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Supply chain collaboration as a facilitator of circular economy for bio-based food packagingHolesova, Gabriela, Ivashneva, Ekaterina January 2021 (has links)
The amount of food packaging waste is one of the issues associated with increasing global population and corresponding increase in consumption rate of packaged foods. Traditional plastic food packaging derived from fossil fuels imposes a significant environmental threat. There are sustainable bio-based alternatives developed to substitute traditional plastic packaging that are implemented in circular economy business models. These solutions often utilise collaboration to be implemented, however, there is a lack of research on the collaborative processes that enable circular economy in bio-based food packaging. In this thesis we examine what collaborative processes are being used in the bio-based packaging supply chain and how these processes help with facilitating the implementation of circular economy in the packaging production. Moreover, this thesis also investigates what are the barriers that the packaging producers face as they collaborate toward a circular economy. Therefore, we use qualitative interviews with representatives of bio-based food packaging companies and study the theories of supply chain collaboration and circular economy such as resource based view, transaction cost economics and various iterations of circular supply chain management models. We find that bio-based food packaging producers collaborate externally with customers, suppliers and internally among organisational teams to enable the circular economy of bio-based alternatives to conventional plastics. We also find that collaboration for circular economy in bio-based food packaging solutions is challenged by cultural differences, varying regulations among countries, opportunistic behaviour across the supply chain, insufficient organisation of communication between collaborators as well and misalignment of their interests. We contribute empirical evidence of collaborative processes across bio-based food packaging supply chains providing a ground for further research streams across the aspects of collaboration for circular economy.
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System Architecture for Asset Traceability using Digital Product Passports and Fingerprint TechnologyMarco 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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