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BIKINI - Bionics and AI for Sustainable Integration of Product Development for Resource-Efficient Lightweight Construction

Overview

To curb climate change, CO2 emissions must be reduced. One of the key technologies is lightweight design and the CO2 savings that can be achieved during the product use phase - especially in the area of mobility - through weight reduction. Within the framework of the BIKINI joint project funded by the Federal Ministry for Economic Affairs and Energy (BMWi), the application of bionic design algorithms and AI-based assistance services in product development is being researched. A consortium of research institutes, IT partners and engineering service providers has joined for this purpose. Current evaluation criteria of lightweight products such as costs and performance are being expanded to include sustainability aspects such as the holistic CO2 emissions, the resource use of the manufacturing processes and the recyclability of the materials used.

Key Facts

Grant Number:
03LB3018C
Project type:
Sonstiger Zweck
Project duration:
07/2021 - 06/2024
Funded by:
Bundesministerium für Wirtschaft und Energie (BMWE)
Websites:
Homepage
Projektseite des Fachgebietes

More Information

Principal Investigators

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Prof. Dr. Iris Gr??ler

Produktentstehung / Heinz Nixdorf Institut

About the person

Cooperating Institutions

Additive Marking GmbH

Cooperating Institution

Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung

Cooperating Institution

Atos Deutschland

Cooperating Institution

EDAG Engineering Group AG

Cooperating Institution

FEYNSINN EDAG Production Solutions GmbH & Co. KG

Cooperating Institution

Forschungszentrum Jülich

Cooperating Institution

Krause DiMaTec GmbH Deutschland

Cooperating Institution

rhaug GmbH

Cooperating Institution

Publications

Handling of uncertainties in the design of sustainable Additive Manufacturing products by merging Design-for-X and Scenario-Technique
I. Gr??ler, I. Mozgova, J. Pottebaum, M. Ott, P. Jung, P. Hesse, in: 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering, Elsevier, 2024, pp. 549–554.
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