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Research Article

Robust parameter design of mixed multiple responses based on a latent variable Gaussian process model

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Pages 1760-1777 | Received 24 Dec 2021, Accepted 17 Aug 2022, Published online: 25 Oct 2022

References

  • Alshraideh, H., and E. Del Castillo. 2014. “Gaussian Process Modeling and Optimization of Profile Response Experiments.” Quality and Reliability Engineering International 30 (4): 449–462.
  • Del Castillo, E., S.-K. Fan, and J. Semple. 1999. “Optimization of Dual Response Systems: A Comprehensive Procedure for Degenerate and Nondegenerate Problems.” European Journal of Operational Research 112 (1): 174–186.
  • Del Castillo, E., S.-K. Fan, and J. Semple. 2018. “The Computation of Global Optima in Dual Response Systems.” Journal of Quality Technology 29 (3): 347–353.
  • Deng, X., C. D. Lin, K.-W. Liu, and R. K. Rowe. 2017. “Additive Gaussian Process for Computer Models with Qualitative and Quantitative Factors.” Technometrics 59 (3): 283–292.
  • Fan, S.-K. S., C. Fan, and C.-F. Huang. 2013. “A Trust Region-Based Approach to Optimize Triple Response Systems.” Engineering Optimization 46 (5): 606–627.
  • Feng, Z., J. Wang, Y. Ma, and Y. Ma. 2020. “Integrated Parameter and Tolerance Design Based on a Multivariate Gaussian Process Model.” Engineering Optimization 53 (8): 1349–1368. doi:10.1080/0305215X.2020.1793976
  • Gu, M., and J. O. Berger. 2016. “Parallel Partial Gaussian Process Emulation for Computer Models with Massive Output.” The Annals of Applied Statistics 10 (3): 1317–1347.
  • Gu, M., and Y. Xu. 2020. “Fast Nonseparable Gaussian Stochastic Process with Application to Methylation Level Interpolation.” Journal of Computational and Graphical Statistics 29 (2): 250–260.
  • Han, G., T. J. Santner, W. I. Notz, and D. L. Bartel. 2009. “Prediction for Computer Experiments Having Quantitative and Qualitative Input Variables.” Technometrics 51 (3): 278–288.
  • Hsieh, K.-L. 2007. “Applying Fuzzy Set Approach Into Achieving Quality Improvement for Qualitative Quality Response.” WSEAS Transactions on Information Science and Applications 4 (5): 1115–1120.
  • Hsieh, K.-L., and L.-I. Tong. 2001. “Optimization of Multiple Quality Responses Involving Qualitative and Quantitative Characteristics in IC Manufacturing Using Neural Networks.” Computers in Industry 46 (1): 1–12.
  • Huang, H., D. K. J. Lin, M.-Q. Liu, and J.-F. Yang. 2016. “Computer Experiments with Both Qualitative and Quantitative Variables.” Technometrics 58 (4): 495–507.
  • Jeng, Y.-C., and S.-M. Guo. 1995. “Quality Improvement for RC60 Chip Resistor.” Quality and Reliability Engineering International 12 (6): 439–445.
  • Johnson, R. A., and D. W. Wichern. 2007. Applied Multivariate Statistical Analysis. 6th ed. London, UK: Pearson.
  • Joseph, V. R., E. Gul, and S. Ba. 2020. “Designing Computer Experiments with Multiple Types of Factors: The MaxPro Approach.” Journal of Quality Technology 52 (4): 343–354.
  • Kang, X., and X. Deng. 2020. “Design and Analysis of Computer Experiments with Quantitative and Qualitative Inputs: A Selective Review.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (3): e1358. doi:10.1002/widm.1358
  • Kleijnen, J. P. C. 2010. Design and Analysis of Computational Experiments: Overview. In Experimental Methods for the Analysis of Optimization Algorithms, 51–72. Berlin: Springer-Verlag. doi:10.1007/978-3-642-02538-9_3
  • Lee, A. H. I., H.-Y. Kang, C. Y. Lin, and J.-S. Chen. 2016. “A Novel Fuzzy Quality Function Deployment Framework.” Quality Technology & Quantitative Management 14 (1): 44–73.
  • Li, W., L. Gao, A. Garg, and M. Xiao. 2020. “Multidisciplinary Robust Design Optimization Considering Parameter and Metamodeling Uncertainties.” Engineering with Computers 38 (11): 191–208.
