In the process of cutting large aircraft parts, the tool may be abnormally worn or damaged due to various factors such as mechanical vibration, disturbances such as chips, and physical properties of the workpiece, which may result in deterioration of the surface quality of the workpiece. Because workpieces used for large aircrafts parts are expensive and require strict processing quality, a maintenance plan is required to minimize the deterioration of the workpiece quality that can be caused by unexpected abnormalities of the tool and take maintenance measures at an earlier stage that does not adversely affect the machining. In this paper, we propose a method to indirectly monitor the tool condition that can affect the machining quality of large aircraft parts through real-time monitoring of the current signal applied to the spindle motor during machining by comparing whether the monitored current shows an abnormal pattern during actual machining by using this as a reference pattern. First, 30 types of tools are used for machining large aircraft parts, and three tools with relatively frequent breakages among these tools were selected as monitoring targets by reflecting the opinions of processing experts in the field. Second, when creating the CNC machining program, the M code, which is a CNC auxiliary function, is inserted at the starting and ending positions of the tool to be monitored using the editing tool, so that monitoring start and end times can be notified. Third, the monitoring program was run with the M code signal notified from the CNC controller by using the DAQ (Data Acquisition) device, and the machine learning algorithms for detecting abnormality of the current signal received in real time could be used to determine whether there was an abnormality. Fourth, through the implementation of the prototype system, the feasibility of the method proposed in this paper was shown and verified through an actual example.

In the development of advanced ceramic tools, material improvements and design freedom are critical in improving tool performance. However, in the die press molding method, many factors limit tool design and make it difficult to develop innovative advanced tools. Ceramic 3D printing facilitates the production of prototype samples for advanced tool development and the creation of complex tooling products. Furthermore, it is possible to respond to mass production requirements by reflecting the needs of the tool industry, which can be characterized by small quantities of various products. However, many problems remain in ensuring the reliability of ceramic tools for industrial use. In this study, alumina inserts, a representative ceramic tool, was manufactured using the digital light process (DLP), a 3D printing method. Alumina inserts prepared by 3D printing are pressurelessly sintered under the same conditions as coupon-type specimens prepared by press molding. After sintering, a hot isostatic pressing (HIP) treatment is performed to investigate the effects of relative density and microstructure changes on hardness and fracture toughness. Alumina inserts prepared by 3D printing show lower relative densities than coupon specimens prepared by powder molding but indicate similar hardness and higher fracture toughness values.

The purpose of this study is to investigate cutting characteristics and wear behavior in SCM440 steel with different cutting tools, CBN(Cubic Boron Nitride) and coated CBN. During the test coated CBN toolespecially with TiAlN showed better wear resistance behavior than orginal CBN tools. In the interruptedcutting condition, axial groove affected tool surface with impact force during the turning operation. Foradvantageous turning parameter in the interrupted process it is recommendable that lower speed. Also surface roughness showed better behavior in the coated CBN tool conditions than normal CBN conditions. Mainly this is caused by reduced friction between material and tool surface with coated layer.