In recent years, significant advancements have been achieved in the domain of machine monitoring as witnessed from the beginning of the new industrial revolution (IR) known as IR 4.0. This new revolution is characterized by complete automation, and an increase in the technological deployments and advanced devices used by various systems. As a result, considerable advancement has been reported by researchers and academia around the world by adopting and adapting the new technology related to the machine condition monitoring problem. For these reasons, it is important to highlight new findings and approaches in machine condition monitoring based on the wireless sensor solution and machine learning signal processing methodology that are relevant to assist in advancing this new revolution. This article presents a comprehensive review on tool condition monitoring (TCM), tool wear, and chatter based on vibration, cutting force, temperature, surface image, and smart label monitoring parameters from signal acquisition, signal processing methodology, and decision-making, particularly for the milling process. The paper also provides a brief introduction to the manufacturing industries and computer numerical control (CNC) machine tool demand and a review of machine monitoring and countries involvement in machine monitoring, as well as the approaches and a survey of machine monitoring. The aim is to contribute to this rapidly growing field of machine condition monitoring research by exploring the latest research findings on the solution approach for milling machine process monitoring, to help expedite future research, and to give some future direction that needs to be considered as a path to produce a standardized CNC machine platform.

近年来，从被称为IR 4.0的新工业革命（IR）的开始就见证了机器监视领域的重大进步。这项新革命的特点是完全自动化，以及各种系统使用的技术部署和先进设备的增加。结果，通过采用和适应与机器状态监视问题有关的新技术，全世界的研究人员和学术界已经报告了相当大的进步。由于这些原因，重要的是要突出基于无线传感器解决方案和机器学习信号处理方法的机器状态监视中的新发现和新方法，这些新方法和新方法和新方法有助于推动这一新革命。本文根据信号采集，信号处理方法和决策制定中的振动，切削力，温度，表面图像和智能标签监视参数，对工具状态监视（TCM），工具磨损和颤动进行了全面回顾。用于铣削过程。本文还简要介绍了制造业和计算机数控（CNC）机床的需求，并回顾了机床监测和参与机床监测的国家，以及机床监测的方法和调查。目的是通过探索铣床过程监控解决方案方法的最新研究成果，为这一快速发展的机器状态监控研究领域做出贡献，以帮助加快未来的研究，