Development of Regression Models for Laser Beam Welding of Inconel 718 Alloy Thin Sheets

2022-28-0340

10/05/2022

Features
Event
10TH SAE India International Mobility Conference
Authors Abstract
Content
Inconel 718 is a superalloy made from nickel that has exceptional mechanical properties. It has been widely used in the manufacturing of various components such as nuclear and aerospace aircraft. Due to its exceptional corrosion resistance, this material can be utilized in various environments. Due to the increasing number of challenges that come with conventional methods of welding, the use of advanced techniques has been developed to produce better and sound quality joints. One of these is Laser Beam Welding (LBW) technique. This method utilizes a high-intensity beam to create a better and more quality weld joints with improved mechanical properties. This study aims to develop multiple regression models that can be used to analyze the performance of laser beam welding on Inconel 718 alloy joints. Aside from the Laser Power (LP), Weld Speed (WS) and Pulse Duration (PD), the response factors such as the top width, bottom width and penetration are also taken into account to improve the performance of the welding process. In order to improve the performance of laser beam welding, a series of experimental studies were conducted. The studies were conducted using the design method of Taguchi. The results of the studies were then analyzed using statistical methods. The results of the studies were then analyzed using statistical methods. Through the use of established regression equations, the researchers were able to predict the performance of the laser beam welding process. This study will provide a comprehensive guide to the manufacturers who are planning on using this LBW technique.
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DOI
https://doi.org/10.4271/2022-28-0340
Pages
6
Citation
Pasupuleti, T., Natarajan, M., Silambarasan, R., and R, R., "Development of Regression Models for Laser Beam Welding of Inconel 718 Alloy Thin Sheets," SAE Technical Paper 2022-28-0340, 2022, https://doi.org/10.4271/2022-28-0340.
Additional Details
Publisher
Published
Oct 5, 2022
Product Code
2022-28-0340
Content Type
Technical Paper
Language
English