2026-04-20T23:39:01Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/69242026-03-17T07:57:52Zcom_20.500.11984_473col_20.500.11984_478

Peña Mangas, David Cernuda, Carlos Reguera-Bakhache, Daniel 2025-03-26T08:05:08Z 2025-03-26T08:05:08Z 2025 1526-6125 https://doi.org/10.1016/j.jmapro.2025.03.031 https://hdl.handle.net/20.500.11984/6924 Viscosity plays a key role in glass container manufacturing, directly impacting product quality and consistency. To date, online measuring of this property during the glass manufacturing process has been both difficult and costly. This study proposes and validates a data-driven approach to develop a soft sensor for measuring glass viscosity. This method employs data on the height of the rotating tube at the forehearth outlet, along with the corresponding glass temperatures. To validate the approach, viscosity estimates are applied to predict glass gob length. Analysis of over 70 production days across various operations demonstrates high predictive accuracy on a per-job basis, with and MSE values consistently above 0.80 and below 1 millimeters, respectively, and reaching over 0.95 for certain jobs. Here, job refers to the continuous production of a single type of container on the production line. Additionally, an aggregate model across all data achieves a predictive accuracy of MSE = 3.80 millimeters. The proposed methodology offers a reliable means to monitor and control glass viscosity, enhancing production efficiency and product quality in the glass container industry. eng © 2025 The Society of Manufacturing Engineers Glass viscosity Glass container Soft sensor Tube height ODS 9 Industria, innovación e infraestructura ODS 12 Producción y consumo responsables Data-driven glass viscosity soft sensor development and validation in a glass container manufacturing line http://purl.org/coar/resource_type/c_6501