Research on intelligent decision method of computer-aided manufacturing numerical control parameters based on model-based definition and back propagation neural networks

Abstract

Aiming at the low efficiency and intelligence degree in the parameter setting of computer-aided manufacturing (CAM) numerical control (NC) programming caused by manual work, an intelligent decision-making method of CAM NC programming parameters based on model-based definition (MBD) is proposed. The hierarchical process model uses MBD technology to express the process flow and manage the process information. The tightness between process and NC machining is enhanced by sorting out NC machining steps and extracting their process information automatically. Then a back propagation (BP) neural network is used to mine the experience of NC programming in historical cases. Sparrow search algorithm (SSA) and other methods are used to optimize BP neural network’s initial weight and threshold, learning rate, and feedback process. A CAM parameter decision model based on BP neural network is constructed. Taking the connecting rod of a certain type of diesel engine as the experimental object, the method increases programming efficiency by 47%, with an accuracy rate of 80%. It is proved that the intelligent decision-making method proposed in this paper has practicability and feasibility.