Conveners
CONTRIBUTED Quality 3
- Jeroen de Mast (University of Waterloo + JADS)
Phase-I monitoring plays a vital role as it helps to analyse the process stability retrospectively using a set of available historical samples and obtaining a benchmark reference sample to facilitate Phase-II monitoring. Since, at the very beginning process state and its stability is unknown, trying to assume a parametric model to the available data (which could be well-contaminated) is...
The univariate Bayesian approach to Statistical Process Control/Monitoring (BSPC/M) is known to provide control charts that are capable of monitoring efficiently the process parameters, in an online fashion from the start of the process i.e., they can be considered as self-starting since they are free of a phase I calibration. Furthermore, they provide a foundational framework that utilizes...
Modern data acquisition systems allow for collecting signals that can be suitably modelled as functions over a continuum (e.g., time or space) and are usually referred to as profiles or functional data. Statistical process monitoring applied to these data is accordingly known as profile monitoring. The aim of this research is to introduce a new profile monitoring strategy based on a...