Abstract: “The traditional control chart for industry often requires identical and independent (i.i.d) assumptions. Thus, some modification on the control chart used in the industry need to be done before it can be used in the environmental application due to the difference in the nature of the data. The recorded environmental data are usually multivariate, correlated, and non-stationary and can be expressed as a function of time. In this present study, a control chart for monitoring curves data is to be applied where the hourly recorded data within a one day period is treated as multivariate point data and the occurrence is treated as a function of time. The control chart is constructed using the Functional Principal Component Analysis (FPCA) model. In the monitoring of quality indices overtime, autocorrelated data often negatively affects the performance of a control chart resulting into increase in the number of false alarm. Data pre-whitening approach is proposed during the monitoring phase o”

Keywords: control chart, PM10, monitoring, autocorrelation effect