ANFIS MODELING IN PROJECTION WELDING OF NUTS TO SHEETS_DATA.zip

Projection welding Adaptive neuro-fuzzy inference system, Genetic algorithm.ojection welding Adaptive neuro-fuzzy inference system, Genetic algorithm. this study, the maximum weld strength in projection welding of nuts to sheets (DD13 sheet metal part and AISI 1010 nut) was investigated using optimum input parameters (weld current, weld time and hold time) in order not to damage weld joint during the car assembly. The experimental strength tests were carried out for each one hundred and forty actual samples. The projection welding process was modeled using an Adaptive Neuro-Fuzzy Inference System (ANFIS). One hundred of these experimental data were used for training in order to model the physical system. Forty experimental data were randomly selected over one hundred and forty actual experimental data. The randomly selected experimental data were used to validate the developed model. The proposed model exhibits good agreements with test data. The developed model was also checked based on squared coefficient of correlation. After all good agreements and validations, Genetic Algorithm (GA) was used to obtain some intermediate values not found on the actual experimental data. Maximum output parameter (weld strength) was determined using these optimum intermediate input parameters. Maximum strength of the projection welding was increased by five percentages using these optimum intermediate input parameters. Finally, all open source Matlab codes and a Google drive links for all Matlab files related to modeling and optimization of the physical system were added to Appendices in order to make other researchers’ works easy. Besides, these Matlab codes and files are applicable for any physical system with very small changes in codding.