by Oliver Yu
If you have statistical software like JMP, then you can just click around on the menu
control charts appear like magic:
But suppose Wall Street bankers crashed the economy by securitizing AAA-rated subprime mortgages and you are the collateral damage; forking over $1,250 for a single-user annual license or $1,895 for a single-user perpetual license of JMP isn't in the cards. What do you do?
Good news. William Shewhart developed control charting principles long before computers so if worse comes to worse, you could probably create a control chart from graph paper and a grease pencil.
Here's what you do:
- Get the data into a column
- Compute moving range
- Multiply MR by 3 and divide by 1.128
Step 1: Get the data into a columnWe haven't talked about this yet, but data for analysis needs to be structured. If you look at the numbers in a column and they represent what the column headers describe, then you got it right.
Step 2: Compute the Moving Range
This is where you take the absolute value of the difference between measurements.
=B3-B2would be the formula that you'd drag in column C. The average of the moving range is used to determine the width of the control limits.
Step 3: Compute distance to control limitsTo get the distance to each control limit, compute 3 * Average( MovingRange ) / 1.128.
In this case, the average of the moving range is 3.90. Take
3.90 * 3 / 1.128 = 10.37.
The Upper Control Limit (UCL) is the
296 + 10.37 = 306
The Lower Control Limit (LCL) is the
296 - 10.37 = 286
What you do is calculate limits for every parameter you measure; apply it to a steady process and lock the limits and monitor the process against the locked-down limits to detect drift.
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