Browsing by Author "Löffler, Stefanie"

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    Human-robot collaboration for efficient circularity decision-making for end-of-usage products
    (Stellenbosch : Stellenbosch University, 2024-03) Löffler, Stefanie; De Kock, Imke ; Braun, Anja; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.
    ENGLISH ABSTRACT: As we move into industry 5.0, the traditional linear economic model is proving unsustainable in the face of resource depletion and climate change. The circular economy offers a more promising path, shifting away from the take-make-dispose approach to create a more sustainable and resilient future. The circular economy focuses on resource efficiency, reducing waste, and preserving value, challenging the traditional "end of life" concept for products. However, the transition is challenging due to many products not being designed for recovery, hindering the shift from a linear to a circular product life cycle. This thesis proposes a human-robot collaboration to improve circularity decision-making for end-of usage products to enable the circular economy. Methodologically, the thesis follows the design science research approach and reviews the literature systematically to provide a generic understanding of the knowledge base and the application domain. Using this knowledge the thesis underscores the integration of human-robot collaboration into decision-making processes, emphasizing the economic, environmental, and social factors as well as product and production related information crucial for well-informed decisions within the circular economy. It explores the joint decision-making process and highlights the pivotal role of human-robot collaboration in achieving sustainability and circularity in product lifecycle management by elaborating on the unique strengths of both humans and cobots. For this, this thesis provides skill profiles of the human operator and the cobot focusing on the cognitive abilities of individuals and the analytical prowess of cobots. Additionally, the recovery strategies of the circular economy are examined for their compatibility with human-robot collaboration, and the integration of advanced technologies such as sensors and machine learning are explored. Those findings resulted in a generic decision-making framework integrating the skills of human operators and cobots to assign products to the optimal recovery strategy. For the evaluation, a case study in a collaborative environment is conducted. For this, a user friendly graphical user interface is chosen to deploy a developed machine-learning algorithm for image classification in a workstation where a cobot and a human operator execute the decision process following the framework.