Data-Driven Modeling of Industrial Robot Repeatability Using Ensemble Artificial Neural Networks Under Varying Operational Conditions
A data-driven framework for predicting repeatability of FANUC LR Mate 200iD and KUKA KR 6 R700 Sixx robots under varying operational conditions provides a practical tool for predicting repeatability, supporting process planning, uncertainty budgeting, and precision manufacturing optimization.