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In the 28th Minitab tutorial, we visit the last process step of the die-casting process for the production of skateboard axles. The production of skateboard Axles at Smartboard Company is currently carried out using the die-casting process. In order to achieve the strength values required by the customer in the skateboard axles, they are subjected to a heat treatment process at the end of the die-casting process. For this purpose, the skateboard axles are brought to heat treatment temperature in a continuous furnace, and then cooled to room temperature in a water bath. During the rapid cooling process, undesirable changes in the shape of the skateboard Axles can occur, which are still accepted by the customer to a certain extent and must therefore not exceed a certain value in accordance with customer requirements. The core of this Minitab tutorial unit is to find out whether the heat transformation process has a required process performance PPk of at least 1.33, in relation to the maximum permissible shape change. However, we will find out right at the beginning of the training unit, that our data in this sample data set does not follow the laws of normal distribution. A central topic in this training unit will therefore be, to first work out which distribution laws our non-normally distributed data set most closely follows. In this context, we will get to know the very helpful function “ Individual Distribution Identification“, in order to be able to assess an existing non-normally distributed data landscape by means of a corresponding so-called mathematical data transformation, by using the already known performance indicators. We will get to know all the transformation functions that are relevant in practice, and understand the system and criteria that can be used to determine the appropriate transformation function, for the respective practical scenario. As part of our process capability analysis of non-normally distributed process data, we will see how the quality team uses the useful and efficient „Capability Six Pack“ option, to efficiently evaluate the test for normal distribution according to Anderson Darling, and the stability analysis using the corresponding control charts in a single step, in addition to the actual capability analysis. This means that we can use the available results based on the necessary data transformation of the non-normally distributed data set, to assess whether the process performance required by the customer is achieved, and how high the error or process yield is based on the available process performance.


  • Non-normally distributed process data, fundamentals
  • Analysis of process data using descriptive statistics
  • Boxplot Analysis
  • Test for normal distribution according to Anderson Darling
  • Identification of the distribution type by using data transformation
  • Checking the process stability of non-normally distributed data
  • Use of the „Capability Six Pack“ option
  • Analysis of the process capability based on capability plot and process yield