We examine how to forecast after a recent break. We consider monitoring for change and then combining forecasts from models that do and do not use data before the change; and robust methods, namely rolling regressions, forecast averaging over different windows and exponentially weighted moving average (EWMA) forecasting. We derive analytical results for the performance of the robust methods rel...

Nonparametric (distribution-free) control charts have been introduced in recent years when quality characteristics do not follow a specific distribution. When the sample selection is prohibitively expensive, we prefer ranked-set sampling over simple random because ranked set sampling-based outperform charts. In this study, proposed nonparametric homogeneously weighted moving average based on Wi...

We introduce QuantTree Exponentially Weighted Moving Average (QT-EWMA), a novel change-detection algorithm for multivariate datastreams that can operate in nonparametric and online manner. QT-EWMA be configured to yield target Run Length (ARL\(_0\)), thus controlling the expected time before false alarm. Control over alarms has many practical implications is rarely guaranteed by algorithms moni...

Process control is widely discussed in the manufacturing process, especially semiconductor manufacturing. Due to unavoidable disturbances manufacturing, different process controllers are proposed realize variation reduction. Since Reinforcement Learning (RL) has shown great advantages learning actions from interactions with a dynamic system, we introduce RL methods for and propose new controlle...