Optimizing air velocity for energy-efficient and sustainable rubberwood drying kilns

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Abstract

The rubberwood industry is a key player in the global timber market, supplying sustainable wood products to meet increasing demands worldwide. Despite its importance, conventional drying processes are energy-intensive, accounting for a substantial portion of production costs while contributing significantly to carbon emissions. This study presents the development of a real-time monitoring and control system for rubberwood drying kilns, integrating smart infrastructure to enhance process efficiency and sustainability. Predicting moisture content accurately during drying is crucial, as it directly impacts wood quality and process optimization. Traditional methods often struggle with dynamic variations in drying behavior, making precise control challenging. To address this, an artificial neural network-based forecasting model was employed to predict changes in moisture content, enabling more effective process adjustments. Experimental investigations were conducted under controlled laboratory conditions on 75 mm thick rubberwood lumber, with a constant dry-bulb temperature of 75°C and wet-bulb temperature of 50°C. Two air velocities—1 m/s and 3 m/s—were employed consecutively until a final moisture content of 10% was achieved. Results highlight the effectiveness of a two-stage drying strategy, starting with a higher air velocity to accelerate drying, followed by a lower velocity as the drying rate diminishes. Notably, reducing air velocity from 3 m/s to 1 m/s when moisture content fell below 40% resulted in approximately 50% energy savings, primarily through reduced motor speed. This strategic approach minimizes energy consumption while maintaining product quality, offering factories significant operational cost reductions and the potential to claim carbon credits. These findings underscore the scalability of this technology, contributing to more sustainable and efficient production practices in the global timber industry.

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