Statistical Monitoring of a Sealing Process by Means of Multivariate Accelerometer Data

Abstract

A multivariate control charting procedure is applied to on-line seal quality evaluation of a packaging process by means of an accelerometer. Based on physical insight it is elucidated in a first step which information in the raw accelerometer data are relevant with respect to the goal of detecting bad seals. Next, a principal component analysis (PCA) based processing of this multivariate information is performed and the related Hotelling's T 2 and Q test statistics are calculated for further data representation. In a last step proper control charts based on these statistics are used as a process monitoring tool for on-line distinction between good and bad seals. The obtained results show that a correct monitoring of accelerometer signals can be a useful tool for the on-line detection of ‘bad seals’ in a packaging process.

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