Online Prediction of Tool Wear in the Milling of the AISI P20 Steel Through Electric Power of the Main Motor

Abstract

Molds and dies have specific geometries that are linked to the profile of injected products. The great challenge for modern industry is to manufacture these products with high quality and low time. Ball nose end cutters provide flexible manufacturing due to their geometry that allows a single point of contact on free-form surfaces. However, the exact definition of the tool’s wear during the milling of molds and dies is complex. This work shows the monitoring of tool wear based on information obtained from the electric power consumed by the main motor. Experiments were carried out on work pieces of AISI P20 steel with dimensions of 20 × 20 × 10 mm. The tools used in the test were solid carbide ball nose mills with a diameter of 6 mm. Analysis of variance was applied to define the most influential input parameter in the milling process, considering electric power and torque as a response. The results showed that the online monitoring of the tool based on electric power information can be a good technique to define the tool’s wear during the milling process. Moreover, the electric system of monitoring was easier to assemble than traditional devices, such as piezoelectric dynamometers or load cells, because it provided an assembly without great interference in the machine tool or milling process. The energy analyzer was capable of detecting a variation in the electric power. The electric power and the torque decreased when the tool’s wear increased from new to worn tool.