Automated Device Prototype using ANN for the Transesterification of Biodiesel

This technique has become increasingly popular recently to convert dietary lipids into compounds with technically more acceptable energy characteristics. It is possible to lower the viscosity of vegetable oils used as feedstock such that they more closely resemble traditional fossil fuels in terms of quality. Triglycerides, an ester composed of three fatty acids and glycerol, are converted into biodiesel by the process of transesterification. In order to forecast biodiesel yield, an artificial neural network (ANN) model was developed using the experimental data. The findings demonstrated that ANN was a potent tool for estimating biodiesel yield, as demonstrated by high R and low mean squared error (MSE) values. This technique has frequently been used to lower high viscosity vegetable oils and triglycerides. There are numerous techniques to produce biodiesel by transesterification, including supercritical, ultra, and high-shear in-line reactors and batch reactors. The setup will include a cylindrical tank, dish, tank cover, heating coil, motor, and rotor with fins. Because it is a renewable source of energy, biodiesel has been viewed as a very good alternative to traditional energy options given the present global energy and environmental problems. Solidworks is used to design the setup for the transesterification process, creating the component parts before assembling them.