Issue |
MATEC Web Conf.
Volume 401, 2024
21st International Conference on Manufacturing Research (ICMR2024)
|
|
---|---|---|
Article Number | 05005 | |
Number of page(s) | 6 | |
Section | Life-Cycle Analysis and Sustainable Manufacturing | |
DOI | https://doi.org/10.1051/matecconf/202440105005 | |
Published online | 27 August 2024 |
Large Language Model-aided Life Cycle Analysis for Circular Bio-manufacturing
1 Izmir University of Economics, Department of Interior Architecture and Environmental Design, Fevzi Cakmak, Sakarya Cd. No:156, Balcova/İzmir, Turkey
21 Izmir University of Economics, Department of Industrial Design, Fevzi Cakmak, Sakarya Cd. No:156, Balcova/İzmir, Turkey
* Corresponding author: gozde.turhan@ieu.edu.tr
This paper explores the pivotal role of circular manufacturing methods and tools for biobased materials through an assessment tool built on a large language model (LLM) embedded mobile application. The LLMs, trained on extensive textual datasets, can provide precision and efficiency for the life cycle assessment (LCA) for biobased manufacturing. The tool automates data collection, categorises information from diverse sources, and supports ecological decision-making in material and manufacturing method selection. The research follows a methodology based on three main workflows, including database development, LCA specifications, and the LLM-embedded mobile interface development. Furthermore, the study recognizes the intricacy involved in utilising newly developed materials, especially considering the abundance of available formulations. It questions how the tool adapts to various material and manufacturing options and how it could augment practicality and applicability in real-life design and manufacturing stages. The study demonstrates that the tool offers a comprehensive and critical evaluation of biobased materials for manufacturing towards product development across design domains, unlocking new possibilities at the intersection of ecology, circular design, and digital tools.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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