Open AccessMonitoring ZA Fertilizer Production using Multivariate Maximum Chart Based on Bootstrap Control Limit
Author(s) -
Rumaisa Kruba,
Muhammad Mashuri,
Dedy Dwi Prastyo
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 - 10.1088/1742-6596/1752/1/012020
Subject(s) - control chart , control limits , ewma chart , multivariate statistics , x bar chart , shewhart individuals control chart , statistics , chart , \bar x and r chart , mathematics , statistical process control , computer science , process (computing) , operating system
Control charts are extensively used to monitor the production process. When there is more than one variable process are considered, the multivariate control charts are typically employed to monitor the mean vector and the variability process separately. In recent years, control charts have been developed for monitoring mean process and variability process simultaneously in a chart. A Maximum multivariate control chart (Max-Mchart) is one of the simultaneous multivariate control charts relying on exact distribution control limit. The objective of this paper is to evolve Max-Mchart based on Bootstrap control limits. This paper also compares Max-Mchart over the Hotelling T 2 and Generalized Variance (GV) control chart. The interpretive examples are implemented to demonstrate the applications of the ZA fertilizer production dataset in carbonation step.