Abstract:
Jointly monitoring the process mean and variance has
become a well-known topic in statistical quality control literature
after it is considered as a bivariate problem. Many joint
monitoring schemes have been proposed by using the Shewhart,
cumulative sum and exponentially weighted moving average
techniques. In this paper, best performing schemes from each
technique has been selected and compared for their performance
using average run length properties. It was found that selection of
better joint monitoring scheme based on the shift in mean and
variance to be detected quickly. In particular, the Shewhart
distance joint monitoring scheme performs well when there is
larger shifts in mean, variance or in both. In addition, the
Shewhart distance joint monitoring scheme performs specific
when there is no shift in mean and decrease in variance. For the
smaller shifts in mean, variance or in both, cumulative sum and
exponentially weighted moving average joint monitoring schemes
can be recommended. At this scenario exponentially weighted
moving average joint monitoring scheme performs marginally
better than the cumulative sum scheme
