We provide an overview and perspective on the Phase I collection and analysis of data for
use in process improvement and control charting. In Phase I, the focus is on understanding …

In many applications the quality of a process or product is best characterized and
summarized by a functional relationship between a response variable and one or more …

Statistical process control plays a key role in today's highly competitive industrial
environment since it allows quality practitioners to timely detect out‐of‐control situations and …

Pertaining to industrial applications in which the response variable of interest is binary, this
paper studies how the profile functional relationship between the response and predictor …

Profile monitoring is a relatively new technique in quality control best used where the
process data follow a profile (or curve) at each time period. Little work has been done on the …

Nonparametric or distribution-free charts are useful in statistical process control when there
is a lack of or limited knowledge about the underlying process distribution. Most existing …

In many applications of manufacturing and service industries, the quality of a process is
characterized by the functional relationship between a response variable and one or more …

Abstract Machine learning methods have been widely used in different applications,
including process control and monitoring. For handling statistical process control (SPC) …

In many industrial processes, the quality characteristic of interest has a relation (linear or
non-linear) with other supporting variable (s). Simple linear profile is a well-known term used …

In many manufacturing processes, study variable is not the only quality characteristic, but
there may exist some explanatory variable (s) that are associated with the study variable …