Study on Breaking Load of Single Lap Joint Using Hybrid Joining Techniques for Alloy Steel AISI 4140 and Mild Steel: Taguchi and Neural Network Approach

Abstract The present investigation carried out to analyze the breaking load of single lap joint using hybrid joining techniques for alloy steel AISI 4140 and mild steel as base material by experimentally and optimized by Taguchi method and neural network. The six samples of lap joints were prepared namely: bolted joint (BJ); adhesive joint (AJ); welded joint (WJ); bolted-welded joint (BWJ); adhesive-welded joint (AWJ) and adhesivebolted joint (ABJ). The breaking load of the joints in terms of breaking load and elongation were evaluated for each joint. The effect of the adjustment attached to the joint on the breaking load and elongation were evaluated. Taguchi method was applied for given input parameters and L4 design of experiments was used. The breaking load and elongation were taken as output response. The predicted values by Taguchi method were used as target values in neural network fitting curve. Neural network fitting tool was used to check whether the obtained values were near the target value or not. Based on the achieved results, the maximum breaking load and elongation were found for bolted-welded joint.