Paper Info
Title
Multivariate Performance Analysis Methods - A Comparison Study
Abstract
It is crucial than ever to measure manufacturing losses due to non-compliance of customer specifications. To assess these losses, industry is widely using proportion of non conformance PNC for performance evaluation of their manufacturing processes. Various methods have been proposed to estimate PNC for univariate quality characteristics, however estimating an accurate PNC for non-normal multivariate correlated quality characteristics is still a challenge for researchers. In this paper we review fitting Burr XII distribution to continuous positively skewed multivariate data using different search algorithm techniques. The proportion of nonconformance PNC for process measurements is then obtained by using only Burr XII distribution, rather than through the traditional practice of fitting different distributions to real data. We also employ artificial neural network based on Burr XII distribution to estimate PNC. The results based on the proposed methods are then compared with the exact proportion of nonconformance using real data from a manufacturing process. . Using the PNC criterion, the results show that the estimated PNC values obtained based on all three methods, simulated annealing, hybrid and artificial neural network are reasonably close to the actual PNC value. However, the estimated PNC based on the simulated annealing method is the closest to the actual PNC value.
Year
DOI
Venue
2011
10.1109/ITNG.2011.109
Information Technology: New Generations
Keywords
Field
DocType
pnc criterion,manufacturing process,estimated pnc,comparison study,actual pnc value,multivariate performance analysis methods,nonconformance pnc,artificial neural network,burr xii distribution,exact proportion,accurate pnc,neural network,quality control,statistical distributions,multivariate data,compass,neural nets,artificial neural networks,simulated annealing,fitting,quality management,search algorithm,process capability analysis,burr distribution
Simulated annealing,Process capability,Data mining,Skewness,Multivariate statistics,Computer science,Burr distribution,Probability distribution,Statistics,Univariate,Artificial neural network
Conference
ISBN
Citations 
PageRank 
978-0-7695-4367-3
0
0.34
References 
Authors
6
3
Name
Order
Citations
PageRank
S. Ahmad1153.91
Mali Abdollahian2254.55
B. Abbasi314519.89