Twin Process Model Driven Machining Quality Optimization for Complex Parts

Abstract

Machining process of complex parts is high-performance processing with equal emphasis on geometric accuracy and physical performance indicators, and its machining quality directly affects service performance. Process optimization based on digital twin is considered as an intelligent method to link machining process and process design, which is benefit to the scientific control of machining quality. This paper summarizes the evolution and development of process model and proposes twin process model, which could support the machining quality optimization of complex parts. What’s more, industrial application of twin process model is introduced through three steps, namely mapping relationship between machine operation data and instruction domain, simulation and monitoring of machining surface roughness, and optimization of machining parameter based on twin process model. Finally, the proposed twin process model could provide theoretical support for machining quality control.