An Approach to Non-normal Process Capability Analysis Using Johnson Transformation

Abstract

The process capability analysis requires that the quality characteristics data follow normal distribution. In actual production, many stable processes do not necessarily satisfy the assumption of normal distribution. Many scholars and quality engineers have proposed methods to transform non-normal data into normal data so that these data can be analyzed using the process capability indices, resulting in reasonable and effective conclusions. One approach to solve this problem is to use the Johnson distribution system to convert these non-normal data. This paper proposes a systematic method to deal with non-normal data and calculate its process capability indices. The method is combined with the percentage fitting of Johnson distribution system, and the steps are given in detail. Finally, this method is applied to a practical case study and the process capability indices can be calculate. The effectiveness and practicability of the method are verified by simulation experiments. In this paper, Minitab analysis software is used to assist with strong operability and convenience, and can be used to guide production practices.

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