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This article will explain in detail about the normal distribution ability analysis after Johnson transformation in Minitab17. The content of the article is of high quality, so the editor shares it for you as a reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

(2) Analysis of normal distribution ability after Johnson transform

[example 17-5] an enterprise collected the power (W) measurement data of 100 chargers, the subgroup size is 1, the data is non-normal distribution, ULS=0.43;LSL=0.26. Try to analyze the ability of normal distribution. (charger power .MTW)

First, open the worksheet: "Charger Power .MTW".

Second, capability analysis (normal distribution) (Capability Analysis (Normal Distribution)) main dialog box (see figure 17-14), [data arrangement (Data are arranged as)] is [single column (Single column)], and select "C2 (power)" and [subgroup size (Subgroupsize)] is 1. Set [lower limit (Lower spec)] to 0.26 and [upper limit (Upper spec)] to 0.43.

3. In the Transform dialog box (see figure 17-15), select [Johnson transform (for global analysis only) (Johnson transformation (for overall analysis only))] and set [the selected best fit P value is (P-Valueto select best fit)] to 0.1. (note: by individual distribution identification, Johnson transformation, normality test, AD=0.407,P=0.344 > 0.1)

Fourth, options (Options) dialog box (see figure 17-17), do not set [goal (add Cpm to the table) (Target (adds Cpm to table))] and do not select [including confidence interval (Include confidence intervals)], other choices are the same as figure 17-17.

V. main results and analysis

The main results are as follows: 1. From the ability histogram of the original data in the upper left corner, it can be seen that the data are skewed and do not meet the conditions of normal distribution capability analysis. After Johnson transformation, the best transformation is SB distribution family, and the best transformation function is

. From the ability histogram of the transformed data, it can be seen that the transformed data approximately obeys the normal distribution, and the transformed data are all smaller than USL.

2. The overall capability index, Pp=1.17, is between 1 and the benchmark value (1.33), indicating that the process capability is normal, but there is still room for improvement, while Ppk=1.05, between 1 and the benchmark value (1.33), indicates that the distribution center deviates slightly, and there will be no more nonconforming products if the process is not adjusted. As a result, manufacturers can improve the process by reducing variation.

3. Performance index, the unqualified rate of charger power is 970ppm.

This is the end of the analysis of the normal distribution ability after the Johnson transformation in Minitab17. I hope the above content can be helpful to everyone and learn more knowledge. If you think the article is good, you can share it for more people to see.

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