ANALYSIS OF THE BENEFITS OF USING DESIGN OF EXPERIMENTS IN VALIDATION OF A NEW METHOD/PRODUCT

Abstract

Total Quality Management as a holistic management system is widely practical in every organization these days and one of the foundations of TQM which should be taken into account in all functions of the company is continuous improvement. In order to improve the quality and establish the qualification of a new product/method – based on recent and future customer needs-, validation is a useful process during the development and before launching that product/method. The variability is also important to be reduced for quality improvement. Statistical methods are the most capable techniques for the purpose of validation and reducing variability in any organization. Design of Experiments is one of the statistical methods in which the important sources of variability are identified besides it helps to establish decisions on facts and execute quality improvements by systematic data gathering.

Keywords

• Quality Management, Continues improvement, Statistical method, Design of experiments, Validation, Experimental

References

1. Barrentine, L. B.(1999), An Introduction to Design of Experiments: A Simplified
2. Approach.Milwaukee(WI): ASQ. Bergman, B. & Klefsjö, B. (2003), Quality from customer needs to customer satisfaction. Translated from Swedish by K.Ashing. Lund : Studentlitteratur.
3. Boqué, R. Maroto, A. Riu, J. & Rius, F. X. (2002), Validation of Analytical
4. Methods. Grasas y Aceites , http://grasasyaceites.revistas.csic.es/index.php/grasasyaceites/article/view/295/29 , [Accessed 13 Nov. 2011]
5. C. Montgomery, D. (2005) , Introduction to Statistical Quality Control. 5th ed.
6. Hoboken(NJ): John Willy & Sonss, Inc . Dr. Dixon, D. Dr. Eatock, J. Prof. Meenan, B.J. & Morgan, M.(2006),
7. Application of Design of Experiment Techniques to Process Validation in Medical Device Manufacture. Journal of Validation Technology, http://www.gxpandjvt.com/ivtnews/templates/IVTNews.aspx?articleid=1439&zo neid=31, [Accessed 11 Nov. 2011]
8. Dyadem Press, 2003. Guidelines for Failure Mode and Effects analysis for

9. Automative, Aerospace and General Manufacturing Industries. http://books.google.com/books?id=a37wp6Xd4LoC&pg=PT244&dq=Guidelines +for+Failure+Mode+and+Effects+analysis+for+Automative,+Aerospace+and+Ge neral+Manufacturing+Industries#v=onepage&q=&f=false, [Accessed 5 Nov. Küppers, S.(1997), A validation concept for purity determination and assay in the pharmaceutical industry using measurment uncertainty and statistical process control. Accred Qual Assur, http://www.springerlink.com/content/xed2f0mumfex6kd2/fulltext.pdf Accessed 25 Oct. 2011]
10. Srikaeo, Kh. & Hourigan, J.A. (2002), The use of statistical process control (SPC) to enhance the validation of critical control points (CCPs) in shell egg washing. Food Control, http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6T6S- T706-1
11. R&_cdi=5038&_user=646739&_orig=search&_coverDate=07%2F31%2F2002&
12. _sk=999869995&view=c&wchp=dGLbVtz- zSkWA&md5=a1ab7a9205526008c4a2e46736e93c22&ie=/sdarticle.pdf , Accessed 7 August 2009]
13. Şenol, Ş., 2007. Poisson Process Approach to Determine The Occurrence Degree in Failure Mode and Effect Reiablity Analysis. Quality Management Journal , http://www.scribd.com/doc/6812849/Quality-Manage-Men-Journal-April2007
14. VG, [Accessed 10 August 2009]
15. Taverniers, I. De Loose, M. & Van Bockstaele, E., 2004. Trends in quality in the analyticallaboratory. II. Analytical method validation and quality assurance.
16. Trends in Analytical Chemistry, http://www.mendeley.com/research/trends-in- quality-in-the-analytical-laboratory-ii-analytical-method-validation-and-quality- assurance/, [Accessed 12 Oct. 2011]