Please use this identifier to cite or link to this item:
Title: Development of univariate control charts for non-normal data
Authors: Çiflikli, Cihan
Advisors: Doymaz, Fuat
Publisher: Izmir Institute of Technology
Abstract: In this study, a new control chart methodology was developed to address statistical process monitoring issue associated with non-normally distributed process variables. The new method (NM) was compared aginst the classical Shewhart control chart (OM) using synthetic datasets from normal and non-normal distributions as well as over an industrial example. The NM involved taking the difference between the specified probability density estimate and non-parametric density estimate of the variable of interest to calculate an error value. Both OM and NM were found to work well for normally distributed data when process is in-control and out-of control situation. Both methods could be returned back to normal operation upon feeding in control data. In case of non-normally distributed data, the OM failed significantly to detect small shifts in mean and standard deviation, however the NM maintained its performance to detect such changes. In the application to an industrial case (data were obtained from a local cement manufacturer about a 90 micrometer sieve fraction of the final milled cement product), the NM methodology outperformed the OM by recognizing the change in the mean and variance of the measured parameter. The data were tested for its distribution and were found to be non-normally distributed. Violations beyond the control limits in the new developed technique were easily observed. The NM was found to successfully operate without the necessity to apply run rules.
Description: Thesis (Master)--Izmir Institute of Technology, Materials Science and Engineering, Izmir, 2006
Includes bibliographical references (leaves: 50-51)
Text in English; Abstract: Turkish and English
xii, 75 leaves
Appears in Collections:Master Degree / Yüksek Lisans Tezleri

Files in This Item:
File Description SizeFormat 
T000228.pdfMasterThesis3.44 MBAdobe PDFThumbnail
Show full item record

CORE Recommender

Page view(s)

checked on Apr 22, 2024


checked on Apr 22, 2024

Google ScholarTM


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.