In this study is a study to measure the section by voltage through the high integration of the circuit of the inspection equipment for the power supply circuit of semiconductor equipment. The experiment was conducted by increasing the -1.5∼4 voltage section by 0.5V. At this time, the tolerance was applied to ±0.1%+5mA. Although the voltage increased through the experiment, the accuracy of the measurement data did not change, and it was confirmed through this experiment that the null hypothesis(H0) was adopted in each section through the hypothesis test.

The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

In order to secure competitiveness of companies in the semiconductor industry, state management of equipment is one of the most important key factors. Particularly, after carrying out preventive maintenance (PM) work to maintain the best equipment condition, process reliability inspection is carried out. This work must be performed manually by the intervention of the operator. This inspection work is becoming more and more difficult due to the difficulty of the manufacturing worker, the increase of the simple repetitive workload, and the increase of the inspection items for the engineer, as the condition and the procedure continuously change as the semiconductor scaling down. Therefore, we would like to carry out an empirical study on the construction of an automatic inspection system in order to carry out the more reliable and efficient inspection procedure by eliminating the problems and unreasonableness of the past based on the investigation and analysis of the work procedures and conditions of the existing manual method.

Cooling towers have been widely applied to control the indoor temperature in the residential area and the living space. At operating the cooling towers, motor, fan and dropping water produce noise and vibration, which diffuse through the air or the solid object, polluting the environment. The standards can be used at estimating noise and vibration emission by showing remarkable economic or social benefits. The purpose of this study is to show the vibration and noise measurement and influence evaluation between cooling towers and semiconductor equipment.

This study was carried out to estimate the usefulness of metal oxide semiconductor(MOS) sensor as an odor measuring instrument. In this study, sensor output for 12 legal malodorous compounds was measured by two kinds of the marketed MOS sensor and was investigated the correlation coefficient between sensor output and odor indicators as like odor concentration, air dilution ratio. As a results, it was estimated that MOS sensor has a high use possibility as odor measuring device for the single compound analysis, as the correlation coefficient between sensor outputs and odor concentration, R2 appeared to 0.9 or more high.