Research on tool wear prediction based on Archard agglomeration scavenging theory

Abstract

Nickel-based superalloy Inconel 718 has been widely used in the modern aviation field, however, its cutting performance is poor. This performance not only affects the effectiveness of the use of the tool but also reduces the efficiency of production. In this article, the cemented carbide tools cutting nickel-based superalloy Inconel 718 was taken as an example to analyze the tool wear mechanism. The wear prediction model of tool wear with cutting parameters and cutting time was established according to the Archard agglomeration scavenging theory. Using the orthogonal test, the multiple regression analysis method was used to obtain the parameters of the model with the help of EXCELL. Then, the prediction model was verified from two directions. Finally a real-time monitoring method of tool wear based on cutting parameters was proposed.