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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

System Architecture for Asset Traceability using Digital Product Passports and Fingerprint Technology

Marco Fabio Buecheler (20290857) 19 November 2024 (has links)
<p dir="ltr">Asset traceability systems support sustainable value creation. Use case scenarios include the transition from a linear to a circular economy (CE) and legislative initiatives in Europe and North America. Traceability systems are needed to consistently link physical assets with the corresponding digital life cycle data. However, there is a lack of system architectures for consistent asset life cycle traceability. Therefore, the work proposes a traceability system architecture using digital product passports (DPPs) and fingerprint (FP) technology. By providing asset related data, DPPs increase the transparency across value chain partners. The system architecture uses the Asset Administration Shell (AAS) to create interoperable and standardized DPPs. Besides, consistent product identification (ID) and unique (single occurrence) identifiers are a prerequisite for effective traceability systems. Using natural markers to identify assets can enhance consistent asset traceability in sustainable supply chains. When using FP technology, the inherent surface structure of an asset is captured by an imaging system and then compressed into a digital asset fingerprint. Since assets are not artificially marked, the work investigates the use of Bounding Symbols (BSs) to locate an asset’s fingerprint Region of Interest (ROI). Furthermore, four fingerprint creation algorithms are compared and evaluated regarding their feasibility for asset life cycle traceability. The research validates the proposed system architecture in an experimental setup by using aluminum raw castings (medallions) as the investigated asset type. Key findings include the successful identification of 80 medallions with a 100% success rate. The related fingerprint information was stored in a DPP as an AAS submodel.</p>

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