Back close

Prediction of Process Parameters ofUltrasonically Welded PC/ABS MaterialUsing Soft-Computing Techniques

Publication Type : Journal Article

Publisher : IEEE

Source : IEEE Access, Vol. 9 pp. 33849-33859, Feb 2021.(Impact factor-3.367; IEEE) (SCIE and Scopus Indexed)

Url : https://ieeexplore.ieee.org/document/9361659

Campus : Coimbatore

School : School of Engineering

Department : Electrical and Electronics

Year : 2021

Abstract : Welding process is found to be a predominant procedure in most of the processing industries, especially in the automobile sector for maintenance operation and fabrication. Ultrasonic Polymer Welding (USW) is used for the joining process because of its flexibility and short needed welding time. In this article, two different polymer materials PC and ABS are blended in the ratio of 60:40 and molded into a sheet. Furthermore, molded PC/ABS sheets are joined using USW with different processing parameter settings. Three major influencing process parameters like pressure (P), amplitude (A) and weld time (Tw) are considered and other processing parameters are kept at constant. The experiment is carried out for 26 welded samples and from the obtained results it is noticed that the above-mentioned process parameters directly influence the tensile strength of welded joints. Additionally, the ultrasonically welded samples tensile strength is analyzed with the help of Artificial Neural Network technique (ANN) and Adaptive Neuro-Fuzzy Inference System method (ANFIS). From the simulation results, an optimized ANFIS model provides the superior result as compared to ANN. Moreover, Scanning Electron Microscope analysis is carried out to visualize the weld interface between the joint. Also, Finite Element Modeling (ANSYS) is performed to understand the heat dissipation during the welding process.

Cite this Research Publication : T. Chinnadurai, Natarajan Prabaharan,S.Saravanan, M. Karthigai Pandean, P. Pandiyan, and Hassan HaesAlhelou, “Prediction of Process Parameters ofUltrasonically Welded PC/ABS MaterialUsing Soft-Computing Techniques”, IEEE Access, Vol. 9 pp. 33849-33859, Feb 2021.(Impact factor-3.367; IEEE) (SCIE and Scopus Indexed)

Admissions Apply Now