A process is stable only when parameters of the distribution of a process or product characteristic remain same over time. Only a stable process has the ability to perform in a predictable manner over time. Statistical analysis of process data usually assume that data are obtained from stable process. In the absence of control charts, the hypothesis of process stability is usually assessed by visual examination of the pattern in the run chart. In this paper appropriate statistical approaches have been adopted to detect instability in the process and compared their performance with the run chart of considerably shorter length for assessing its patterns and ensuring the process stability.
Wooluru, Yerriswamy; Swamy, D. R.; and Nagesh, P.
"Approaches for Detection of Unstable Processes: A Comparative Study,"
Journal of Modern Applied Statistical Methods:
2, Article 17.
Available at: http://digitalcommons.wayne.edu/jmasm/vol14/iss2/17