  • Li, J., F. Tsung, and C. Zou. 2014. “A Simple Categorical Chart for Detecting Location Shifts with Ordinal Information.” International Journal of Production Research 52 (2): 550–562.
  • Li, W., M. Xiao, and L. Gao. 2019a. “Improved Collaboration Pursuing Method for Multidisciplinary Robust Design Optimization.” Structural and Multidisciplinary Optimization 59 (6): 1949–1968.
  • Li, W., M. Xiao, Y. Yi, and L. Gao. 2019b. “Maximum Variation Analysis Based Analytical Target Cascading for Multidisciplinary Robust Design Optimization Under Interval Uncertainty.” Advanced Engineering Informatics 40 (2019): 81–92.
  • Lin, D. K. J., and W. Tu. 1995. “Dual Response Surface Optimization.” Journal of Quality Technology 27 (1): 34–39.
  • Liu, D.-T., and D.-J. Zhou. 2006. “A Method of Job Scheduling on SMEs' Key Equipments Based on Hybrid Multi-Attribute Decision Making.” Journal of Wuhan University of Technology 28 (S2): 694–699.
  • Myers, R. H., D. C. Montgomery, and C. M. Anderson-Cook. 2016. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. New York: Wiley.
  • Nair, V. N., W. Taam, and K. Q. Ye. 2002. “Analysis of Functional Responses From Robust Design Studies.” Journal of Quality Technology 34 (4): 355–370.
  • Ouyang, L., S. Zhu, K. Ye, C. Park, and M. Wang. 2021. “Robust Bayesian Hierarchical Modeling and Inference Using Scale Mixtures of Normal Distributions.” IISE Transactions 54 (7): 659–671.
  • Ozdemir, A., and B. R. Cho. 2017. “Response Surface-Based Robust Parameter Design Optimization with Both Qualitative and Quantitative Variables.” Engineering Optimization 49 (10): 1796–1812.
  • Qian, P. Z. G., H. Wu, and C. F. J. Wu. 2008. “Gaussian Process Models for Computer Experiments with Qualitative and Quantitative Factors.” Technometrics 50 (3): 383–396.
  • Qin, S. 2003. Principle and Application of Comprehensive Evaluation. Beijing: Electronics Industry Press.
  • Rougier, J. 2008. “Efficient Emulators for Multivariate Deterministic Functions.” Journal of Computational and Graphical Statistics 17 (4): 827–843.
  • Sacks, J., W. J. Welch, T. J. Mitchell, and H. P. Wynn. 1989. “Design and Analysis of Computer Experiments.” Statistical Science 4 (4): 409–423.
  • Spanos, C. J., and R. L. Chen. 1997. “Using Qualitative Observations for Process Tuning and Control [IC Manufacture].” IEEE Transactions on Semiconductor Manufacturing 10 (2): 307–316. doi:10.1109/66.572086
  • Taguchi, G. 1985. Introduction to Off-Line Quality Control. Central Japan Quality Control Association.
  • Taguchi, G. 1986. Introduction to Quality Engineering: Designing Quality into Products and Processes. Technical Report. White Plains, NY: Asian Productivity Organization.
  • Williams, C. K., and C. E. Rasmussen. 2006. Gaussian Processes for Machine Learning. Cambridge, MA: MIT Press.
  • Xiong, X., S. Li, and F. Wu. 2020. “Robust Parameter Design for Nonlinear Signal–Response Systems Using Kriging Models.” Engineering Optimization 52 (8): 1344–1361. doi:10.1080/0305215X.2019.1650924
  • Yang, S., J. Wang, X. Ren, and T. Gao. 2021. “Bayesian Online Robust Parameter Design for Correlated Multiple Responses.” Quality Technology & Quantitative Management 18 (5): 620–640.
  • Zadeh, L. A. 1965. “Fuzzy Set.” Information Control 8: 338–353.
  • Zadeh, L. A. 1973. “Outline of a New Approach to the Analysis of Complex Systems and Decision Processes.” IEEE Transactions on Systems, Man, and Cybernetics SMC-3 (1): 28–44.
  • Zhang, Y., S. Tao, W. Chen, and D. W. Apley. 2020. “A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors.” Technometrics 62 (3): 291–302.
  • Zhou, Q., P. Z. G. Qian, and S. Zhou. 2011. “A Simple Approach to Emulation for Computer Models with Qualitative and Quantitative Factors.” Technometrics 53 (3): 266–273.

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