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Multivariate SPC for total inertial tolerancing

Published online by Cambridge University Press:  06 March 2014

M. Pillet ,
A. Boukar ,
E. Pairel ,
B. Rizzon ,
N. Boudaoud  and
Z. Cherfi
M. Pillet*
Affiliation:
SYMME Laboratory – Université de Savoie, 7 chemin de Bellevue, 74944 Annecy, France
A. Boukar
Affiliation:
SYMME Laboratory – Université de Savoie, 7 chemin de Bellevue, 74944 Annecy, France
E. Pairel
Affiliation:
SYMME Laboratory – Université de Savoie, 7 chemin de Bellevue, 74944 Annecy, France
B. Rizzon
Affiliation:
SYMME Laboratory – Université de Savoie, 7 chemin de Bellevue, 74944 Annecy, France
N. Boudaoud
Affiliation:
ROBERVAL Laboratory, UMR CNRS 6253, Université de Technologie de Compiègne, 60200 Compiègne, France
Z. Cherfi
Affiliation:
ROBERVAL Laboratory, UMR CNRS 6253, Université de Technologie de Compiègne, 60200 Compiègne, France
*
⋆ Correspondence:maurice.pillet@univ-savoie.fr
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Abstract

This paper presents a joint use of the T2 chart and total inertial tolerancingfor process control. Here, we will show an application of these approaches in the case ofthe machining of mechanical workpieces using a cutting tool. When a cutting tool inmachining impacts different manufactured dimensions of the workpiece, there is acorrelation between these parameters when the cutting tool has maladjustment due to badsettings. Thanks to total inertial steering, the correlation structure is known. Thispaper shows how T2 charts allow one to take thiscorrelation into account when detecting the maladjustment of the cutting tool. Then thetotal inertial steering approach allows one to calculate the value of tool offsets inorder to correct this maladjustment. We will present this approach using a simpletheoretical example for ease of explanation.

Keywords

MachiningadjustmentT2multivariateinertial tolerancing
Type
Research Article
Information
International Journal of Metrology and Quality Engineering , Volume 4 , Issue 3 , 2013 , pp. 169 - 175
Copyright
© EDP Sciences 2014

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References

M. Pillet, Improving the productivity and industrial deployment of Inertial Tolerancing – Améliorer la productivité, déploiement industriel du tolérancement inertiel (Eyrolles, Éditions d’Organisation, 2010)
M. Pillet, Inertial tolerancing in the case of assembled products. Recent advances in integrated design and manufacturing in mechanical engineering, pp. 85–94, ISBN 1-4020-1163-6
P.A. Adragna, M. Pillet, S. Samper, F. Formosa, Guaranteeing a maximum Non-Conformity Rate on the assembly resulting from a statistical tolerancing approach, Computer Aided Tolerancing (CAT), Erlangen, Germany, 2007
Denimal, D., Pillet, M., The Adjustment and Monitoring of Freeform Surfaces using Inertial Tolerancing, ASIGURAREA CALITATII – QUALITY ASSURANCE XVII, 8–16 (2011) Google Scholar
Hotelling, H., The generalization of Student’s ratio, Ann. Math. Stat. 2, 360–378 (1931) CrossRefGoogle Scholar
Bersimis, S., Psarakis, S., Panaretos, J., Multivariate Statistical Process Control Charts: An Overview, Qual. Reliab. Eng. Int. 23, 517–543 (2007) CrossRefGoogle Scholar
R.L. Mason, J.C. Young, Multivariate Statistical Process Control with Industrial Application, ASA-SIAM Series on Statistics and Applied Probability (Copyright 2002 by the American Statistical Association and the Society for Industrial and Applied Mathematics, 2002)
Ghute, V.B., Shirke, D.T., A multivariate synthetic control chart for monitoring process mean vector, Commun. Stat. Theory Meth. 37, 2136–2148 (2008) CrossRefGoogle Scholar
Champ, C.W., Aparisi, F., Double sampling Hotelling’s T 2 charts, Qual. Reliab. Eng. Int. 24, 153–166 (2008) CrossRefGoogle Scholar
Aparisi, F., Deuna, M.A., The design and performance of the multivariate synthetic T 2 control chart, Commun. Stat. Theory Meth. 38, 173–192 (2009) CrossRefGoogle Scholar
Boudaoud, N., Cherfi, Z., A comparative study of cusum and EWMA charts: detection of incipient drifts in a multivariate framework, Qual. Eng. 17, 703–709 (2004) CrossRefGoogle Scholar
Bourdet, P., Clement, A., A study of optimal – criteria identification based on the small – displacement screw model, CIRP Ann. 37, 503–506 (1988) CrossRefGoogle Scholar
D.C. Montgomery, Introduction to statistical quality control, 4th edn. (Wiley, 2001)
M. Pillet, Applying Statistical Process Control (Appliquer la Maîtrise Statistique des processus MSP/SPC) (Eyrolles, Éditions d’Organisation, 2008)
T.P. Ryan, Statistical Methods for Quality Improvement (Wiley, New York, 2000)