Abstract

Biodiesel is a sustainable and green fuel with high potential for mitigating the adverse environmental impacts associated with conventional fossil fuels. Since the production of biodiesel is a complex process affected by many parameters which can influence the quality, cost, and environmental impact of the fuel, optimizing these factors is crucial to facilitate the commercialization of biodiesel and reduce emissions. Response Surface Methodology (RSM) is a statistical approach that is used to optimize processes and understand the relation between factors and their combined effect on the output response. RSM in biodiesel applications has been used to optimize process variables and to enhance the performance of biodiesel in engines. The goal of this review paper is to offer a brief overview of RSM, its benefits, and how it can be employed to improve the biodiesel production process and engine performance. The input process parameters, output response parameters, optimized combination of values, experimental design used, and the adequacy of the model and response for the studies were discussed. Additionally, this paper analyses the current status of literature on RSM in biodiesel applications, discusses the methodologies used by researchers, and provides useful information about the challenges and potential solutions. The main takeaways from this review include gaining an understanding of the benefits of RSM and its integration with other tools, insights into the challenges associated with biodiesel production and RSM limitations, along with potential research areas for further improvements.

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