Big data-oriented wheel position and geometry calculation for cutting tool groove manufacturing based on AI algorithms

Groove is a key structure of high-performance integral cutting tools. It has to be manufactured by 5-axis grinding machine due its complex spatial geometry and hard materials. The crucial manufacturing parameters (CMP) are wheel positions geometries. However, it challenging problem solve the CMP for designed groove. traditional trial-and-error or analytical methods have defects such as time-consuming, limited-applying, low accuracy. In this study, translated into multiple output regression model groove manufacture (MORGM) based on big data technology AI algorithms. inputs 34 features, outputs 5 CMP. Firstly, two machining sets with different range established, each which includes 46,656 records. They used resource MORGM. Secondly, 7 algorithms, including linear regression, k nearest-neighbor decision trees, random forest support vector ANN discussed build model. Then, 28 experiments carried out test set Finally, best MORGM built algorithm larger range. results show that can calculated accurately conveniently