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Recent Trends in Artificial Intelligence and Machine Learning Methods Applied to Water Jet Machining

  • Rehan Khan,
  • Michał Wieczorowski,
  • Ariba Qureshi,
  • Muhammad Ammar,
  • Tauseef Ahmed,
  • Umair Khan

摘要

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.