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A Toolbook for Quality Improvement and Problem Solving (contents)

Process Capability: How to do it

The Quality Toolbook > Process Capability > How to do it

When to use it | How to understand it | Example | How to do it | Practical variations

 

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How to do it

  1. Identify the objectives of measuring the Process Capability. Typical reasons include:
    • Prioritization of process improvement projects.
    • Investigation of causes of specification limit failure.
    • Setting realistic specification limits for process.
    • Determining results of improvements made.
       
  2. Define the process that is to be investigated. Typically this will encompass all actions and variables that will affect the item to be measured and which may be changed. For example, if measuring the elasticity of a rubber cord, both the molding and curing processes may be included in the study, when both are believed to contain variables that affect the elasticity.
     
  3. Identify the actual measure to make. This is usually easy to find, as it has specification limits already defined.
  4. Also define the process of measurement in order that measurements may be consistently made. This may include such activities as verification of measurement equipment accuracy, training of people doing the measurement, etc.
     

  5. Take sample measures of the process at random times over a period which is long enough for all variables within the process to travel through their full range of possible values. Also take enough measurements to enable this range to be identifiable, as detailed in step 5.
  6. The measurements should be made under normal working conditions, because if machines and other items in the process are set up specially for measurements to be made, the result will only show the capability of the process under 'best case' conditions.
     

  7. Verify that the process is in a 'state of statistical control', with no special causes of variation. This can be performed by plotting Control Charts and checking for significant trends or points outside the control limits. If special causes are found, they must be eliminated before Process Capability indices can be measured.
  8. Make this as accurate as possible by using Average and Range (X-bar, R) Control Charts, plotting at least 25 points, for example with 100 measurements and a sample size of 4. If so many measurements are not possible, use Individuals and Moving Range (X, MR) Control Charts with at least 31 measurements.
     

  9. Verify that the process has a Normal (bell-shaped) distribution, for example by plotting a Histogram and inspecting its shape.
     
  10. Calculate the Capability Indices, using the same data that was used for drawing the Control Charts, as below.

 

Fig. 1. Capability Index calculation

    A common short-cut method of estimating the standard deviation is used in this example, where a table value is combined with the average range. This is useful where subgroup, average and range measurements are already made for a Control Chart. If an Individuals Control Chart is used, then the standard deviation can be calculated as shown in Chapter 5.
     

  1. Interpret and act on the results. Thus, in the figure above, Cp shows that the process is reasonably capable of meeting specification, but Cpk shows that it also is performing off-center. The process may then be examined to determine whether it can be permanently centered and whether the variation can be reduced some more.

 

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