The application of control charts to data provides a simple, widely applicable, and powerful method to aid trouble-shooting, and search for causes. There are many and various patterns which develop on control charts when processes are not in control. One classification is based on three basic changes: a change in process mean with no change in standard deviation, a change in process standard deviation with no change in mean, and a change in both mean and standard deviation. The manner of changes, in both mean and standard deviation may also be differentiated: sustained shift, drift, trend or cyclical, or frequent irregular. The appearance of control charts for mean and range help to identify different categories of out-of-control processes. Many processes are out of control when first examined and this is often due to an excessive number of adjustments in the process. The most frequent met causes of out of control situations may be characterized under people, plant/equipment, processes/procedures, materials, and environment. They can range from fatigue and illness, lack of training, rotation of shifts and machines, lack of maintenance, new processes, changes in inspections, accumulation of waste products, temperature changes, noise, etc. Where I work, this breakdown most often occurs when the corporate home office rolls out new programs that we don’t have the staffing for instead of waiting for use to get staffed and then roll out the program. This non-exhaustive list of causes above could manifest different patterns in various industries and conditions. It is clear that an intimate knowledge of the process through control chart management can be an advantage and even essential for effective process improvement.
Wheelter, D.J. (1986) The Japanese Control Chart, SPC Press, Knoxville TN, USA.
Wheeler, D.J. and Chambers, D.S. (1992) Understanding Statistical Process Control, 2nd Ed, SPC Press, Knoxville TN, USA