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Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities.
Devarajan Ramanujan1, William Z Bernstein2, Senthil K Chandrasegaran3
1Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.
Journal of Mechanical Design (New York, N.Y. : 1990)
|November 25, 2017
Summary
Visual analytics (VA) tools can bridge the gap between complex lifecycle data and human decision-making in sustainable lifecycle design (SLD). These tools enhance expert insight by integrating data processing with user-driven analysis for better environmental impact assessments and design improvements.
Area of Science:
- Engineering
- Computer Science
- Environmental Science
Background:
- Data collection technologies are rapidly advancing, creating opportunities for data-rich lifecycle decision-making.
- Translating complex lifecycle data into actionable insights for human decision-makers remains a significant challenge, particularly in sustainable lifecycle design (SLD).
- Current SLD practices often rely heavily on human expertise and intuition for environmental impact assessment and design change feasibility.
Purpose of the Study:
- To review existing research on visual analytics (VA) tools developed for sustainable lifecycle design (SLD).
- To identify current challenges and future opportunities for VA tools across various lifecycle stages.
- To explore how VA can support human sense-making by combining data-driven and user-driven methods in SLD.
Main Methods:
- Systematic review of previous research on visual analytics (VA) tools in sustainable lifecycle design (SLD).
- Analysis of VA tool applications across different lifecycle stages: design, manufacturing, distribution & supply chain, use-phase, and end-of-life.
- Examination of VA's role in life cycle assessment (LCA) and its integration with human expertise.
Main Results:
- The body of research on VA tools for SLD, while currently small, is experiencing increasing attention from researchers.
- VA tools demonstrate potential in addressing existing challenges within SLD by integrating computational data processing with human expert guidance.
- Significant opportunities exist for the further development and application of VA tools to enhance decision-making throughout the product lifecycle.
Conclusions:
- Visual analytics (VA) offers a promising approach to enhance sustainable lifecycle design (SLD) by facilitating the interpretation of complex lifecycle data.
- The integration of VA tools can empower human decision-makers by leveraging both data processing capabilities and expert domain knowledge.
- Further research and development in VA tools are crucial for realizing their full potential in supporting sustainable practices across all lifecycle stages.
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