Monitoring Autocorrelated Reliability Data in Multistage Processes

In this paper, multistage process monitoring with the purpose of improving the product reliability is addressed. To this end, the process output is usually inspected under specific loadconditions and the tensile strength of reliability-related quality characteristic is measured. However, in some cases, theobservations from the process output are autocorrelated. This makes the use of existing monitoring procedures futile.Therefore, the proportional hazards (PH) models have been modified to effectively justify the effect of cascade property in line with the autocorrelation issue and three monitoring schemesare devised. The problem of unobserved heterogeneity is discussed as well. The simulation-based study is conducted toinvestigate the performance of the proposed control charts. Theresults reveal that the cumulative sum control chart is superior in that it can detect shifts much faster. Finally, the impact of ignoring autocorrelation has been studied which confirms the significant effect of autocorrelation on the performance of the process control