Control (management)

Process (computing)

Engineering

Reliability engineering

Statistics

EWMA chart

Operating system

Computer science

Chart

Manufacturing engineering

Statistical process control

Shewhart individuals control chart

Operations research

Mathematics

\bar x and R chart

Industrial engineering

Control chart

Mathematical analysis

Operations management

Artificial intelligence

CUSUM

Generalization

Quality Engineering

We discuss some practical issues involving the control of the number of false alarms in process monitoring. This topic is of growing importance as the number of variables being monitored and the frequency of measurement increase. An alternative formulation for evaluating and comparing the performance of control charts is given based on defining in-control, indifference and out-of-control regions of the parameter space. Methods are designed so that only changes of practical importance are to be detected quickly. This generalization of the existing framework makes control charting much more useful in practice, especially when many variables are being monitored. It also justifies to a greater extent the use of cumulative sum (CUSUM) methods.

Rethinking control chart design and evaluation