Statistical Quality Control. Chapter 17. To accompany Quantitative Analysis for Management , Tenth Edition , by Render, Stair, and Hanna Power Point slides created by Jeff Heyl. © 2009 Prentice-Hall, Inc. . Define the quality of a product or service
To accompanyQuantitative Analysis for Management, Tenth Edition,by Render, Stair, and Hanna
Power Point slides created by Jeff Heyl
© 2009 Prentice-Hall, Inc.
After completing this chapter, students will be able to:
17.2 Defining Quality and TQM
17.3 Statistical Process Control
17.4 Control Charts for Variables
17.5 Control Charts for Attributes
Lower control limit
Upper control limit
Lower control limitStatistical Process Control
Two plots near upper control Investigate for cause.
Two plots near lower control. Investigate for cause.
Run of 5 above central line. Investigate for cause.
Run of 5 below central line. Investigate for cause.
The x-chart (mean) and R-chart (range) are the control charts used for processes that are measured in continuous units
We often estimate and with the average of all sample means ( )The Central Limit Theorem
Figure 17.2 shows three possible population distributions, each with their own mean () and standard deviation ( )
x = S.D.
x = S.D.
x = S.D.
99.7% of all x
fall within ±3x
95.5% of all x fall within ±2x
+3xThe Central Limit Theorem
Sampling Distribution of Sample Means (Always Normal)
= average of the samples
A2 = value found in Table 17.2
= mean of the sample meansBox Filling Example
16.01 + 0.144
16.01 – (0.577)(0.25)
16.01 – 0.144
15.866Super Cola Example
We have determined upper and lower control limits for the process average
Collect 20 to 25 samples of n = 4 or n = 5 from a stable process and compute the mean and range of each
Compute the overall means ( and ), set appropriate control limits, usually at 99.7% level and calculate the preliminary upper and lower control limits. If process not currently stable, use the desired mean, m, instead of to calculate limits.
Graph the sample means and ranges on their respective control charts and determine whether they fall outside the acceptable limitsFive Steps to Follow in Using x and R-Charts
= mean proportion or fraction defective in the sample
z = number of standard deviations
= standard deviation of the sampling distribution which is estimated by where n is the size of each samplep-Charts
Percentage can’t be negative
In the previous example we counted the number of defective records entered in the database