Advanced Statistical Procedures for Effective Monitoring of Processes with Multiple Characteristics

Project: Research

View graph of relations


Statistical Process Control (SPC) was traditionally established for the manufacturingindustry. In the past, we have investigated time-between-events (TBE) control charts thathave proven to be very effective with reference to the monitoring and control of high quality manufacturing processes. In this proposed research, we will develop and investigate some advanced control charts for TBE and related process characteristics targeted for more generalized applications, with a focus on multivariate situations. Another issue of investigation is the effective use of an exponentially weighted moving average (EWMA) or cumulative sum (CUSUM) approach to increase the sensitivity when applied to multivariate distributions. We will also investigate the modelling and monitoring of extreme-value characteristics, such as those related to peak usage, extreme damage or performance levels in important areas beyond manufacturing. Furthermore, nonparametric methods could be more useful and effective due to the fact that there are fewer restrictions on the distribution.


Project number7004460
Grant typeSRG-Fd
Effective start/end date1/09/1511/04/18