# More on Statistical Process Analysis and Control

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```					More on Statistical Process
Analysis and Control
Engineering Experimental Design
Winter 2003
In Today’s Lecture
• Control charts
• Process capability
What are Control Charts?
• A graphical method of evaluating process
performance and comparing it to process
specifications (requirements)
• A graphical method of distinguishing
between common-cause (random, normal)
and special-cause variation
• A graphical tool for deciding when you
should intervene in a process
• A graphical representation of statistics
Different Control Charts for
Different Types of Data
• Variable (Continuous)   • Attribute (Discrete)
Data                      Data
– X-Bar chart              –   np-chart
– R chart                  –   p-chart
–   c-chart
–   u-chart
Variable or Attribute Data?
•   Assay of each batch made in a plat
•   Average assay of batches produced in a week
•   Number of printing defects on a pallet label
•   Number of typos per sales contract
•   Number of batches off-spec in monthly production
•   Percentage off-spec pounds in monthly production
•   Number of samples rejected per 100 tested
•   Time to close an “account receivable”
Control Charts in this Course
• They are covered in Chapter 6
• You will construct and x-Bar and an R chart
in HW 5
• I am planning a control chart project for
later in the quarter
• No more lecture on control charts now
Process Capability Ratios
(Desired Performance) / (Actual Performance)
Note that average
performance is not centered
between the spec limits The shaded areas
This curve is the                                  represent the
distribution of data                            percentage of off-spec
from the process                                    production

Voice of Customer

Voice of Process
Cp
• The simplest process capability ratio
• Cp = (USL – LSL) / (6 s)
– USL = upper spec limit
– LSL = lower spec limit
– s = estimate of process standard deviation
• No penalty for being off-target
Cpk
• Combines variability and location
• Cpk = min((USL-x)/3s, (LSL-x)/3s)
– x = estimate of process mean
– s = estimate of process standard deviation
• Note typo in book. On p. 255, both sigmas in the
Cpl equation should be wearing hats
Why Use Cp?
• Sometimes called “process potential”
• Gives you an idea of what the process could
do, given its current variability, if it were
on-target
How is Cpk linked to Six-Sigma?
• Through the denominator, ± 3s
• If x ± 3s (a range of 6s centered on x)
doesn’t fit inside the SLs, you are not Six-
Sigma compliant

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 views: 7 posted: 9/29/2012 language: Unknown pages: 11