Statistical Process Management: The Concept Of Statistical Process Control

CHAPTER 10 : STATISTICAL PROCESS CONTROL (SPC) FOR ATTRIBUTE DATA.

1.0 Introduction
The concepts of Statistical Process Control (SPC) were initially developed by Dr. Walter Shewhart of Bell Laboratories in the 1920's, and were expanded upon by Dr. W. Edwards Deming, who introduced SPC to Japanese industry. SPC allows us to make assumptions about data to help separate simple random variation–also called natural variation–from variation that is caused by changes in the process–called assignable variation. according to webster, an attribute is a peculiar and essential characteristic. It can be said as something either does or does not exist. There are five types attributes such as structural attributes, sensory attributes, performance attributes, temporal attributes and ethical attributes. Structural attributes is a physical characteristic of a particular product or service such as a car contains airbag

The process will be most effective if the quality managers make it part of their daily routine to review charts and make comments and analysis.
This tool requires a great deal of coordination and if done successfully can greatly improve a processes ability to be controlled and analysed during process improvement projects. SPC helps define the capability of the stable process to judge whether it is operating at an acceptable level. The conclusion is Statistical Process Control is an analytical decision making tool which allows you to see when a process is working correctly and when it is not.

4.0 Reference
Grant, E.L., and R.S. Leavenworth. 1996. Statistical Quality Control (7th edition). New York, NY: McGraw-Hill.

Montgomery, D.C. 2012. An Introduction to Statistical Quality Control (7th edition). New York, NY: John Wiley & Sons

Thomas foster, 2013.integrating the supply chain (5th edition). England ,pearson education