The process control methods based on the statistical analysis apply the analysis method or mathematical model under the assumption that the process characteristic is normally distributed. However, the distribution of data collected by the automatic measurement system in real time is often not followed by normal distribution. As the statistical analysis tools, the process capability index (PCI) has been used a lot as a measure of process capability analysis in the production site. However, PCI has been usually used without checking the normality test for the process data. Even though the normality assumption is violated, if the analysis method under the assumption of the normal distribution is performed, this will be an incorrect result and take a wrong action. When the normality assumption is violated, we can transform the non-normal data into the normal data by using an appropriate normal transformation method. There are various methods of the normal transformation. In this paper, we consider the Box-Cox transformation among them. Hence, the purpose of the study is to expand the analysis method for the multivariate process capability index using Box-Cox transformation. This study proposes the multivariate process capability index to be able to use according to both methodologies whether data is normally distributed or not. Through the computational examples, we compare and discuss the multivariate process capability index between before and after Box-Cox transformation when the process data is not normally distributed.

I-D-F곡선을 유도할 때 강우자료의 보유연한이 충분하지 않을 경우 지속시간별 강우강도의 변화가 매끄럽게 연결되지 못하는 경우가 발생하기도 한다. 특히 곡선에서, 상대적인 장시간에 강우강도가 크게 되는 문제는 실무적으로 I-D-F 곡선을 이용하는데 큰 혼란을 야기 시킨다. 본 연구에서는 강우자료를 Box-Cox변환을 이용하여 지속시간과 강우강도의 상관관계를 통해 이러한 문제를 해결하는 방법을 제시한다. 산청과 영천의 강우자료에 대한 분석결과 Box-Co