Statistical process control methods for monitoring processes with individual measurements are considered and two new individual control charts for monitoring process variability and correlation are proposed. The influence function of variance is proposed to monitor process variability. To investigate correlation among two quality characteristics control charts based on the influence function of correlation coefficient are suggested. The advantage of our variance influential control chart is its ability to monitor process variance based only on the measurements of each inspected unit, which is not the case for classical moving range chart where differences from one point to the next are displayed in the graphic, so limiting its use in the matter of mated parts. The proposed techniques are general, and the influence functions may be used to build up individual control charts relative to either nominal values or estimates. The method is further illustrated with real datasets, from a manufacturing system producing precisely interfitting and mating parts.