数控机床中的机器学习和人工智能,综述

Mohsen Soori , Behrooz Arezoo , Roza Dastres
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引用次数: 16

摘要

人工智能(AI)和机器学习(ML)代表了计算机科学和数据处理系统的重要发展,可用于提升几乎所有技术服务、产品和工业应用。机器学习是人工智能和计算机科学的一个子领域,其重点是利用数据和算法来模拟机器的学习过程,并提高系统的准确性。机器学习系统可应用于数控机床的切削力和刀具磨损预测,以提高加工操作过程中的刀具寿命。通过使用先进的机器学习系统,可以优化数控加工操作的加工参数,从而提高零件制造过程的效率。此外,还可以利用先进的机器学习系统预测和改进加工部件的表面质量,从而提高加工部件的质量。为了分析并最大限度地减少数控加工操作过程中的用电量,机器学习被应用于数控机床能耗的预测技术。本文对机器学习和人工智能系统在数控机床中的应用进行了综述,并对未来的研究工作提出了建议,概述了当前在数控加工过程中对机器学习和人工智能方法的研究。因此,可以通过审查和分析已发表论文中的最新成果,为人工智能和机器学习在数控机床中的应用提供创新概念和方法,从而推动研究工作向前发展。
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Machine learning and artificial intelligence in CNC machine tools, A review

Artificial Intelligence (AI) and Machine learning (ML) represents an important evolution in computer science and data processing systems which can be used in order to enhance almost every technology-enabled service, products, and industrial applications. A subfield of artificial intelligence and computer science is named machine learning which focuses on using data and algorithms to simulate learning process of machines and enhance the accuracy of the systems. Machine learning systems can be applied to the cutting forces and cutting tool wear prediction in CNC machine tools in order to increase cutting tool life during machining operations. Optimized machining parameters of CNC machining operations can be obtained by using the advanced machine learning systems in order to increase efficiency during part manufacturing processes. Moreover, surface quality of machined components can be predicted and improved using advanced machine learning systems to improve the quality of machined parts. In order to analyze and minimize power usage during CNC machining operations, machine learning is applied to prediction techniques of energy consumption of CNC machine tools. In this paper, applications of machine learning and artificial intelligence systems in CNC machine tools is reviewed and future research works are also recommended to present an overview of current research on machine learning and artificial intelligence approaches in CNC machining processes. As a result, the research filed can be moved forward by reviewing and analysing recent achievements in published papers to offer innovative concepts and approaches in applications of artificial Intelligence and machine learning in CNC machine tools.

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