Journal Article

Machine learning for intelligent welding and manufacturing systems: research progress and perspective review

Wu, ChuanSong, Gaur, Vidit, Kumar, Sachin

2022

Overview

In the modern era, welding systems have been made smart with the inclusion of contemporary information technologies such as intelligent manufacturing and machine learning (ML). The ML has been integrated with a wide application area of metal joining to achieve the status of intelligent welding systems (IWS). The IWS, using ML, has drawn massive consideration from researchers and industrialists to obtain high product quality and cost-effective solutions. Intelligent welding uses modern computers for sensing, learning, decision-making, monitoring, and control, thus replacing/minimizing human interference. ML-integrated welding is primarily for modeling, identification, optimization, prediction, and controlling multiple variables. Citing the necessity and importance of ML models in weld quality and process optimization, the current study is aimed on describing basics of ML techniques, their types, models, and adaptability scenarios in numerous industrially sought IWS.

• Publisher: Springer London,Springer Nature B.V
• Subject: Accuracy / Advanced manufacturing technologies / Algorithms / Automation / CAE) and Design / Computer-Aided Engineering (CAD / Continuous casting / Critical Review / Data collection / Decision making / Economic crisis / Engineering / Friction stir welding / Industrial and Production Engineering / Intelligent manufacturing systems / Machine learning / Manufacturing / Mechanical Engineering / Media Management / Optimization / Product quality / Production planning / R&D / Research & development / Welding