A Survey on Artificial Intelligence-Based Modeling Techniques for High Speed Milling Processes


The process of high speed milling is considered one among the most refined and difficult producing operations. In the past four decades, several investigations are conducted on this process, aiming to better perceive its nature and improve the surface quality of the product along with extending tool life. To achieve these goals, it is necessary to form a general descriptive reference model of the milling method using experimental knowledge, thermomechanical analysis, statistical or artificial intelligence (AI) models. Moreover, increasing demands for more economical milling processes, qualified surface finishing, and modeling techniques have propelled the development of a lot of effective modeling methods and approaches. In this paper, an in depth literature survey of the state-of-the-art modeling techniques of milling processes will be disbursed, additional specifically of recent advances and applications of AI-based modeling techniques. The comparative study of the accessible ways additionally as the suitability of every technique for corresponding varieties of experiments will be presented. In addition, the weaknesses of every technique and open analysis challenges can be presented. Therefore, a comprehensive comparison of recent developments in the field can be a tenet for selecting the most appropriate modeling technique for this process regarding its goals, conditions, and specifications.

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