Open AccessThe use of statistical transformation in six sigma analysis
Author(s) -
Mustafid Mustafid,
I. Yulvia,
D. Ispriyanti,
Sugito Sugito,
Abdelilah Hakim
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1943/1/012156
Subject(s) - ewma chart , weibull distribution , control chart , transformation (genetics) , data transformation , normal distribution , sigma , statistical process control , computer science , statistics , mathematics , data mining , process (computing) , data warehouse , biochemistry , chemistry , physics , quantum mechanics , gene , operating system
The basic assumptions in six sigma analysis are use data assumptions from the quality characteristic variables in-control and normal distributed. The use of normal distribution assumptions aims to facilitate the computational and analytical processes. In fact, there are many observational data obtained from industry which are uncontrolled and not normally distributed. The aim of the research is to use exponentially weight moving average (EWMA) as statistical transformation to make data uncontrolled and not normally distributed into data in-control and normal distributed. This research uses a case study with empirical data Weibull distributed, and use the statistics of EWMA to the data can be transformed into in-control and normal distributed. Based on the results of the transformation from empirical data, the EWMA control chart were made to determine the data position of in-control and also measured six sigma values.