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Statistical Process Control

Statistical Process Control. Using Control Charts to Monitor “Quality”. Walter Shewhart. Developer of Control Charts in the late 1920’s. www.york.ac.uk/.../ histstat/people/welcome.htm. Statistical Process Control. SPC does not refer to a particular technique, algorithm or procedure

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Statistical Process Control

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  1. Statistical Process Control Using Control Charts to Monitor “Quality”

  2. Walter Shewhart Developer of Control Charts in the late 1920’s www.york.ac.uk/.../ histstat/people/welcome.htm

  3. Statistical Process Control • SPC does not refer to a particular technique, algorithm or procedure • SPC is an optimisation philosophy concerned with continuous process improvements, 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

  4. Ultimately, SPC seeks to maximize profit by: • improving product quality • improving productivity • streamlining process • reducing wastage • reducing emissions • improving customer service, etc. http://lorien.ncl.ac.uk/ming/spc/spc1.htm

  5. Control Charts • 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 to producing defective parts.

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

  7. Objectives • Be able to explain how control charts relate to assigned dimension and tolerance • State what value you get from control charts • Be able to name several ways that control charts indicate that a process is “out of control”

  8. Reminder: Normal Distribution Defined by two parameters: mean and standard deviation http://www.campbell.berry.edu/faculty/jgrout/spclecture.ppt

  9. 2.500.05 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?

  10. Control charts are normal distributions with an added time dimension http://lorien.ncl.ac.uk/ming/spc/spc8.htm#interpretation

  11. Control charts provide a graphical means for testing hypotheses about the data being monitored. Consider the commonly used Shewhart Chart as an example. http://lorien.ncl.ac.uk/ming/spc/spc8.htm#interpretation

  12. What does the control chart look like? - 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. How does the control chart relate to the tolerances? Assigned Tolerances 2.55 2.45 -3 +3 Measured Variation

  14. Value of Control Charts • Defect Prevention through “Early Warning” • Prevent “Over-Tweaking” of Process • Assures that Process is Working • Provides Information on “Process Capability”

  15. Defect Prevention • When you see signs that the process is “out of control” you can look for and fix the causes before you make bad parts. • The control chart can help you distinguish between “common cause” and “special cause” problems.

  16. Q - How do you know a process is “out of control”? A – When the data aren’t “normal” “Out of Control” cues include - Points outside of control limits (3σ) - 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

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  18. Prevent “Over-Tweaking” • Without understanding of the statistics you can chase your tail trying to get rid of variation

  19. Process Capability • Comparing the control chart information with the tolerance specification tells you about the process capability.

  20. The capability index is defined as: Cp = (allowable range)/6s = (USL - LSL)/6s LSL USL (Upper Specification Limit) LCL UCL (Upper Control Limit) http://lorien.ncl.ac.uk/ming/spc/spc9.htm

  21. The process performance index takes account of the mean (m) and is defined as: Cpk = min[ (USL - m)/3s, (m - LSL)/3ss ] LSL USL (Upper Specification Limit) LCL UCL (Upper Control Limit) http://lorien.ncl.ac.uk/ming/spc/spc9.htm

  22. Process Capability Assigned Tolerances 2.45 2.55 Good CPK>1 -3 +3 Measured Variation Poor CPK<1 -3 +3

  23. Tolerance Stackups

  24. Tolerance Stack-up for an O-Ring www.afmusa.com/doc_ generator.asp?doc_id=1238

  25. How to calculate Stack-up • WC – Worst Case (add all the tolerances at full value) • RSS – Root Sum Squared (add the tolerances statistically) • Monte Carlo (use part distribution data to predict the distribution of the added tolerances)

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