Optimization of biodiesel production from waste cooking oil in a local food processing enterprise

Thesis Abstract

The escalating demand for sustainable and renewable energy sources has heightened interest in biodiesel as a viable alternative to conventional fossil fuels, especially within industries that generate substantial quantities of waste cooking oil. This study addresses the critical challenge of optimizing biodiesel production from waste cooking oil in a local food processing enterprise, aiming to contribute cost-effective and environmentally sustainable energy solutions while minimizing waste disposal issues. The primary objective is to develop an optimal process protocol that maximizes biodiesel yield and quality, while also assessing the economic and environmental viability of the process within the enterprise context. Secondary objectives include evaluating the effect of operational variables—such as reaction temperature, catalyst concentration, and reaction time—on biodiesel conversion efficiency, and establishing a predictive model for process optimization. Employing a mixed-methods research design, the study combines experimental laboratory investigations with qualitative insights from plant engineers and technical staff. The population comprises waste cooking oil samples, process operators, and technical staff involved in the biodiesel production process within the enterprise. A stratified random sampling technique was employed, selecting 50 waste cooking oil samples over a six-month period to account for variability in feedstock quality, and 10 plant personnel for qualitative interviews. Data collection instruments include a laboratory setup for biodiesel transesterification experiments, gas chromatography-mass spectrometry (GC-MS) for quality analysis, and semi-structured interview guides to gather experiential insights. The experimental design encompasses factorial experiments testing key operational variables at multiple levels to identify optimal conditions, with each experimental run replicated thrice. Data analysis utilizes response surface methodology (RSM) to develop a quadratic model predicting biodiesel yield based on process variables, complemented by analysis of variance (ANOVA) for model validation. Regression analysis further refines the understanding of variable interactions and their significance on biodiesel quality parameters, such as ester content, viscosity, and flash point. Qualitative data from interviews undergo thematic analysis to contextualize operational challenges and facilitators, enriching the experimental findings with practical insights. The expected findings include identifying an optimal temperature range of 60–65°C, catalyst concentration of 1.0–1.5% w/w of oil, and reaction time of 60 minutes that collectively maximize biodiesel yield up to 92% with high purity as confirmed by GC-MS analysis. The study anticipates creating a validated predictive model with an R-squared value exceeding 0.95, demonstrating strong reliability. It is also projected that operational constraints, such as catalyst recovery and feedstock variability, significantly influence process efficiency. Furthermore, qualitative insights are expected to reveal key organizational and technical factors influencing process consistency and sustainability. This research significantly advances understanding of process parameters for waste cooking oil biodiesel production within small to medium-sized food enterprises, filling a notable gap in applied industrial biofuel research. It contributes a validated mechanistic model adaptable to similar industrial settings, facilitating evidence-based decision-making. The findings intend to inform best practices for technological implementation, policy formulation, and enterprise sustainability strategies, ultimately promoting environmentally responsible waste management and renewable energy utilization. The study concludes with tailored recommendations for process scaling, energy integration, and policy incentives and proposes avenues for further research into lifecycle assessment and economic analysis of biodiesel integration within food industry frameworks.