Industrial study on holistic digital factory models

Abstract Although studies have demonstrated the potential of holistic digital factory models, their application in industry remains limited. There is a research gap as to why this is the case. In particular, the starting point of the factory operators and their specific requirements for such models are still unclear. This paper presents a mixed-methods study that addresses the existing research gap regarding the implementation of holistic digital factory models. The study investigates the evolving understanding of factory planning, emphasizing the transition from one-time projects to continuous tasks. The key findings reveal a significant need for cross-life-cycle information continuity, highlighting the importance of collaboration and data integration among stakeholders. The research identifies obstacles to achieving holistic digital factory planning, including knowledge management and data availability challenges. Furthermore, the applicability of existing technologies for holistic digital factory models, such as Building Information Modeling and Digital Twins, is examined, demonstrating their relevance in factory planning. Additionally, it is shown that while there is an apparent demand for standardized methods and tools, many existing methodologies are underutilized. The paper concludes with recommendations to further investigate the contrasts between literature and industry practices, as well as the implementation of shared data environments to enhance the efficiency of factory planning processes.