Exponentially weighted moving average control graphs for processes with Type I right-censored weibull distribution

The lifetime data commonly encountered today is a type of data associated with multiple fields such as production and health. Life span data, especially in the production sector, is of great importance in measuring the reliability of the system. Regardless of the field, it is crucial to monitor and control the process to ensure the sustainability of the system. One of the major problems arising here is that the data generated within the guiding system for controlling the process may be censored due to cost or time constraints. In this case, the commonly used statistical process control methods lose their effectiveness in accurately conveying the system. In this thesis, the distribution parameters were estimated for censored data with Weibull distribution; EWMA control charts were created under different statistics developed for censored data. The performance of control over different parameter values and censorship rates was evaluated with a simulation study and an application was made on real- life data.