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Functional process capability analysis in mechanical systems

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Abstract

Functional quality in the mechanical products is governed mainly by the degree of satisfaction of the design requirements, which itself depends on the variations in the effective variables. The functional parameters cannot be easily measured in mass production, and thus, are not usually considered as a direct inspection objective. Process capability indices are useful tools for evaluating the ability of a process to produce the dependent variables of a product that meet certain specifications. In this paper, the conventional process capability concept is extended to develop a computational tool for analysis of the functional quality of a mechanical product. Through defining new proper indices called functional process capability indices (FPCp, FPCpk, FPCpm, and FPCpmk), a statistics-based process capability analysis method is used to estimate the ability of a manufacturing process for meeting the functional requirements of a mechanical system. Using this approach for statistical design of a mechanical product, the effects of variations in manufacturer’s dimensions on the functional requirements of a product can be evaluated. A parameter is introduced which quantifies the contribution of variables that reduce the functional process capability. The applications of the proposed method are demonstrated through implementing it on two case studies and the results are discussed.

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References

  1. Kane VE (1986) Process capability indices. J Qual Technol 18(1):41–52

    Google Scholar 

  2. Taguchi G (1985) A tutorial on quality control and assurance-the Taguchi methods. ASA Annual Meeting, Las Vegas, Nevada

    Google Scholar 

  3. Chan LK, Cheng SW, Spiring FA (1988) A new measure of process capability: C pm. J Qual Technol 20(3):162–175

    Google Scholar 

  4. Pearn WL, Kotz S, Johnson NL (1992) Distributional and inferential properties of process capability indices. J Qual Technol 24(4):216–231

    Google Scholar 

  5. Adragna PA, Pillet M, Formosa F, Samper S (2006) Inertial tolerancing and capability indices in an assembly production. Revue Internationaled’IngenierieNumerique 2(1–2):71–88

    Google Scholar 

  6. Kaya I, Kahraman C (2010) Development of fuzzy process accuracy index for decision making problems. Inf Sci 180:861–872

    Article  MathSciNet  Google Scholar 

  7. Mannar K, Geglarek D (2010) Functional capability space and optimum process adjustments for manufacturing processes with in-specs failure. IIE Trans 42:95–106

    Article  Google Scholar 

  8. Delaney KD, Phelan P (2009) Design improvement using process capability data. J Mater Process Technol 209:619–624

    Article  Google Scholar 

  9. Khodaygan S., Movahhedy M.R (2011) “Statistical-based Process Capability Analysis for Fit Quality Prediction of Mechanical Assemblies with Asymmetric Tolerance”, SAE Technical Paper 2011-01-0466

  10. Khodaygan S, Movahhedy MR (2012) Fuzzy-based analysis of process capability for assembly quality assessment in mechanical assemblies. Int J Prod Res 50(12):3395–34152012

    Article  Google Scholar 

  11. Zhang Y, Yang M (2009) A coordinate SPC model for assuring designated fit quality via quality-oriented statistical tolerancing. Comput Ind Eng 57:73–79

    Article  Google Scholar 

  12. Pearn WL, Kotz S (2006) “Encyclopaedia and handbook of process capability indices: Comprehensive exposition of Quality Control Measures”, series in quality, reliability & engineering statistic, vol 12. World Scientific, USA

    Google Scholar 

  13. Wu C, Pearn WL, Kotz S (2009) An overview of theory and practice on process capability indices for quality assurance. Int J Prod Econ 117:338–359

    Article  Google Scholar 

  14. Moore RE, Kearfott RB, Cloud MJ (2009) Introduction to interval analysis. Siam, Philadelphia

    Book  MATH  Google Scholar 

  15. Greenwood WH, Chase KW (1990) Root sum squares tolerance analysis with nonlinear problems. J Eng Ind Trans ASME 112(4):382–384

    Article  Google Scholar 

  16. Movahhedy MR, Khodaygan S (2007) “Tolerance analysis of mechanical assemblies with asymmetric tolerances”, SAE 2007 Transactions. J Mater Manuf 116:44–52

    Google Scholar 

  17. Khodaygan S, Movahhedy MR (2010) Tolerance analysis of assemblies with asymmetric tolerances by unified uncertainty—accumulation model based on fuzzy logic. Int J Adv Manuf Technol 53(5–8):777–788

    Google Scholar 

  18. Bryan A., Camelio J., Hu S.J (2007) “Error analysis of a nanomechanical drill”, Selected Conference Papers from the 9th CIRP International Seminar on Computer-Aided Tolerancing in “Models for Computer Aided Tolerancing in Design and Manufacturing”, Edited by Davidson J. K., Springer

  19. Uicker J, Pennock G, Shigley J (2010) Theory of machines and mechanisms, 4th edn. Oxford University Press, USA

    Google Scholar 

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Correspondence to M. R. Movahhedy.

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Khodaygan, S., Movahhedy, M.R. Functional process capability analysis in mechanical systems. Int J Adv Manuf Technol 73, 899–912 (2014). https://doi.org/10.1007/s00170-014-5800-0

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