A new tool wear estimation method based on shape mapping in the milling process

In the milling process, tool wear has a great influence on product machining quality, especially for a difficult-to-cut material. In this paper, a new approach based on shape mapping is proposed to acquire tool wear in order to establish an off-line tool wear predicting model for assessing the degree of wear and remaining useful life. The new approach maps tool wear shape into a metal material by milling holes mode after finishing each of the machining experiments. The metal material has low influence on tool wear compared to the experimental material. Thus, a series of mapped holes, which can represent the worn tool information, are formed on the metal material when finishing all milling experiments. These mapped holes on the metal material are analyzed according to all types of milling cutters in order to establish the relationship between the characteristic parameters of these mapped holes and tool wear. According to the established relationship, the characteristic parameters of these mapped holes are measured on the coordinate measure machine. The tool wear of each machining experiment can be obtained from the measured characteristic parameters of these mapped holes. The new tool wear estimation method does not require the stoppage of the machine tool and the removal of the cutter to measure tool wear in the process of conducting tool wear experiments. The new method can increase the machine tool efficiency of tool wear machining experiments and provide an efficient way to acquire tool wear in the process of establishing an off-line tool wear predicting model. In order to verify the new tool wear estimation method, a series of machining experiments were conducted on the five-axis machining center for cemented carbide cutting tool milling stainless steel. Experiments show that the shape mapping strategy of tool wear can allow for an effective assessment of tool wear and indicate good correlation with the expected wear characteristics and easily conduct tool wear experiments.