Gohari, H.; Hassan, M.; Shi, B.; Sadek, A.; Attia, H.; M’Saoubi, R. Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review. Sensors2024, 24, 2324.
Gohari, H.; Hassan, M.; Shi, B.; Sadek, A.; Attia, H.; M’Saoubi, R. Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review. Sensors 2024, 24, 2324.
Gohari, H.; Hassan, M.; Shi, B.; Sadek, A.; Attia, H.; M’Saoubi, R. Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review. Sensors2024, 24, 2324.
Gohari, H.; Hassan, M.; Shi, B.; Sadek, A.; Attia, H.; M’Saoubi, R. Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review. Sensors 2024, 24, 2324.
Abstract
The fifth Industrial revolution (I5.0) prioritizes resilience and sustainability, integrating cognitive cyber-physical systems and advanced technologies to enhance machining processes. Numerous research studies have been conducted to optimize machining operations by identifying and reducing the sources of uncertainty and estimating the optimal cutting parameters. Virtual modeling and Tool Condition Monitoring (TCM) methodologies have been developed to assess the cutting states during machining processes. With a precise estimation of cutting states, the safety margin necessary to deal with the uncertainties can be reduced, resulting in improved process productivity. This paper reviews the recent advances in high-performance machining systems with a focus on the cyber-physical models developed for the cutting operation of difficult-to-cut materials using cemented carbide tools. An overview of the literature and background on the advances in the offline and online process optimization approaches have been presented. Process optimization objectives such as tool life utilization, dynamic stability, enhanced productivity, improved machined part quality, and reduced energy consumption and carbon emissions are independently investigated for the offline and online optimization methods. Addressing the critical objectives and constraints prevalent in industrial applications, the paper explores the challenges and opportunities inherent in developing a robust cyber-physical optimization system
Keywords
process optimization; adaptive control; cyber-physical systems; industry 5.0; finite element analysis
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
