Monitoring the alternating renewal processes with Weibull window-censored data

Many applications, especially in the industrial or medical fields, frequently encounter window-censored alternating renewal process (ARP). Process monitoring for window-censored ARP observations has received increasing attention recently. However, some conventional methods are inadequate as they are mainly designed considering only one censoring mechanism. In this paper, we utilize a 'residual life' distribution, and propose a novel online monitoring strategy that combines the likelihood with all kinds of censoring information, along with a modified conditional expected value exponentially weighted moving average control chart. The construction and implementation of these control schemes are studied by simulations which give desirable in-control and out-of-control performances and are robust under various scenarios. Finally, this paper shows by example based on driver's glance data that the proposed methods have a good monitoring effect in practical scenarios.