Multiresponse Optimization of Chopping Corn Stalk Parameters Using Fuzzy Logic and Regression Analysis
Author(s):
Charankumar G†, Rajyalakshmi K† and Prof. Giulio Lorenzini‡
Affiliation(s):
† Department of Mathematics, Koneru Lakshmaiah Education Foundation, Greenfields, Vaddeswaram, Guntur, AP, India.
‡ Department of Engineering and Architecture, University of Parma, Parma (Italy)
Corresponding Author Email: [email protected]
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fuzzy models help us to solve the complex systems effectively. Taguchi design of experiments identifies optimal process variables and demands additional experimentation for confirmation (if necessary). One of the widely applied Chopping processes (namely, Agricultural residues) utilizes Cutting Force and Cutting Power under different conditions of chopping process. This article presents optimal process variables for Cutting Force and Cutting power in Chopping agricultural residues adopting multi-objective optimization. In this paper, we adopted traditional Taguchi, Fuzzy inference model and regression analysis approaches to determine the optimum parameters and compare these methods with experimental results. Here we noted that the results obtained by Fuzzy logic are near and close to the experimental results.