199
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Concurrent optimization of parameter and tolerance design based on the two-stage Bayesian sampling method

, ORCID Icon &
Pages 88-110 | Received 08 Apr 2022, Accepted 25 Dec 2022, Published online: 06 Jan 2023

References

  • Berger, J. (2006). The case for objective Bayesian analysis. Bayesian Analysis, 1(3), 385–402. https://doi.org/10.1214/06-BA115
  • Bisgaard, S., & Ankenman, B. (1995). Analytic parameter design. Quality Engineering, 8(1), 75–91. https://doi.org/10.1080/08982119508904606
  • Boylan, G. L., & Cho, B. R. (2013). Comparative studies on the high-variability embedded robust parameter design from the perspective of estimators. Computers & Industrial Engineering, 64(1), 442–452. https://doi.org/10.1016/j.cie.2012.10.012
  • Cho, B.-R., Kim, Y., Kimbler, D., & Phillips, M. (2000). An integrated joint optimization procedure for robust and tolerance design. International Journal of Production Research, 38(10), 2309–2325. https://doi.org/10.1080/00207540050028115
  • Del Castillo, E., Montgomery, D. C., & McCarville, D. R. (1996). Modified desirability functions for multiple response optimization. Journal of Quality Technology, 28(3), 337–345. https://doi.org/10.1080/00224065.1996.11979684
  • Delignette-Muller, M. L., & Dutang, C. (2015). Fitdistrplus: An R package for fitting distributions. Journal of Statistical Software, 64(4), 1–34. https://doi.org/10.18637/jss.v064.i04
  • Dellaportas, P., & Smith, A. (1993). Bayesian inference for generalized linear and proportional hazards models via Gibbs sampling. Journal of the Royal Statistical Society Series C (Applied Statistics), 42(3), 443–459. https://doi.org/10.2307/2986324
  • Dey, D. K., Ghosh, S. K., & Mallick, B. K. (2000). Generalized linear models: A Bayesian perspective. CRC Press.
  • Engel, J., & Huele, A. F. (1996). A generalized linear modeling approach to robust design. Technometrics, 38(4), 365–373. https://doi.org/10.1080/00401706.1996.10484548
  • Feng, Z., Wang, J., Ma, Y., & Ma, Y. (2021). Integrated parameter and tolerance design based on a multivariate Gaussian process model. Engineering Optimization, 53(8), 1349–1368. https://doi.org/10.1080/0305215X.2020.1793976
  • Gilks, W. R., & Wild, P. (1992). Adaptive rejection sampling for Gibbs sampling. Journal of the Royal Statistical Society Series C (Applied Statistics), 41(2), 337–348. https://doi.org/10.2307/2347565
  • Hamada, M., & Nelder, J. A. (1997). Generalized linear models for quality-improvement experiments. Journal of Quality Technology, 29(3), 292–304. https://doi.org/10.1080/00224065.1997.11979770
  • Han, M., Liu, X., Huang, M., & Tan, M. H. (2020). Integrated parameter and tolerance optimization of a centrifugal compressor based on a complex simulator. Journal of Quality Technology, 52(4), 404–421. https://doi.org/10.1080/00224065.2019.1611358
  • Han, Y., Ma, Y., Ouyang, L., Wang, J., & Tu, Y. (2020). Integrated multiresponse parameter and tolerance design with model parameter uncertainty. Quality and Reliability Engineering International, 36(1), 414–433. https://doi.org/10.1002/qre.2589
  • Han, M., & Tan, M. H. Y. (2017). Optimal robust and tolerance design for computer experiments with mixture proportion inputs. Quality and Reliability Engineering International, 33(8), 2255–2267. https://doi.org/10.1002/qre.2188
  • Han, Y., Tu, Y., Ouyang, L., Wang, J., & Ma, Y. (2022). Economic quality design under model uncertainty in micro-drilling manufacturing process. International Journal of Production Research, 60(3), 1086–1104. https://doi.org/10.1080/00207543.2020.1851792
  • Han, M., & Yong Tan, M. H. (2016). Integrated parameter and tolerance design with computer experiments. IIE Transactions, 48(11), 1004–1015. https://doi.org/10.1080/0740817X.2016.1167289
  • Hazrati-marangaloo, H., & Shahriari, H. (2017). A novel approach to simultaneous robust design of product parameters and tolerances using quality loss and multivariate ANOVA concepts. Quality and Reliability Engineering International, 33(1), 71–85. https://doi.org/10.1002/qre.1991
