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Exploitation des études de capabilité dans le calculstatistique des tolérances géométriques de localisation

Published online by Cambridge University Press:  06 January 2012

Antoine S. Tahan  and
Sylvain Lévesque
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Abstract

L’article propose une méthodologie pour exploiter les mesures de capabilité des procédésde fabrication dans le calcul des tolérances de localisation d’un ensemble d’élémentsgéométriques selon les standards ISO 1101 et ASME Y14.5 avec une approche statistique. Lenombre d’éléments géométriques étudiés, les erreurs systématique et aléatoire du procédéde fabrication seront retenues et incluses dans l’approche. Un modèle mathématiqueexplicite est développé dans le but d’identifier les fonctions de distribution statistiquepour différents types de tolérances de localisation. À partir de ces distributions, nousprésentons une méthodologie servant à estimer les valeurs des tolérances qui permettent derencontrer un seuil de conformité prétabli, et vice versa. L’article présente égalementune série d’abaques permettant un usage industriel simple et commode. Plusieurs exemplesde calculs sont illustrés et un cas d’étude y est présenté.

Keywords

Tolérance géométriquetolérance statistiquetolérancement probabilistetolérance de localisationtolérance de positionindice de capabilitéGeometric tolerancestatistical tolerancingprobabilistic tolerancinglocalization toleranceposition tolerancecapability study
Type
Research Article
Information
Mechanics & Industry , Volume 12 , Issue 6 , 2011 , pp. 503 - 512
Copyright
© AFM, EDP Sciences 2011

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References

Références

ISO 8015, ISO 1101, ISO 5458, ISO 5459, ISO 1660, ISO 2768, ISO 10578, ISO 10579, Tolérances géométriques, International Standard Organisation
ASME Y14.5-2009, Geometric and Dimensioning Tolerancing, ASME Press, 2009
ISO 21747, Statistical methods, Process performance and capability statistics for measured quality characteristics, International Standard Organisation, 2006, p. 42
Polansky, A.M., A smooth nonparametric approach to multivariate process capability, Technometrics 43 (2001) 199–211 CrossRefGoogle Scholar
Nejad, M.K., Vignat, F., Villeneuve, F., 3D Simulation of Manufacturing Defects for Tolerance Analysis, Int. J. Adv. Manuf. Technol. 45 (2009) 631–648 CrossRefGoogle Scholar
Desrochers, A., Ghie, W., Laperriere, L., Statistical tolerance analysis using the unified Jacobian-Torsor model, Int. J. Prod. Res. 48 (2010) 4609–4630 Google Scholar
Hawkins, D.M., Multivariate quality control based on regression adjusted variables, Technometrics 33 (1991) 61–75 Google Scholar
Polansky, A.M., A general framework for constructing control charts, Qual. Reliab. Eng. Int. 21 (2005) 633–653 CrossRefGoogle Scholar
Chen, H., A multivariate process capability index over a rectangular solid zone, Stat. Sinica 4 (1994) 749–758 Google Scholar
Foster, E.J., Barton, R.R., Gautam, N., Truss, L.T., Tew, J.D., The process-oriented multivariate capability index, Int. J. Prod. Res. 43 (2005) 2135–2148 CrossRefGoogle Scholar
Taam, W., Subbaiah, P., Liddy, J.W., A note on multivariate capability indices, J. Appl. Stat. 20 (1993) 339–351 CrossRefGoogle Scholar
Wang, F.K., Hubele, N.F., Lawrence, F.P., Miskulin, J.D., Shahriari, H., Comparison of three multivariate process capability indices, J. Quality Technol. 32 (2000) 263–275 Google Scholar
Mannar, K., Ceglarek, D., Functional capability space and optimum process adjustments for manufacturing processes with in-specs failure, IIE Transactions 42 (2010) 95–106 CrossRefGoogle Scholar
Jackson, P.F., Simple Process Capability? J. Quality Eng. 40 (2001) 34–38 Google Scholar
Wang, F.K., Hubele, N.F., Quality evaluation of geometric tolerance regions in form and location, J. Quality Eng. 14 (2002) 205–211 CrossRefGoogle Scholar
Knowles, G., March, G., Anthony, J., Evaluation process capability for geometrically toleranced parts: A practical approach, J. Quality Eng. 14 (2002) 365–374 CrossRefGoogle Scholar
H.C. Zhang, Advanced Tolerancing Techniques, Wiley Interscience, John Wiley & Sons, New York, 1997
Dowling, M., Griffin, P., Tsui, K., Zhou, C., Statistical issues in geometric feature inspection using coordinate measuring machines, Technometrics 39 (1997) 3–17 CrossRefGoogle Scholar
Bothe, D.R., Assessing capability for hole location, J. Quality Eng. 18 (2006) 325–331 CrossRefGoogle Scholar
Xi, M., Lehtihet, E.A., Cavalier, T.M., Numerical approximation approach to the producibility of composite position tolerance specifications for pattern of holes, Int. J. Prod. Res. 42 (2004) 243–266 CrossRefGoogle Scholar
Phillips, M.D., Cho, B., Quality improvements for process with circular and spherical specification regions, J. Quality Eng. 11 (1999) 235–243 CrossRefGoogle Scholar
Shan, A., Roth, R.N., Wilson, R.J., A new approach to statistical geometrical tolerance analysis, Int. J. Adv. Manuf. Technol. 15 (1999) 222–230 CrossRefGoogle Scholar
A. Papoulis, Probability, random variables, and stochastic process, 3rd Edition, McGraw Hill, 1991
N.D. Cox, S.S. Shapiro, Statistical Model in Engineering, John Wiley & Sons, New York, 1967
M.J. Harry, Six Sigma Mechanical Design Tolerancing, Publication No. 6s-2-10/88, Motorola Inc., 1988, p. 242
ASME B5.54, Methods for Performance Evaluation of Computer Numerically Controlled Machining Centers, ASME Press, 1992
S. Tichadou, et al., 3-D manufacturing dispersions: two experimental applications, 10th CIRP International Conference on Computer Aided Tolerancing, Erlangen, Germany, 2007