Intelligent Manufacturing Management Systems

6Application of Machine Learning in the Machining Processes: Future Perspective Towards Industry 4.0

Bikash Chandra Behera¹*, Bikash Ranjan Moharana¹, Matruprasad Rout² and Kishore Debnath³

¹Department of Mechanical Engineering, C.V. Raman Global University, Bhubaneswar, India

²Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India

³Department of Mechanical Engineering, National Institute of Technology, Shillong, Meghalaya, India

Abstract

Machining is a subtractive manufacturing method that removes chip from a work item. Machining can be broadly divided into two kinds depending on the cutting tool and energy sources: (i) conventional machining and (ii) non-conventional machining. Turning and milling are two common conventional machining processes whereas electrical discharge machining (EDM), ultrasonic machining (USM), laser beam machining (LBM), etc. are non-conventional machining processes. Improving productivity necessitates the selection of process parameters, cutting tools, and machines with attention. However, over the previous few decades, such parameters have been chosen via a standard approach. The efficiency of the machining process can be improved if the industry adopts intelligent machining techniques that can offer self-optimization and adaptation to unforeseen situations. Machine learning (ML) algorithms have been used to diagnose and forecast the health of machine tools, optimize process parameters, and anticipate ...