Optimization of the exponential moving average chart

Abstract

Statistical Quality Control (SQC) is a statistical technique used to monitor and control

the production of goods and services in order to have good quality. Statistical Process Control

(SPC) mainly involves control charts, which are used to detect the occurrence of a shift in a

process mean in a production area. The Exponentially Weighted Moving Average (EWMA)

control chart is one of the control charts used to detect the occurrence of a shift in a process

mean. This chart makes use of the information from all the historic data, and therefore, is able

to significantly improve the effectiveness of the variable quality control.

This project will develop a simulation program through Microsoft Visual C++, to

design the EWMA chart under different design specifications, and also compare its

performance with that of the non-optimal counterpart. In this report, the author would

introduce the concepts of the EWMA chart, its various parameters as well as discuss the

significance that was attained from the data collected from the simulation program. Case

studies would be looked into so as to further corroborate the author’s findings.

Through these tasks and observations, the author was able to have a better appreciation

of how the EWMA chart works and the ways that such control charts have helped today’s

manufacturing environment. In summation, this research has extended beyond just being an

engineering experience to providing essential skills required to forge a successful career.