Most productive processes are affected by multiple variables and generate a great amount of data and simultaneous monitoring becomes necessary. Thus, the main purpose of this work is to show, by means of an example, procedures of identification of variables responsible for process instability. It considers weakly and strongly correlated variables. The behavior of these variables is analyzed, initially by means of a Hotteling`s T² chart for the verification of the process stability. When the process is considered to be out-of-control, another investigation is carried out. For variables of weak correlation an X-bar chart with Bonferroni limits is used. For variables of strong correlation, the data are decomposed in principal components and analyzed by means of a X-bar control chart. In both cases, the techniques used can correctly identify the variable responsible for the process instability, as well as the period of disturbance.
Statistical process control; Hotelling's T2 chart; X-bar chart with Bonferroni limits; Principal components analysis
