Assembly Lines in Circulation – Towards a Holistic Framework to Enable the Reuse of Assembly Resources

The research project ALICIA – Assembly Lines in Circulation – will provide a marketplace platform that enables the reuse of second-hand assembly resources. Based on a formalized resource description and AI-based decision-making support, the platform suggests suitable second-hand resources for new assembly lines. For these resources, an Asset Administration Shell (AAS) is developed to integrate them into Industrial Internet of Things (IIoT) systems. In return, the legacy resources can be connected to their Digital Twins (DTs) while complying with data security standards. Further, ALICIA evaluates environmental sustainability aspects measured by Key Performance Indicators (KPIs) as well as worker-centric aspects, e.g., worker skills, when selecting second-hand equipment to reuse in new lines. ALICA also identifies potential ethical impacts and risks caused by the technologies, stakeholders, or the ecosystem's processes to be addressed in designing digital solutions. Besides ALICIA’s core services, developed within the project, the platform will be open to partners to offer their services in the context of a second-hand equipment market, such as equipment health state assessment, repair, and Life Cycle Assessment (LCA), among others. To evaluate the platform‘s business models, a value proposition analysis is conducted, showing how Robotics as a Service (Raas) concepts can address potential stakeholder challenges in the project.

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Publication Details

Published
2025-08-17
DOI
https://doi.org/10.1109/case58245.2025.11163991
Primary Topic
Assembly Line Balancing Optimization
Type
article
Field-Weighted Citation Impact
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article

Assembly Lines in Circulation – Towards a Holistic Framework to Enable the Reuse of Assembly Resources

Simon Thevenin, Sebastian Kurscheid, Hamid Reza Rezaei, Rüdiger Daub et al.
Assembly Line Balancing Optimization
article

Assembly Lines in Circulation – Towards a Holistic Framework to Enable the Reuse of Assembly Resources

Simon Thevenin, Sebastian Kurscheid, Hamid Reza Rezaei, Rüdiger Daub, Wolfgang Vorraber, Philipp Url, Sahar Noori, Ronald L. Larsen, Nora Reinbold, Maximilian Orgler, German Bluvstein, Shamaim Wöss, Emad Yaghmaei
article en

Abstract

The research project ALICIA – Assembly Lines in Circulation – will provide a marketplace platform that enables the reuse of second-hand assembly resources. Based on a formalized resource description and AI-based decision-making support, the platform suggests suitable second-hand resources for new assembly lines. For these resources, an Asset Administration Shell (AAS) is developed to integrate them into Industrial Internet of Things (IIoT) systems. In return, the legacy resources can be connected to their Digital Twins (DTs) while complying with data security standards. Further, ALICIA evaluates environmental sustainability aspects measured by Key Performance Indicators (KPIs) as well as worker-centric aspects, e.g., worker skills, when selecting second-hand equipment to reuse in new lines. ALICA also identifies potential ethical impacts and risks caused by the technologies, stakeholders, or the ecosystem's processes to be addressed in designing digital solutions. Besides ALICIA’s core services, developed within the project, the platform will be open to partners to offer their services in the context of a second-hand equipment market, such as equipment health state assessment, repair, and Life Cycle Assessment (LCA), among others. To evaluate the platform‘s business models, a value proposition analysis is conducted, showing how Robotics as a Service (Raas) concepts can address potential stakeholder challenges in the project.

Centre National de la Recherche Scientifique (FR), Graz University of Technology (AT), Laboratoire des Sciences du Numérique de Nantes (FR), IMT Atlantique (FR), Linz Center of Mechatronics (Austria) (AT), Technical University of Munich (DE), Nantes Université (FR), Delft University of Technology (NL)
Openalex Percentile: Top 64%
Assembly Line Balancing Optimization
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