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神经网络提供了获取知识的一条新途径。在机械加工学科中，人们可以利用影响工件表面粗糙度的切削或磨削参数来建造神经网络模型，然后通过实际样本对神经网络进行自学习训练，使此模型变成切合车间不同设备的实用模型，从而可以有针对性地改变某些切削或磨削参数，以降低工件表面粗糙度和提高表面质量。本文论述了神经网络模型的建立、自训练原理和降低表面粗糙度的途径
Neural networks provide a new way to acquire knowledge. In the machining discipline, one can build a neural network model using cutting or grinding parameters that affect the surface roughness of a workpiece, and then train the neural network through actual samples to make the model a practical model that fits different plant-floor equipment , Which can be targeted to change some cutting or grinding parameters to reduce the surface roughness and improve the surface quality of the workpiece. This article discusses the establishment of neural network model, self-training principle and ways to reduce the surface roughness