Digital Twins in High Variety Low Volume environments
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2024-08-28
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en
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In this thesis conditions in organizational structure are discovered for use of a digital twin to optimize the decision-making capacity for a company in a high variety low volume environment. This is done by means of a literature review and interviews at three companies that operate in such environments. The research found that digital twins introduce significant complexity, especially through their reliance on accuracy of a vast amount of complex and real-time data. This complexity often results in a perceived lack of transparency, where digital twins function as "black boxes" that are difficult for operators to fully understand and trust. The conditions identified for successful digital twin implementation include the establishment of standardized architectures, enhanced data transparency through open communication channels, facilitation of collaborative platforms, adoption of continuous improvement practices, and provision of adequate training and skill development for users. The interviewees recognized the challenges of maintaining accurate data inputs and highlighted the complexity of digital twin models. They also recognized the need for regular communication and collaboration between departments. However, there was less recognition of the need for formal training and skill development, suggesting an area to bring attention to in the future.
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Faculteit der Managementwetenschappen