In some production environments the defect rates are considerably low such that
measurement of fraction of nonconforming items reaches parts per million level. In
such environments, monitoring the number of conforming items between
consecutive nonconforming items, namely the time between events (TBE) is often
suggested. However, in the design of control charts for TBE monitoring a
common practice is the assumptions of known process parameters. Nevertheless,
in many applications the true values of the process parameters are not known.
Their estimates should be determined from a sample obtained from the process at a
time when it is expected to operate in a state of statistical control. Additional
variability introduced through sampling may significantly effect the performance
of a control chart. In this study, the effect of parameter estimation on the
performance of Time Between Events Exponentially Weighted Moving Average
(TBE EWMA) schemes is examined. Conditional performance is evaluated to
show the effect of estimation. Marginal performance is analyzed in order to make
recommendations on sample size requirements. Markov chain approach is used for
evaluating the results.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12610031/index.pdf |
| Date | 01 September 2008 |
| Creators | Ozsan, Guney |
| Contributors | Koksal, Gulser |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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