FORMULATION OF DATA BASED ANN MODEL FOR HUMAN POWERED OIL PRESS

Abstract

In this study, an artificial neural network (ANN) model for a human-powered oil press is 
developed using experimental data. The design of the experiments for the creation of such a 
model was proposed by the authors in their previously published research article. A human-
powered oil press has been used for the experiment. In accordance with the recommended 
process, mathematical models have been developed, verified, and optimized. The ANN model is 
developed in this paper to produce the appropriate output parameter values for the different input 
parameter values. This best fit model is supported by the regression coefficient between the 
observed values and the response variable values calculated by the ANN. In order to maximize 
the quantity of oil extracted and minimize the instantaneous torque and angular velocity of the 
presser's shaft, the developed ANN can now be used to choose the optimal values of the various 
independent parameters for the designed oil press to match the characteristics of the machine 
operator performing the oil press task. The efficiency of an experimental setup may now be 
increased by the entrepreneur utilizing this ANN to choose the optimal combinations of the input 
parameters