Consider the following quality data for three different manufacturers of automobile weather-strips:
Weather-strip Bulb Dimension
Specification y=20 +or- 4mm
|
supplier
|
mean
|
variance
|
Cp
|
Cpk
|
%Defects
|
$Defects
|
Warranty Cost ($)
|
|
I
|
20.0
|
(4/3)2
|
1.0
|
1.0
|
0.270
|
|
|
|
II
|
18.0
|
(2/3)2
|
2.0
|
1.0
|
0.135
|
|
|
|
III
|
17.2
|
(2/5)2
|
3.33
|
1.0
|
0.135
|
|
|
Assume a customer loss per defective unit of $1450; cost of the weather-strip is $150, and a customer specified functional tolerance of ?0 = ± 5mm. Assume the annual production rate is 200,000 units.
1. Confirm the entries in the %Defects column.
2. Calculate the $Defects for each supplier, and fill in the table.
3. Using a quadratic loss function of the form:
Average Loss = k [ s2 + ( mean - target )2
calculate the $ loss due to variation, and fill in the table.
4. What is the sigma level for each supplier?
5. What is the value of manufacturing specifications to customers?
6. Select the best supplier, and explain your choice.