Abstract:
Tea industry in Sri Lanka holds significant economic importance, contributing
substantially to the country's overall revenue and foreign exchange earnings. However,
the industry faces a critical challenge in the form of high production costs, primarily
driven by the considerable energy consumption involved, including the usage of electricity
and fuelwood. Among the various stages of tea production, the withering process
emerges as the most energy-intensive unit operation. Traditionally, the control of the
withering process has relied on the subjective judgement and experience of supervisors
based on factors such as temperature, leaf characteristics, and environmental conditions.
Consequently, ensuring optimal control and energy efficiency in the withering process has
become a considerable challenge. To address this challenge and improve energy
efficiency, a model was developed to predict moisture content during the withering
process. The model also aims to optimize the control of air flow rate and temperature
based on these predictions. Simulations were conducted using the model to identify the
optimal withering time for a given set of inputs, with the objective of minimizing both
electrical and thermal energy consumption. Simulation results revealed that the lowest
electrical energy consumption was achieved with a withering time of 14 hours, while the
lowest thermal energy consumption occurred at 10 hours. These findings highlight the
potential for optimizing flow rate and temperature variations at different stages of the
withering process to achieve energy efficiency. Development of this predictive model and
its subsequent simulations provide a foundation for the future automation of the tea
withering process.
