Industrial drying of spunlace nonwovens (fibrous materials produced by hydroentanglement using high-pressure water jets) represents one of the most energy-intensive stages of production due to the high water content remaining after the hydroentanglement process and the large thermal energy required for water evaporation. Understanding the relationship between material structure, production parameters, and water removal intensity is therefore essential for improving process efficiency. This study investigates the drying behavior of viscose–polyester spunlace nonwovens using an integrated mass balance and statistical modeling approach based on industrial production data. Process parameters were collected from an industrial SCADA (Supervisory Control and Data Acquisition) monitoring system and combined with laboratory measurements of nonwoven mass per unit area. Experimental results show that 926–1840 kg/h of water can be removed during drying at temperatures below 100 °C, depending primarily on production speed and structural parameters of the material. A multivariate exponential regression model was developed to describe the nonlinear relationship between drying temperature, production parameters, and water removal intensity. The model demonstrated high predictive accuracy when validated with independent test data. The results indicate that mass throughput and structural characteristics dominate the drying process, while temperature variations remain limited by technological constraints. The proposed modeling framework enables predictive control of industrial drying conditions and provides a practical tool for improving energy efficiency in industrial nonwoven manufacturing.
Niedziela et al. (Wed,) studied this question.