statistical process control @ black

7/27/2019 Statistical Process Control @ black

1/26


2/26

Walter Shewhart

www.york.ac.uk/.../ histstat/people/welcome.htm

Developer of Control Charts in the late 1920s
http://www.york.ac.uk/depts/maths/histstat/people/welcome.htmhttp://www.york.ac.uk/depts/maths/histstat/people/welcome.htm


3/26

SPC does not refer to a particulartechnique, algorithm or procedure

SPC is an optimisation philosophyconcerned with continuous processimprovements, using a collection of(statistical) tools for

data and process analysis making inferences about process behaviour

decision making

http://lorien.ncl.ac.uk/ming/spc/spc1.htm
http://lorien.ncl.ac.uk/ming/spc/spc1.htmhttp://lorien.ncl.ac.uk/ming/spc/spc1.htm


4/26

improving product quality

improving productivity

streamlining process

reducing wastage

reducing emissions

improving customer service, etc.



5/26

Control charts are particularly useful for

monitoring quality and giving early

warnings that a process may be going

Out of Control and on its way toproducing defective parts.


6/26

http://www.pqsystems.com/products/SPC/CHARTrunner/CHARTrunnerChartingExample1.php
http://www.pqsystems.com/products/SPC/CHARTrunner/CHARTrunnerChartingExample1.phphttp://www.pqsystems.com/products/SPC/CHARTrunner/CHARTrunnerChartingExample1.php


7/26

Be able to explain how control chartsrelate to assigned dimension and

tolerance State what value you get from control

charts

Be able to name several ways thatcontrol charts indicate that a process isout of control


8/26

Normal DistributionDefined by two parameters:

mean and standard deviation

http://www.campbell.berry.edu/faculty/jgrout/spclecture.ppt

Reminder:
http://www.campbell.berry.edu/faculty/jgrout/spclecture.ppthttp://www.campbell.berry.edu/faculty/jgrout/spclecture.ppt


9/26

2.500.05

Example:

Suppose we specify a dimension

and tolerance as shown.

Questions:

- What does the control chart look like?

- How does control chart relate to the tolerances?

X


10/26

Control charts are normal distributions

with an added time dimension

http://lorien.ncl.ac.uk/ming/spc/spc8.htm#interpretation


11/26

http://lorien.ncl.ac.uk/ming/spc/spc8.htm#interpretation


12/26

What does the control chart look like?X

- First we measure a number of parts as they come off the line.- For example we might measure 4 parts per hour for 20 hours.

- Those 80 parts would give us an overall mean and standard deviation

that would define the control chart.

- The average of the size of the four parts would give us

the y values for each hour (plotted on the x-axis)

+3

-3

Time


13/26

+3-3

2.552.45

Assigned Tolerances

Measured Variation

How does the control

chart relate to the tolerances?


14/26

Defect Prevention through EarlyWarning

Prevent Over-Tweaking of Process Assures that Process is Working

Provides Information on Process

Capability


15/26

When you see signs that the process isout of control you can look for and fix

the causes before you make bad parts. The control chart can help you

distinguish between common causeand special cause problems.


16/26

Q - How do you know a process is out of control?

AWhen the data arent normal

Out of Control cues include

- Points outside of control limits (3)- 8 consecutive points on one side of center line

- 2 of 3 consecutive points outside the 2 limits

- 4 of 5 points outside the 1 limits

- 7 consecutive points trending up or down


17/26

Screen Dump from MiniTab


18/26

Without understanding of the statisticsyou can chase your tail trying to get rid

of variation


19/26

Comparing the control chart informationwith the tolerance specification tells you

about the process capability.


20/26

Cp = (allowable range)/6s = (USL - LSL)/6s

USL (Upper Specification Limit)LSL

LCL UCL (Upper Control Limit)



21/26

Cpk = min[ (USL - m)/3s, (m - LSL)/3ss ]

USL (Upper Specification Limit)LSL

LCL UCL (Upper Control Limit)



22/26

+3-3

2.552.45

Assigned Tolerances

Measured Variation

-3 +3

Process Capability

Good

Poor

CPK>1

CPK


23/26


24/26

www.afmusa.com/doc_ generator.asp?doc_id=1238

Tolerance Stack-up for an O-Ring
http://www.afmusa.com/doc_generator.asp?doc_id=1238http://www.afmusa.com/doc_generator.asp?doc_id=1238


25/26

WC Worst Case (add all the tolerancesat full value)

RSS

Root Sum Squared (add thetolerances statistically)

Monte Carlo (use part distribution datato predict the distribution of the addedtolerances)


26/26

statistical process control @ black

Documents