|dc.contributor.author||Abughazaleh, Tareq Ali Ibrahim||
|dc.description.abstract||This research deals with some Statistical Quality Control (SQC) methods, which are
used in quality testing. It investigates the problem encountered with statistical process
control (SPC) tools when small sample sizes are used. Small sample size testing is a
new area of concern especially when using expensive (or large) products, which are
produced in small batches (low volume production).
Critical literature review and analysis of current technologies and methods in SPC
with small samples testing failed to show a conformance with conventional SPC
techniques, as the confidence limits for averages and standard deviation are too wide.
Therefore, using such sizes will provide unsecured results with a lack in accuracy.
The current research demonstrates such problems in manufacturing by using
examples, in order to show the lack and the difficulties faced with conventional SPC
tools (control charts). Weibull distribution has always shown a clear and acceptable
prediction of failure and life behaviour with small sample size batches. Using such
distribution enables the accuracy needed with small sample size to be obtained. With
small sample control charts generate inaccurate confidence limits, which are low. On
the contrary, Weibull theory suggests that using small samples enable achievement of
accurate confidence limits. This research highlights these two aspects and explains
their features in more depth. An outline of the overall problem and solution point out
success of Weibull analysis when Weibull distribution is modified to overcome the
problems encountered when small sample sizes are used.
This work shows the viability of Weibull distribution to be used as a quality tool and
construct new control charts, which will provide accurate result and detect nonconformance
and variability with the use of small sample sizes. Therefore, the new
proposed Weibull deduction control charts shows a successful replacement of the
conventional control chart, and these new charts will compensate the errors in quality
testing when using small size samples.||en_US
|dc.publisher||University of Hertfordshire||en_US
|dc.subject||Statistical quality control, Manufacturing processes, Mathematical statistics, Operations research||en_US
|dc.title||The viability of Weibull analysis of small samples in process manufacturing||en_US