Joon-Young Koo

Machining Characteristics of Micro-Flow Channels in Micro-Milling Process

□ This article presents a method for machining micro-flow channels on dies for precise and effective mass production of metallic bipolar plates of proton exchange membrane fuel cells (PEMFCs). To find an effective method for machining micro-flow channels on dies of metallic bipolar plates, machining experiments are conducted on micro-flow channels using a micro-scale milling process under various machining conditions. Machining variables are axial depth of cut, feed per tooth, supply/non-supply of cold wind, and single-tool/multi-tool cutting processes. The machining process is monitored by acquiring cutting force signals and acoustic emission signals while conducting the experiments. Surface conditions of machined micro-flow channels are analyzed. In this study, a cold-wind process is better than other processes in terms of burr generation and surface roughness. A cold-wind process with multi-tool process has a particularly better surface quality than the other processes.

Point of tool change time and monitoring program for microscale milling process

In this article, a point in time at which tool change should take place and a program to monitor tool condition are proposed for microscale milling processes. The response surface method, which is one of designs of experiments, was used to determine cutting conditions. The independent variables were the spindle speed, axial depth of cut, and feed per tooth; each variable was divided into five levels. After tool life measurement experiments were performed with the determined cutting conditions, a second-order tool life equation was derived, and optimal cutting conditions were obtained by means of the tool life equation. A point of tool change time for the microscale milling process was proposed by analyzing the characteristics of cutting force signals and acoustic emission signals acquired during the experiments. Then the values were determined by analyzing the experimental results and were used to determine the tool change time in a machining monitoring program. The results of this study may be used to enhance machining efficiency in microscale milling processes.

Analysis on the correlation between cutting signals and surface quality in milling process of Ti-6Al-4V

The application of Titanium alloys has gradually increased because of its superior thermal and mechanical properties. Ti-alloys have higher strength and light weight compared to steel. However, Ti-alloys have poor machineability due to their low thermal conductivity and stiffness. As the machining proceeds, the tool wear is accelerated and abnormal conditions such as chipping and fracture of cutting edge occur. This paper presents an investigation on the effect of tool wear on surface quality in milling process of Ti-6Al-4V. The cutting force signals and acceleration signals are acquired during the machining experiments. And the machined surface is observed to check tool marks and surface roughness. The experiments are conducted until the milling tool is completely worn out. The changes of cutting force, acceleration, and surface condition according to tool wear are analyzed in machining process.

Investigation on the correlation between micro burrs and AE signal characteristics in micro-scale milling process

Micro burrs are likely to occur due to the size effect associated with cutting edge radius in a micro-scale milling process. Micro burrs reduce the machined surface quality and cause damages to the contact surfaces of micro parts, so it should be removed through the deburring process. However, the micro burrs formed by micro cutting process are not easy to remove, and require much time and cost for deburring process. Therefore, it is necessary to suppress the generation of micro burrs by the optimization of machining process. Also, it is important to detect the generation of micro burrs in advance through real-time monitoring of cutting signals to change in cutting conditions. In this paper, the influence of each cutting variables on the size of micro burrs and the correlation between micro-burrs and cutting signals are investigated through micro channel machining experiments in micro-scale milling process. The feed per tooth and spindle speed in the cutting variables are selected as independent variables. Each variable is divided into 3 levels and a total of 9 cutting conditions are derived. The size of micro burrs formed on the micro-channels is measured, and the effect of each cutting variable on the generation of micro burrs. Also signal characteristics such as AE RMS, band energy, AE count are extracted through signal processing of AE signals and the correlation between the size of micro burrs and the AE signal characteristics is figured out.

Analysis on signals characteristics for machining condition monitoring in high speed milling process of Inconel 718

Inconel 718 is widely used in automotive and aerospace industry because it has excellent mechanical properties such as light weight and high rigidity. However, it is typical difficult-to-cut materials, and has poor machinability. In machining of Inconel 718, tool fracture is likely to occur because tool wear is rapidly proceeded and tool temperature becomes high, which is derived from its lower thermal conductivity. Since properties of Inconel 718 are main cause of tool wear and deterioration of workpiece surface condition, tool and workpiece condition monitoring is important in machining. The types of sensors for tool and workpiece condition monitoring are limited because coolant is generally used in machining of difficult-to-cut materials. In this study, the cutting force, acceleration signal and surface roughness are investigated in high speed milling process of Inconel 718 under various cutting conditions. The correlation between signal characteristics by the cutting conditions and machining state such as Tool and workpiece condition are being analyzed.