Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Progress for Life Cycle Sustainability Assessment by Means of Digital Lifecycle Twins - A Taxonomy
    ( 2021)
    Riedelsheimer, Theresa
    ;
    Neugebauer, Sabrina
    ;
    Lindow, Kai
    To understand and optimize the impact of a product along its lifecycle, the consideration of social, economic and environmental factors is of increasing interest for customers and regulating institutions. In this context, Life Cycle Sustainability Assessment (LCSA) is used to monitor and understand the trade-offs of the three sustainability dimensions. Today, LCSA still faces major challenges, such as availability, actuality and validity of data or consistent and appropriate measures to support Design for Sustainability. New technological innovations may support the enhancement of the methodology. In the background of a digitized product and service lifecycle, especially Industry 4.0 technologies, Digital Twins and the integration of Artificial Intelligence may solve data and feedback challenges through new ways of data collection, transfer, validation and intelligent analysis. This paper aims at exploring this potential of new technological innovations for an enhanced LCSA of capital goods and durable consumer goods as well as related services and proposes a taxonomy. Therefore, a literature review to identify existing digital solutions and research gaps is established. For the identified gaps, a new concept, the Digital Lifecycle Twin for LCSA is presented. The authors address both, the positive but also the negative implications put on the LCSA framework from a sustainability perspective. Ultimately, these findings will contribute to the enhancement of the LCSA methodology as well as to the design of a support system to enable environmentally and socially sound design of products and services.
  • Publication
    Feedback to Design with Digital Lifecycle-Twins - literature review and concept presentation
    ( 2018)
    Riedelsheimer, Theresa
    ;
    Lindow, Kai
    ;
    Stark, Rainer
    In this paper, the authors propose a concept for optimizing the design process as well as product-related features and services through learning from Digital Twin data and establishing a continuous feedback loop from downstream phases of the product lifecycle to the design phase. As a first step, a systematic review of existing concepts in literature as well as a gap analysis is conducted. The presented concept details existing Digital Twin concepts and implementations by focusing on the specific objective of realizing Feedback to Design and integrating the lifecycle aspect.