Badril Azhar, Muhammad Ikhsan Taipabu, Cries Avian, Karthickeyan Viswanathan, Wei Wu, Raymond Lau
This study presents the design and optimization of a biodiesel production process, emphasizing the integration of machine learning (ML) models and process optimization techniques. The biodiesel production process involves multiple stages, including feedstock preparation, esterification, and transesterification, with catalysts Amberlyst-15 and KOH used in continuous stirred-tank reactors (CSTRs). Sensitivity analysis reveals that high conversions of free fatty acids (94 %) and triglycerides (97 %) are achievable under optimized operating conditions. To enhance process efficiency, adjustments to reaction temperature, time, and methanol-to-oil ratios are proposed, resulting in lower energy consumption and material costs. A ML model evaluation, using various algorithms, identify XGBoost, Extra Trees, Gradient Boosting, LGBM, and Random Forest demonstrate the best performer for predicting process parameters, achieving an R2 value of nearly to 1. Particle Swarm Optimization (PSO) is then employed to optimize the selected ML model (XGBoost), leading to the identification of optimal input parameters for biodiesel production. The optimized process, combined with heat integration, reduces pre-heating energy requirements by 80.9 % and total heat duties by 19.9 %. The findings demonstrate the effectiveness of combining ML and optimization techniques to enhance biodiesel production efficiency while reducing costs and energy consumption. © 2025 The Author(s)
Department of Chemical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia; Department of Chemical Engineering, Pattimura University, Ambon, 97134, Indonesia; Departement of Electrical Engineering, Brawijaya University, Indonesia; Department of Mechanical Engineering, Dr. N.G.P. Institute of Technology, Coimbatore, 641048, India; Department of Chemical Engineering, National Cheng Kung University, Tainan, 70101, Taiwan; School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 62 Nanyang Drive, Singapore, 637459, Singapore; Academy of Innovative Semiconductor and Sustainable Manufacturing, National Cheng Kung University, Tainan, 70101, Taiwan
