WDM(Wavelength Division Multiplexing) is called a wavelength division multiplexing optical transmission method and is a next-generation optical transmission technology. Case company F has recently developed and sold PLC(Planar Lightwave Circuit), a key element necessary for WDM system production. Although Chinese processing companies are being used as a global outsourcing strategy to increase price competitiveness by lowering manufacturing unit prices, the average defect rate of products manufactured by Chinese processing companies is more than 50%, causing many problems. However, Chinese processing companies are trying to avoid responsibility, saying that the cause of the defect is the defective PLC Wafer provided by Company F. Therefore, in this study, the responsibility of the PLC defect is clearly identified through estimating the defect rate of PLC using the sampling inspection method, and the improvement plan for each cause of the PLC defect for PLC yeild improvement is proposed. The result of this research will greatly contribute to eliminating the controversy over providing the cause of defects between global outsourcing companies and the head office. In addition, it is expected to form a partnership with Company F and a Chinese processing company, which will serve as a cornerstone for successful global outsourcing. In the future, it is necessary to increase the reliability of the PLC yield calculation by extracting more precisely the number of defects.

The sampling bag is used as a storage container for odor gas samples. It is known that the substances recovery rate of odor bags decreases during storage time, and the degree of recovery varies depending on the characteristics of the gas sample and the material of the bag. This study investigated the recovery rate of VFA (ACA, PPA, BTA, VLA) in PEA bags during storage time. In addition, a model was developed to estimate the recovery rate of each substance as a function of time. Standard gas (ACA, PPA, BTA, VLA mixed) recovery rate was used for the model development. The concentration of the compound in the bag was measured by SIFT-MS at intervals of 1 to 2 hours. The recovery rate according to the storage time was calculated as the ratio to the initial concentration. The recovery rate of each substance according to the storage period (12h, 24h, 36h, 48h) was ACA (66.2%, 62.8%, 55.6%, 52.0%), PPA (77.6%, 72.1%, 63.0%, 58.1%, 86.6%), BTA (86.6%, 81.3%, 71.6%, 66.9%), VLA (94.8%, 89.0%, 76.6%, 71.7%). The recovery rate continued to decrease over the course of 48 hours of storage time. ACA, PPA, and BTA showed the greatest decrease within the initial 12 hours, which is form of exponential decrease. Therefore, we considered a 1~3 degree polynomial regression model and a 1~2 degree exponential decay model. Each developed model was evaluated by r², RMSE, MAPE, AIC, and then a model for each substance was selected. Selected models were tested with recovery rate data from swine farm odor samples. Only the ACA model exhibited a good performance (r² = 0.76).