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METHOD FOR THE INTEGRATION OF COMPUTER AIDED MANUFACTURING DATA IN LIFE CYCLE ASSESSMENT

Published online by Cambridge University Press:  19 June 2023

Niklas Quernheim ,
Sven Winter ,
Lars Arnemann  and
Benjamin Schleich
Niklas Quernheim*
Affiliation:
Product Life Cycle Management, TU Darmstadt
Sven Winter
Affiliation:
Product Life Cycle Management, TU Darmstadt
Lars Arnemann
Affiliation:
Product Life Cycle Management, TU Darmstadt
Benjamin Schleich
Affiliation:
Product Life Cycle Management, TU Darmstadt
*
Quernheim, Niklas, TU Darmstadt, Germany, [email protected]

Abstract

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Precise sustainability assessment becomes increasingly important in decision-making, marketing, and regulations. Therefore, reliable and comparable LCA becomes mandatory. Currently, primary data is rarely available due to vastly complex value chains. Secondary data from eco-databases provide a remedy to estimate the sustainability impacts of up- and downstream processes. While giving insights and estimations, this data is seldom fitting exactly to the own processes and lacks comparability. Therefore, this paper proposes a method to close the gap between unreliable secondary data and unavailable primary data. This gap is to be closed by the integration of simulated process data. CAM is a tool during the work preparation to assess the design's manufacturability, decrease set-up times and optimize the NC code. However, integrating DES into LCA is still subject to research and will be discussed in this paper. This paper answers the question of the necessary steps to integrate the simulated production process in an LCA to increase the quality and reliability of sustainability indicators. A method is presented, and the implementation of the steps with the help of a developed assistance system on an example is performed.

Keywords

Life Cycle AssessmentDecision makingComputer Aided ManufacturingSustainabilitySimulation
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2635 - 2644
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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