and interdisciplinary project management for innovation are to be promoted, the organizational context must be conducive to risk-taking for this redeployment.

Charging network scheduling for battery electric vehicles is a challenging research issue on deciding where and when to activate users’ charging under the constraints imposed by their time availability and energy demands, as well as the limited available capacities provided by the charging stations. Moreover, users’ strategic behaviors and untruthful revelation on their real preferences on charging schedules pose additional challenges to efficiently coordinate their charging in a market setting, where users are reasonably modelled as self-interested agents who strive to maximize their own utilities rather than the system-wide efficiency. To tackle these challenges, we propose an incentive-compatible combinatorial auction for charging network scheduling in a decentralized environment. In such a structured framework, users can bid for their preferred destination and charging time at different stations, and the scheduling specific problem solving structure is also embedded into the winner determination model to coordinate the charging at multiple stations. The objective is to maximize the social welfare across all users which is represented by their total values of scheduled finishing time. The Vickrey–Clarke–Groves payment rule is adopted to incentivize users to truthfully disclose their true preferences as a weakly dominant strategy. Moreover, the proposed auction is proved to be individually rational and weakly budget balanced through an extensive game-theoretical analysis. We also present a case study to demonstrate its applicability to real-world charging reservation scenarios using the charging network data from Manhattan, New York City.