Use of Change-Point Analysis for Process Monitoring and Control - A better method for trend analysis than CUSUM and control charts. - BioPharm International

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Use of Change-Point Analysis for Process Monitoring and Control
A better method for trend analysis than CUSUM and control charts.


BioPharm International
Volume 22, Issue 8

SUMMARY

Change-point analysis is a powerful statistical tool for detecting shifts over time in a data set. The analysis can be run using Excel or Change-Point Analyzer, and can work with any data distribution and data type (continuous, categorical, or attribute). Multiple changes can be detected using change-point analysis in the mean or variation of a data set. It can be used in three types of analysis: 1) verification of improvements, 2) problem solving, and 3) trend analysis.

Change-point analysis offers several advantages over other methods of detecting data shifts. Cumulative sum (CUSUM) charts have historically been used for this purpose; however, that technique does not yield a confidence level. Using CUSUM charts in combination with bootstrapping, change-point analysis can produce a confidence level for every change in the mean or variation detected. The software application Change-Point Analyzer produces a confidence interval that provides 95% confidence that a change occurred within the bounds of the interval. Also, using trend analysis with control charts has several limitations that do not arise with change-point analysis. For example, change-point analysis can work with any data distribution and data type. With control charting, a different type of control chart is required for each data type and it is advised to only use trend rules on normally distributed data. Furthermore, change-point analysis can detect more subtle changes than control charts and produces fewer false positives.

ACKNOWLEDGEMENTS

The authors would like to acknowledge several people who contributed to this work. Cathy Sar, Danny Pitpit, and Allan Fajardo contributed to the potency targeting improvement project that formed the basis for one of the case studies presented here. Sundar Ramanan, PhD, contributed to the yield improvement case study. We are grateful to Yeong Wang, PhD, Michael Bellomo, and Wayne Taylor, PhD, for helpful advice in the preparation of the manuscript.

Patrick Gavit is a technical director, Yasser Baddour is a research scientist, and Rebecca Tholmer is a manager, quality, all at Baxter Healthcare Corp., Los Angeles, CA, 818.507.8237,

REFERENCES

1. Bandurek GR. Cumulative sum charts for problem solving. BioPharm Int. 2008 May;21(5):58–67.

2. Taylor WA. Change-Point Analysis: A Powerful New Tool For Detecting Changes. 2000. Available from: http://www.variation.com/cpa/tech/changepoint.html.


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