Multivariate Control Charts for Manufacturing Processes with Multivariate Data and Their Applications

Virojana Tantibadaro

Authors

Virojana Tantibadaro Faculty of Engineering and Technology, Punyapiwat Institute of Management, Nonthaburi, Thailand

Keywords:

Quality Characteristics, Multivariate Data, Multivariate Control Charts, Univariate Control Charts, Out-Of-Control Signal, False Alarm

Abstract

Quality of individual units of a product from any given production process usually consists of more than one characteristics, which are considered to be a set of multivariate data in nature. Multivariate data analysis therefore seems to be more appropriate for this type of data. However, its use is not common in industrial settings. For example, implementation of multivariate control charts to analyze the status of a production process involves relatively complex computations, thus creating a barrier to practitioners who normally prefer simpler univariate control charts even when the latter is less efficient. This article aimed to present an experimental implementation of multivariate control charts by relying on case studies for illustrating the tools and to compare the results of using univariate control charts in the same case studies. The results of the comparison revealed that the use of multivariate control charts for multivariate processes provided a more accurate analysis of the state of the processes than using univariate control charts. In addition, a practical method to determine which of the monitored variables exhibited responsibility for out-of-control signals on the multivariate control charts is presented.

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