Energy Prediction in Process Planning of Five-axis Machining by Data-driven Modelling

摘要

Process planning for a computer numerical control (CNC) machining is a multi-objective decision-making activity. A process planner defines machining set-up along with operation-sequencing at macro-level and decides toolpath strategies with its cutting parameters at micro-level. This paper proposes a data driven model that enables consideration of energy consumption also as a decision-making criterion during process planning for five-axis machining. A two-stage predictive energy model with an intermediate stage of exact feed prediction is proposed for machining on a five-axis machine. A process planner can use this model to choose optimal machining conditions that minimizes energy consumption during five-axis machining.