Projection Methods for Process Analysis and Statistical Process Control: Examples and Experiences from Industrial Applications

Article

Kourti, Theodora; MacGregor, J. F.   (1998, ASQ)   McMaster University, Hamilton, ON

Annual Quality Congress, Philadelphia, PA    Vol. 52    No. 0
QICID: 10665    May 1998    pp. 73-77
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Article Abstract

Methods like principle components analysis (PCA) and partial least squares (PLS) project the information from a highly dimensional monitoring space into a lower dimensional space, thereby allowing multidimensional control charts to be as useful and simple as single variable charts. These methods have worked with a variety of processes, whether continuous or batch. This paper provides two examples. One covered a continuous recovery process at a petrochemical plant. Over 400 process variables collected daily for 498 days were projected into seven components that accounted for 93 percent of recovery and purity variation. In the second example, 80 wafer electronic test variables in a semiconductor manufacturing operation were used simultaneously as the response space.

Keywords

Process analysis,Statistical process control (SPC),Process control


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