  • He, Z., Zhu, P. F., & Park, S. H. (2012). A robust desirability function method for multiresponse surface optimization considering model uncertainty. European Journal of Operational Research, 221(1), 241–247. https://doi.org/10.1016/j.ejor.2012.03.009
  • Jeang, A. (1994). Tolerance design: Choosing optimal tolerance specifications in the design of machined parts. Quality and Reliability Engineering International, 10(1), 27–35. https://doi.org/10.1002/qre.4680100107
  • Jeang, A. (1996). Optimal tolerance design for product life cycle. International Journal of Production Research, 34(8), 2187–2209. https://doi.org/10.1080/00207549608905020
  • Jeang, A. (2001). Combined parameter and tolerance design optimization with quality and cost. International Journal of Production Research, 39(5), 923–952. https://doi.org/10.1080/00207540010006717
  • Jeang, A. (2003). Robust computer-aided parameter and tolerance determination for an electronic circuit design. International Journal of Production Research, 41(5), 883–895. https://doi.org/10.1080/0020754021000033850
  • Jeang, A., & Leu, E. (1999). Robust tolerance design by computer experiment. International Journal of Production Research, 37(9), 1949–1961. https://doi.org/10.1080/002075499190851
  • Jiang, F., & Tan, M.H.-Y. (2021). Shifted log loss Gaussian process model for expected quality loss prediction in robust parameter design. Quality Technology & Quantitative Management, 18(5), 527–551. https://doi.org/10.1080/16843703.2021.1910190
  • Jin, Q., Liu, S., & Wang, P. (2015). Optimal tolerance design for products with non-normal distribution based on asymmetric quadratic quality loss. International Journal of Advanced Manufacturing Technology, 78(1–4), 667–675. https://doi.org/10.1007/s00170-014-6681-y
  • Kim, Y. J., & Cho, B. R. (2000). Economic integration of design optimization. Quality Engineering, 12(4), 561–567. https://doi.org/10.1080/08982110008962621
  • Kleijnen, J. P. C. (2017). Regression and Kriging metamodels with their experimental designs in simulation: A review. European Journal of Operational Research, 256(1), 1–16. https://doi.org/10.1016/j.ejor.2016.06.041
  • Ko, Y. H., Kim, K. J., & Jun, C. H. (2005). A new loss function-based method for multiresponse optimization. Journal of Quality Technology, 37(1), 50–59. https://doi.org/10.1080/00224065.2005.11980300
  • Lee, Y., & Nelder, J. (1998). Generalized linear models for the analysis of quality-improvement experiments. The Canadian Journal of Statistics, 26(1), 95–105. https://doi.org/10.2307/3315676
  • Lee, Y., & Nelder, J. A. (2003). Robust design via generalized linear models. Journal of Quality Technology, 35(1), 2–12. https://doi.org/10.1080/00224065.2003.11980187
  • Lesaffre, E., & Lawson, A. B. (2012). Bayesian biostatistics. John Wiley & Sons.
  • Li, W., & Wu, C. (1999). An integrated method of parameter design and tolerance design. Quality Engineering, 11(3), 417–425. https://doi.org/10.1080/08982119908919258
  • Montgomery, D. C. (2017). Design and analysis of experiments. John Wiley & Sons, Inc.
  • Myers, W. R., Brenneman, W. A., & Myers, R. H. (2005). A dual-response approach to robust parameter design for a generalized linear model. Journal of Quality Technology, 37(2), 130–138. https://doi.org/10.1080/00224065.2005.11980311
  • Myers, R. H., & Montgomery, D. C. (1995). Response surface methodology: Process and product in optimization using designed experiments. John Wiley & Sons, Inc.
  • Myers, R. H., Montgomery, D. C., & Vinning, G. G. (2002). Generalized linear models with application in engineering and the sciences. John Wiley&Sons, Inc.
  • Myers, R. H., Montgomery, D. C., Vinning, G. G., Borror, C. M., & Kowalski, S. M. (2004). Response surface methodology: A retrospective and literature survey. Journal of Quality Technology, 36(1), 53–77. https://doi.org/10.1080/00224065.2004.11980252
  • Nelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society, Series A, 135(3), 370–384. https://doi.org/10.2307/2344614
  • Ntzoufras, I. (2009). Bayesian modeling using WinBUGS. John Wiley & Sons Inc.
