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Product design is one of the most important sectors influencing global sustainability, as almost all the products consumed by people are outputs of the product development process. In particular, early design decisions can have a very significant impact on sustainability. These decisions not only relate to material and manufacturing choices but have a far-reaching effect on the product’s entire life cycle, including transportation, distribution, and end-of-life logistics. However, key challenges have to be overcome to enable eco-design methods to be applicable in early design stages. Lack of information models, semantic interoperability, methods to influence eco-design thinking in early stages, measurement science and uncertainty models in eco-decisions, and ability to balance business decisions and eco-design methodology are serious impediments to realizing sustainable products and services. Therefore, integrating downstream life cycle data into eco-design tools is essential to achieving true sustainable product development. Our review gives an overview of related research and positions early eco-design tools and decision support as a key strategy for the future. By merging sustainable thinking into traditional design methods, this review provides a framework for ongoing research, as well as encourages research collaborations among the various communities interested in sustainable product realization.

The issue of environmental sustainability, which is unprecedented in both magnitude and complexity, presents one of the biggest challenges faced by modern society. Engineers, including mechanical engineers, can make significant contribution to the development of solutions to this problem by designing products and processes that are more environmentally sustainable. It is critical that engineers take a paradigm shift of product design i.e. from cost and performance centered to balance of economic, environmental, and societal consideration. Although there have been quite a few design for environment (DfE, or ecodesign) tools developed, so far these tools have only achieved limited industrial penetration: they are either too qualitative/subjective to be used by designers with limited experiences, or too quantitative, costly and time consuming and thus cannot be used during the design process specially during the early design stage. This paper develops a novel, semi-quantitative ecodesign tool that targets specially on early design process. The new tool is a combination of environmental life cycle assessment, working knowledge model, and visual tools such as QFD, functional-component matrix, and Pugh chart. Redesign of staplers is selected as a case study to demonstrate the use of the proposed tool. Efforts are on going to confirm that the new design generated using this new tool does have improved environmental performance.

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The rapid rise in technologies for data collection has created an unmatched opportunity to advance the use of data-rich tools for lifecycle decision-making. However, the usefulness of these technologies is limited by the ability to translate lifecycle data into actionable insights for human decision-makers. This is especially true in the case of sustainable lifecycle design (SLD), as the assessment of environmental impacts, and the feasibility of making corresponding design changes, often relies on human expertise and intuition. Supporting human sense-making in SLD requires the use of both data-driven and user-driven methods while exploring lifecycle data. A promising approach for combining the two is through the use of visual analytics (VA) tools. Such tools can leverage the ability of computer-based tools to gather, process, and summarize data along with the ability of human-experts to guide analyses through domain knowledge or data-driven insight. In this paper, we review previous research that has created VA tools in SLD. We also highlight existing challenges and future opportunities for such tools in different lifecycle stages—design, manufacturing, distribution & supply chain, use-phase, end-of-life, as well as life cycle assessment. Our review shows that while the number of VA tools in SLD is relatively small, researchers are increasingly focusing on the subject matter. Our review also suggests that VA tools can address existing challenges in SLD and that significant future opportunities exist.