Digital twin and predictive quality solution for insulated glass line

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Aydin G., Tezcan M., Ozgen B., Ozkan T. N.

JOURNAL OF INTELLIGENT MANUFACTURING, vol.36, no.5, pp.3543-3567, 2025 (SCI-Expanded, Scopus)

• Publication Type: Article / Article
• Volume: 36 Issue: 5
• Publication Date: 2025
• Doi Number: 10.1007/s10845-024-02426-y
• Journal Name: JOURNAL OF INTELLIGENT MANUFACTURING
• Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, INSPEC
• Page Numbers: pp.3543-3567
• Keywords: Digital twin, Gas filling process, Insulated glass manufacturing, Predictive quality, Production process, Quality control
• Kocaeli University Affiliated: No

Abstract

This study is an integral part of an international research and development initiative investigating the application of digital twins and predictive quality solutions to enhance quality control and streamline production processes within the insulating glass manufacturing industry. The critical factor influencing the transformation of insulating glass into a high-quality, energy-efficient product is the gas filling rate. Therefore, this study focuses on the real-time monitoring and analysis of the gas filling process. Concurrently, predictive quality solutions are implemented to improve product quality and reduce defects. Consequently, it is evident that these technologies hold significant potential to advance the quality of insulating glass production and promote sustainable production practices on an international scale.