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In this work, waste chicken eggshell (WCES) was used as a heterogeneous catalyst for the production of biodiesel from waste cooking oil (WCO). The catalyst was prepared via calcination technique. Response Surface Method (RSM) optimisation and Artificial Neural Network (ANN) modelling were performed to achieve maximum biodiesel yield. Both models perform reasonably well in achieving maximum biodiesel yield (91%). However, the efficacy of the models was determined with R 2 , R (coefficient of determination), and MSE (mean square error). Results show that the ANN model achieved the highest R 2  (98.48), R (99.24), and lowest MSE (0.08) compared to the RSM model. This shows that ANN predictive capability was more accurate. The fatty acid composition (FAC) analysis by GCMS reveals that 56.75% unsaturated and 41.99% saturated were recognised. The key physicochemical properties of biodiesel satisfy the standards of ASTMD6751 and EN 14,214.

Biodiesel production from low-grade oil using heterogeneous catalyst: an optimisation and ANN modelling