  • Ortiz, F., Simpson, J. R., Pignatiello, J. J., & Heredia Langner, A. (2004). A genetic algorithm approach to multiple-response optimization. Journal of Quality Technology, 36(4), 432–450. https://doi.org/10.1080/00224065.2004.11980289
  • Ouyang, L., Ma, Y., Wang, J., & Tu, Y. (2017). A new loss function for multiresponse optimization with model parameter uncertainty and implementation errors. European Journal of Operational Research, 258(2), 552–563. https://doi.org/10.1016/j.ejor.2016.09.045
  • Pignatiello, J. J. (1993). Strategies for robust multiresponse quality engineering. IIE Transactions, 25(3), 5–15. https://doi.org/10.1080/07408179308964286
  • Plummer, M. (2003). JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. In: Proceedings of the 3rd international workshop on distributed statistical computing (Vol. 124, pp. 1–10): Vienna, Austria.
  • Scrucca, L. (2013). GA: A package for genetic algorithms in R. Journal of Statistical Software, 53, 1–37. https://doi.org/10.18637/jss.v053.i04
  • Shen, L., Yang, J., & Zhao, Y. (2013). Simultaneous optimization of robust parameter and tolerance design based on generalized linear models. Quality and Reliability Engineering International, 29(8), 1107–1115. https://doi.org/10.1002/qre.1462
  • Shin, S., Truong, N. K. V., Cho, B. R., & Hong, S. H. (2011). Development of a sequential robust–tolerance design model for a destructive quality characteristic. Computers & Industrial Engineering, 60(4), 777–789. https://doi.org/10.1016/j.cie.2011.01.014
  • Taguchi, G., & Wu, Y. (1979). Introduction to off-line quality control. Central Japan Quality Control Assoc.
  • Tsai, J.-T. (2010). Robust optimal-parameter design approach for tolerance design problems. Engineering Optimization, 42(12), 1079–1093. https://doi.org/10.1080/03052151003650084
  • Vining, G. G. (1998). A compromise approach to multiresponse optimization. Journal of Quality Technology, 30(4), 309–313. https://doi.org/10.1080/00224065.1998.11979867
  • Vining, G., Kulahci, M., & Pedersen, S. (2016). Recent advances and future directions for quality engineering. Quality and Reliability Engineering International, 32(3), 863–875. https://doi.org/10.1002/qre.1797
  • Wang, J., & Ma, Y. (2013). Bayesian analysis of two-level fractional factorial experiments with non-normal responses. Communications in Statistics-Simulation and Computation, 42(9), 1970–1988. https://doi.org/10.1080/03610918.2012.687063
  • Wang, J., Mao, T., & Tu, Y. (2021). Simultaneous multiresponse optimisation for parameter and tolerance design using Bayesian modelling method. International Journal of Production Research, 59(8), 2269–2293. https://doi.org/10.1080/00207543.2020.1730011
  • Wang, J., Ma, Y., Ouyang, L., & Tu, Y. (2016). A new Bayesian approach to multiresponse surface optimization integrating loss function with posterior probability. European Journal of Operational Research, 249(1), 231–237. https://doi.org/10.1016/j.ejor.2015.08.033
  • Wang, J., Ma, Y., Ouyang, L., & Tu, Y. (2020). Bayesian modeling and optimization for multiresponse surfaces. Computers & Industrial Engineering, 142, 106357. https://doi.org/10.1016/j.cie.2020.106357
  • Wang, J., Tu, Y., Ma, Y., Ouyang, L., & Tu, Y. (2021). A novel approach for non-normal multiresponse optimisation problems. International Journal of Production Research, 59(23), 7194–7215. https://doi.org/10.1080/00207543.2020.1836420
  • Wu, C.-C., Chen, Z., & Tang, G.-R. (1998). Component tolerance design for minimum quality loss and manufacturing cost. Computers in Industry, 35(3), 223–232. https://doi.org/10.1016/S0166-3615(97)00087-0
  • Yang, S., Wang, J., Ren, X., & Gao, T. (2021). Bayesian online robust parameter design for correlated multiple responses. Quality Technology & Quantitative Management, 18(5), 620–640. https://doi.org/10.1080/16843703.2021.1952545
  • Zong, Z., He, Z., & Kong, X. (2006). Concurrent optimization of parameter design and tolerance design for multiple responses. Modular machine tool & automatic manufacturing technique, 11, 4–7. In Chinese.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.