Here's how you'd perform the relevant analyses in Minitab, along with interpretations for assessing 6-sigma capability:
1. Data Requirements: You need data from your process. This data should represent measurements taken from the process over a sufficient timeframe. The amount of data needed depends on your process variability. More variability requires more data for accurate estimates.
2. Choosing the Right Analysis:
* Capability Analysis (Normal): Use this if your data is approximately normally distributed. This is the most common approach. Minitab will provide you with several capability indices, the most relevant for 6-sigma assessment are:
* Pp, Ppk: These indices assess process potential (Pp) and process performance (Ppk) considering only the spread of your data. A 6-sigma process generally aims for Pp and Ppk ≥ 1.5 (corresponding to a 4.5 sigma process, as the 6-sigma specification usually considers 1.5 sigma for shifts and drift). For a true 6-sigma capability (considering no shifts or drift), Pp and Ppk ≥ 2.0 would be ideal, but rarely achieved in real-world applications.
* Cp, Cpk: These indices are similar to Pp and Ppk, but also consider the process centering relative to specification limits. Like Pp and Ppk, a 6-sigma process is often represented by values of Cp and Cpk ≥ 1.5. Again, ≥ 2.0 would be an ideal, but rarely achieved, true 6-sigma performance.
* Capability Analysis (Nonnormal): Use this if your data is not normally distributed (check histograms and normality tests in Minitab). Minitab will offer various non-parametric indices that are less precise but can still provide valuable insights. Interpretation of these indices in relation to 6-sigma is more complex and often requires experience.
3. Steps in Minitab (using Capability Analysis (Normal) as an example):
1. Enter your data: Input your process measurements into a Minitab worksheet column.
2. Specify your specification limits: You need the upper and lower specification limits (USL and LSL) for your process.
3. Go to Stat > Quality Tools > Capability Analysis > Normal: This opens the dialog box.
4. Select your data column.
5. Enter your USL and LSL.
6. Click OK.
Minitab will generate various graphs and statistics, including the Cp, Cpk, Pp, and Ppk indices mentioned above.
4. Interpretation:
Examine the Cp, Cpk, Pp, and Ppk values. As mentioned before, values of 1.5 or greater are often considered to indicate a 6-sigma level of capability (though 2.0 is closer to a truer 6-sigma), *but context is crucial*. Remember that these are just indicators and don't provide a definitive "6 sigma" label. Consider the following factors:
* Short-term vs. Long-term Capability: The analysis above often reflects short-term capability. Long-term capability analyses account for shifts in the process mean over time. These are often better indicators of true performance. Minitab can also perform such analyses.
* Process Stability: Your process needs to be stable (in statistical control) for capability analysis to be meaningful. Use control charts (Minitab's Control Charts menu) to verify this before assessing capability.
* Data Quality: Ensure the data accurately reflects the process. Outliers can significantly impact your results.
In summary, Minitab doesn't give you a single "6 Sigma" number. Instead, it provides tools to assess process capability, allowing you to infer whether your process achieves a level of performance consistent with commonly accepted 6-sigma interpretations of capability indices like Cpk and Ppk. Careful consideration of the indices, process stability, and the limitations of the analysis are critical for making accurate judgments.