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A thermal-structural model for process performance analysis

机译:用于过程性能分析的热结构模型

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摘要

In the present study, a Box-Behnken design of experiment strategy is adopted to obtain necessary information from a proposed numerical simulation model using thermal-structural analysis with reduced number of runs. Influence of important process parameters on several output responses has been studied to gain insight into machining performance. The numerical model is validated through conducting necessary experiments. Subsequently, artificial neural network (ANN) is used to establish relation between input parameters and the responses. The model provides an inexpensive and time saving alternative to study the performance of machining before actual cutting operation. The model can be used for selecting ideal process states to improve machining efficiency.
机译:在本研究中,采用Box-Behnken实验策略设计来从拟议的数值模拟模型中使用热结构分析从运行次数减少的过程中获取必要的信息。研究了重要工艺参数对几种输出响应的影响,以深入了解加工性能。通过进行必要的实验验证了数值模型。随后,使用人工神经网络(ANN)建立输入参数与响应之间的关系。该模型提供了一种廉价且省时的替代方案,可以在实际切割操作之前研究加工性能。该模型可用于选择理想的过程状态以提高加工效率。

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