In this chapter, the author introduces two types of variation, predictable and unpredictable, and the improvement strategies applied to each variation respectively. XmR chart is also presented as a tool to distinguish the types of variation. However, the author does not explain why XmR chart works in this Chapter. This made me a bit confused and not being persuaded to use the chart. Then, I look at the content page again and find that in Chapter 11, the author will talk about What Makes the XmR Chart Work?. So, I decided to read Chapter 11 directly after finishing Chapter 7. I need to understand the rationale behind it.

Predictable ProcessUnpredictable Process
ReasonsProcess subjects to many cause-and-effect relationships where no one cause is dominant over the others.Process subjects to some dominant causes which are called assignable causes.
Improvements neededImprovement will only come by changing a major portion of the process. It will be a waste of time to look for assignable causes (a particular cause).Improvement will come by finding and removing the assignable causes. Changing a major portion of the process will be premature.

But how can we know a process is predictable or unpredictable. The author then introduces a tool called XmR chart. The basic concept of XmR chart is to compute an upper bound and lower bound of a time series. Anything outside the bounds is unpredictable.

https://i0.wp.com/www.skybluelogistics.com/Images/XMRChart.jpg?w=780&ssl=1

The red line in the top chart is the original time series. The steps to reproduce the charts are as follow:

  1. Compute the Moving Ranges (mR) by calculating the running difference between two points.
  2. Plot the mR in the red line of the bottom chart
  3. Compute the average of mR. Plot it as the blue line.
  4. Compute the Upper Range Limit (URL) = 3.27 * the average of mR. Plot it as the green line.
  5. Compute the Upper Natural Process Limit (UNPL) = average of the time series + (2.66 * average of mR). Plot it as the green line in the top chart.
  6. Compute the Lower Natureal Process Limit (LNPL) = average of the time series – (2.66 * average of mR). Plot it as the orange line in the top chart.

In this chapter, the author does not explain the reason why XmR Chart work. I will jump a few chapters and read Chapter 11: What Makes the XmR Chart Work?.

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