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The machining know-how or knowledge exists in the NC programs if they are generated through experienced workers. To realize autonomous CNC machining, accumulation and representation of such know-how in a reusable way is needed. In this paper, an autonomous machining process analyzer for hole machining is studied. With the method, the machining process can be analyzed and the know-how can be extracted from existing successful NC programs. Specifically, machining feature, operation sequence, and cutting parameters including used tools, feedrate and spindle/cutting speed can be extracted. Based on the proposed method, a prototype system has been developed to verify the feasibility of the know-how extraction.

The paper deals with the end-milling machinability of α-β titanium alloy (Ti-6AI-4V alloy) by new PCD (Polycrystal-line Diamond) cutting tools at high cutting speeds in order to develop a new technology for a high productivity titanium finishing. The main focus of this paper is on investigating the relationships among cutting conditions, PCD tool materials, and tool wear. It was found that the edge engagement time of cutting tools with titanium workpiece has a great effect on PCD tool wear. Compared to cemented carbide tools, PCD tools have a longer tool life, especially at higher cutting speeds. The geometric shape of cutting edges and tool material greatly influences the performance of PCD tools in cutting titanium alloy.

The study aims at analyzing the tool utilization by using a real-time machining simulation and investigating the behavior of the parameters which affect the tool wear based on the results of the analysis. In this study, the method of calculation of parameters which are necessary to predict the tool wear by using Z-map based machining simulation is developed. Furthermore, the possibility of estimating the tool wear from the results of the simulation was also examined by performing the real cutting experiments.

This paper deals with a new multi-axis motion control method for high performance machine tool systems. The intelligent multi-axis motion control system proposed is mainly composed of a multi-axis motion trajectory monitoring system and an intelligent compensator with dynamic gain control. The multi-axis motion trajectory monitoring system calculates the motion trajectory error of all axes. The intelligent compensator with the dynamic gain control dynamically changes the servo gain to prevent a motion error from happening. A feasibility verification of the system is conducted on an actual CNC machining center. It is found that the new control method could improve the motion trajectory accuracy of the axes greatly. The control concept, system design, system implementation as well as the feasibility study of this new control system are described.