Measuring the Performance of an Eigenvalue Control Chart for Monitoring Multivariate Process Variability
DOI:
https://doi.org/10.11113/mjfas.v7n2.249Keywords:
Statistical Process Control, Multivariate Dispersion, Covariance Matrix, Generalized Variance, Vector Variance,Abstract
In manufacturing process, it is very important to control and monitor the stability of a process such that a high quality product will be produced. The most common statistical tool used for monitoring the stability of a process is the control chart. In recent applications of control charting methods, there is a need to construct a control chart that is able to represent the behaviour of a multivariate process since in many manufacturing processes; quality of a product is determined by the joint-level of several quality characteristics. For this reason, in this paper, a new control chart is introduced for monitoring the stability of multivariate process in terms of the process variability. The proposed method is based on charting each of the eigenvalues of a covariance matrix. To show the efficiency of the proposed method, we conduct a simulation study and compare the performance of the proposed method with the existing method. A real example will be presented to illustrate the advantage of our proposed method.References
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