Author(s)
Deverajan Ramanujan, William Z. Bernstein, Senthil K. Chandrasegaran, Karthik Ramani
Abstract
The rapid rise in technologies for data collection across the entire lifecycle creates an unmatched opportunity to advance the use of data-rich tools for decision-making in lifecycle design. 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 sensemaking in SLD requires the use of both, data-driven methods---that gather, process, and summarize the data---as well as user-driven methods---that allow input of expert domain knowledge or data-driven insights---while exploring lifecycle data. A promising approach for combining the two is through the use of computer-supported, interactive, visual tools. In this paper, we review previous research that has created visual analytics (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 topic. Our review also points to the fact that VA tools can potentially address existing challenges in SLD and that significant future opportunities exist.
Citation
Journal of Mechanical Design
Keywords
visual analytics, sustainable manufacturing, sustainable design, lifecycle design
Citation
Ramanujan, D.
, Bernstein, W.
, Chandrasegaran, S.
and Ramani, K.
(2017),
Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities, Journal of Mechanical Design, [online], https://doi.org/10.1115/1.4037479, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=922975 (Accessed April 24, 2026)
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