%K Jets; Machine learning; Machining centers; Process monitoring, Abrasive water jet machining; Abrasive waterjets; Artificial intelligence learning; Cutting technology; Machine learning methods; Machining Process; Modeling; Process parameters; Recent trends; Waterjet machining, Neural networks
%X Abrasive Water Jet Machining is a revolutionary unconventional cutting technology that has a wide range of applications in the machining of difficult-to-machine materials. Process parameters are critical in determining the efficiency and economics of a high-quality machining process. As a consequence of advancements in sensor technology, machining operations may now be automated, and the massive amounts of data generated can be used to model and monitor the processes using Artificial Intelligence (AI) and Machine Learning (ML) approaches. This paper presents an overview of the current research trends linking the application of AI and ML methods to AWJM processes for enhanced performance metrics, process monitoring and control, and improved variable optimization. Overcoming challenges related to data quality, model interpretability, and system integration will be essential for the successful implementation of AI and ML in the field of water jet machining. The potential future directions in the ever-expanding field of AI and machining processes, particularly AWJM, are also discussed. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
%P 34-45
%L scholars20061
%A R. Khan
%A M. Wieczorowski
%A A. Qureshi
%A M. Ammar
%A T. Ahmed
%A U. Khan
%D 2024
%T Recent Trends in Artificial Intelligence and Machine Learning Methods Applied to Water Jet Machining
%O cited By 0; Conference of 8th International Scientific-Technical Conference Manufacturing, MANUFACTURING 2024 ; Conference Date: 14 May 2024 Through 16 May 2024; Conference Code:310369
%J Lecture Notes in Mechanical Engineering
%R 10.1007/978-3-031-56444-4₃