Open AccessMonitoring Industrial Process using a Robust Modified Mean Chart
Author(s) -
M. R. Sindhumol,
Michele Gallo,
M. R. Srinivasan
Publication year - 2019
Publication title -
österreichische zeitschrift für statistik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.342
H-Index - 9
ISSN - 1026-597X
DOI - 10.17713/ajs.v48i1.765
Subject(s) - control chart , standard deviation , statistical process control , estimator , control limits , chart , process (computing) , statistics , computer science , x bar chart , mathematics , operating system
Shewhart control chart is the most popular and widely used Statistical process Control tool to monitor process. It is developed under the assumption of independent and normally distributed process. In order to control process mean and standard deviation, robust estimator of these parameters can be better alternatives as charts based on that are more resistant to moderate changes in process distribution. Modified Maximum Likelihood Estimator (MMLE) for mean and standard deviation is a pair of statistics with good robust properties. Authors introduced these measures to control charting process and investigate the advantages of using it. A modification to mean based on MMLE and its standard deviation are introduced to improve industrial process performance. Using Monte Carlo simulation method, performance of this chart is compared with classical control chart. Performance is also studied based on the Average Run Length.