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.

The purpose of this study was to improve the noise measurement method of noise sources and the corresponding noise reduction measures during each manufacturing process closest to the workers in the large and hige power machine. To this end, the noise generated in the large and high power machine was measured and analyzed, and the frequency characteristics of noise sources and the causes of noise were identified. The noise map was used to predict the noise reduction effect. Moreover, it is expected that this will ultimately contribute to the reduction of human risks caused by the noise of the large and high power machine.

In order to commercialize large diameter PP pipes, the cutting work was attempted with the cutting machine (∅18″and AL120 cutter, 2100 r.p.m) used for the conventional PE or PVC pipe(∅1200 mm, t 70), but the cutting work was failed because the material of “PP pipe” melted and sticked to the surface of the wheel-cutter. In order to find the optimal structure and number of blades for wheel-cutters, an experimental investigation the temperature measurement of specimen and wheel-cutter and the visualization of cutted specimen surface and chip shape were carried out during and after experiment. In addition, modelings for cutting and heat transfer mechanisms have been developed for theoretical analysis. The theoretical and experimental results were in good agreement. The results show that the appropriate structure and the rotational speed of wheel-cutter are W60 and 650 rpm for the large diameter PP pipe cutting machine.

The purpose of this study was to establish the noise generation actual condition of large machine in plant. most of the plant's large-scale machines are designed and manufactured overseas, so it is difficult to access basic information. The regulatory standards, management plans and measurement methods for these machines are insufficient. It is necessary to obtain information about the noise storage devices installed for warranty and the noise reduction device when designing the equipment. Investigation of the occurrence of large-scale machine noise at domestic plant sites was conducted. The sound insulation design of the industrial safety and health care law benchmark and the large-scale machine compound noise design of the equipment are carried out.

The study on the database for the noise of the large machine and high power machine. The object of this project is to prepare the countermeasure of the health care according to investigate and database the basic information of the large machine and high power machine. To accomplish the object ; The dimension and noise of the large machine, which is mounted in the factory, was investigated. And the prediction and measurement method of the noise for the machine by manufacturers were investigated. The database of the noise by the machine type and power was built. The measurement and management methods for the machine noise were considered. The database of the noise was built from the measurement data. The major sound sources and frequency range for the large machine and the high power machine were investigated. The noise effect by the large machine and the high power machine was investigated. The application fields are; The setting of the management plan of the noise which generates from the large machine and the high power machine. The effective noise reduction for the major sound source with low cost. The application as the frequency transition considering the psycho-acoustics characteristics.

There is a growing demand for improving the welding quality by reducing the machining error and improving the quality of the machined surface in the beveling for the improvement of the welding groove of the thick plate. For this purpose, it is necessary to develop an automatic beveling machine that adopts a cutting method that replaces the conventional oxygen flame cutting method. In this study, the cutting characteristics according to the machining conditions were evaluated during the face milling applied to the thick plate welding groove. We measured and evaluated cutting force for the machining conditions such as cutting depth, feed rate, chamfer angle, workpiece material, and material of the tool. We expect that this study is used as basic data for designing the stiffness of the spindle, the strength of the fixture and the power of the spindle and the feeding device when designing the automatic beveling machine.

The object of this project is to prepare the countermeasure of the health care according to investigate and database the basic information of the large machine and high power machine. To accomplish the object; The dimension and noise of the large machine, which is mounted in the factory, was investigated. The prediction and measurement method of the noise for the machine by manufacturers were investigated. The noise at the 500 points of the large machine and high power machine in the 40 processes of the 6 factories, 6 business fields was measured. The database of the noise was built from the measurement data. The major sound sources and frequency range for the large machine and the high power machine were investigated. The noise effect by the large machine and the high power machine was investigated.