Integrating digital twins in metal sink factories: A pathway to smart manufacturing

Abstract. This study presents the development and validation of a digital twin for the production line of monoblock sinks. The digital twin was created using the AnyLogic simulation platform, integrating both 2D and 3D environments to replicate the factory’s operations. The model simulates the movement of workers and machinery across key stations in the production process, providing detailed insights into resource availability, machine usage, and potential bottlenecks. Validation of the model was conducted through a comparison of simulated production rates with real-world data for key production stations. The results demonstrated a high degree of accuracy, with discrepancies between simulated and actual production times within a few seconds. The digital twin offers a powerful tool for experimentation and optimization, enabling adjustments in process times, workforce allocation, and equipment utilization. This approach not only enhances production efficiency but also provides a reliable platform for future decision-making and process improvements.

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Publication Details

Journal
Materials research proceedings
Published
2024-12-04
DOI
https://doi.org/10.21741/9781644903377-52
Primary Topic
Digital Transformation in Industry
Type
article
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article

Integrating digital twins in metal sink factories: A pathway to smart manufacturing

Vassilios Kappatos
Materials research proceedings
Digital Transformation in Industry
article

Integrating digital twins in metal sink factories: A pathway to smart manufacturing

Vassilios Kappatos
article en

Abstract

Abstract. This study presents the development and validation of a digital twin for the production line of monoblock sinks. The digital twin was created using the AnyLogic simulation platform, integrating both 2D and 3D environments to replicate the factory’s operations. The model simulates the movement of workers and machinery across key stations in the production process, providing detailed insights into resource availability, machine usage, and potential bottlenecks. Validation of the model was conducted through a comparison of simulated production rates with real-world data for key production stations. The results demonstrated a high degree of accuracy, with discrepancies between simulated and actual production times within a few seconds. The digital twin offers a powerful tool for experimentation and optimization, enabling adjustments in process times, workforce allocation, and equipment utilization. This approach not only enhances production efficiency but also provides a reliable platform for future decision-making and process improvements.

Materials research proceedingsVol. 46
Centre for Research and Technology Hellas (GR)
Openalex Percentile: Top 68%
Digital Transformation in Industry
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