Multivariate Statistical Process Control Based on Principal Component Analysis (MSPC-PCA): Some Reflections and a Case Study in an Autobody Assembly Process

Author： Ferrer Alberto  

Publisher： Taylor & Francis Ltd

ISSN： 0898-2112

Source： Quality Engineering, Vol.19, Iss.4, 2007-10, pp. : 311-325

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Related content

Latent Structures-Based Multivariate Statistical Process Control: A Paradigm Shift

By Ferrer Alberto  

Quality Engineering, Vol. 26, Iss. 1, 2014-01 ,pp. : 72-91

Taylor & Francis Ltd

Access to resources Recommend Favorite

Discussion of “Latent Structures-Based Multivariate Statistical Process Control: A Paradigm Shift”

By Lin Dennis K. J.  

Quality Engineering, Vol. 26, Iss. 1, 2014-01 ,pp. : 96-98

Taylor & Francis Ltd

Access to resources Recommend Favorite

Discussion of “Latent Structures-Based Multivariate Statistical Process Control: A Paradigm Shift”

By Woodall William H.  

Quality Engineering, Vol. 26, Iss. 1, 2014-01 ,pp. : 92-95

Taylor & Francis Ltd

Access to resources Recommend Favorite

An Integrated Approach Based on Principal Component and Multivariate Process Capability for Simultaneous Optimization of Location and Dispersion for Correlated Multiple Response Problems

By Bera Sasadhar   Mukherjee Indrajit  

Quality Engineering, Vol. 25, Iss. 3, 2013-07 ,pp. : 266-281

Taylor & Francis Ltd

Access to resources Recommend Favorite

Quality Quandaries: The Application of Principal Component Analysis for Process Monitoring

By Bisgaard* Søren   Kulahci Murat  

Quality Engineering, Vol. 18, Iss. 1, 2006-01 ,pp. : 95-103

Taylor & Francis Ltd

Access to resources Recommend Favorite