Paper Info
Title
Nonlinear Profile Monitoring of Reflow Process Data Based on the Sum of Sine Functions.
Abstract
In most statistical process control (SPC) applications, it is often assumed that the quality of a process or product can be adequately represented by the distribution of a univariate quality characteristic. However, in some particular situations, the quality-related response of interest is not a single variable but a function of some independent variables. Such a functional relationship is called a profile. Recently, profile monitoring has drawn considerable attention in the statistical process control literature. This article proposes a new approach for the reflow process data, which applies the sum of sine functions to model the nonlinear profiles and then the vector of parameter estimates is monitored using the Hotelling T-2 and metric control charts. Through an actual data set of the reflow process, the proposed approach is compared with the polynomial regression approach in phase I and phase II analyses. The experimental results show that the proposed approach demonstrates good abilities to detect outlying profiles in phase I and provides better out-of-control average run length performances than the polynomial regression approach in phase II. Copyright (C) 2012 John Wiley & Sons, Ltd.
Year
DOI
Venue
2013
10.1002/qre.1425
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
Keywords
Field
DocType
statistical process control (SPC),nonlinear profiles,sum of sine functions,polynomial regression,average run length (ARL),Hotelling's,(2) statistics,metrics
Econometrics,Nonlinear system,Hotelling's T-squared distribution,Polynomial regression,Sine,Control chart,Statistical process control,Variables,Univariate,Statistics,Mathematics
Journal
Volume
Issue
ISSN
29
5
0748-8017
Citations 
PageRank 
References 
8
0.66
7
Authors
3
Name
Order
Citations
PageRank
Shu-Kai S. Fan128017.82
Yuan-Jung Chang2101.36
Nafy Aidara380.66