Weld Strength Analysis of Ultrasonic Polymer Welding Using Adaptive Neuro-Fuzzy Inference System

Polymers are widely used in automotive and aerospace industries for its better strength and easy to design the expected shape and size of parts. To join the two plastic parts, ultrasonic welding is an effective way because of fast and clean process. The present study intends to investigate the weld strength of Ultrasonic Welding (USW) for PC/ABS blend using adaptive neuro-fuzzy inference system (ANFIS). The ANFIS models are utilized for the formulation of mathematical model of USW. All the input parameters are expected to have a significant impact on the weld strength but the most influencing input parameters are pressure, weld time and amplitude are prepared for this study. By comparing the real-time experimental results with the ANFIS predicted results, it is observed that the predicted and experimental models are in accordance with each other. This novel ANFIS model could be further employed for identifying the tensile strength of USW joints in various joining applications. Finally, the SEM images are analyzed to predict the nature of the weld condition.