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Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 41, 2009 - Issue 4
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Articles

Statistical Adjustments to Engineering Models

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Pages 362-375 | Published online: 21 Nov 2017

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Read on this site (23)

Rui Tuo, Shiyuan He, Arash Pourhabib, Yu Ding & Jianhua Z. Huang. (2023) A Reproducing Kernel Hilbert Space Approach to Functional Calibration of Computer Models. Journal of the American Statistical Association 118:542, pages 883-897.
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Arvind Krishna, V. Roshan Joseph, Shan Ba, William A. Brenneman & William R. Myers. (2022) Robust experimental designs for model calibration. Journal of Quality Technology 54:4, pages 441-452.
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Jialei Chen, Zhaonan Liu, Kan Wang, Chen Jiang, Chuck Zhang & Ben Wang. (2022) A calibration-free method for biosensing in cell manufacturing. IISE Transactions 54:1, pages 29-39.
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Fangzheng Xie & Yanxun Xu. (2021) Bayesian Projected Calibration of Computer Models. Journal of the American Statistical Association 116:536, pages 1965-1982.
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Babak Farmanesh, Arash Pourhabib, Balabhaskar Balasundaram & Austin Buchanan. (2021) A Bayesian framework for functional calibration of expensive computational models through non-isometric matching. IISE Transactions 53:3, pages 352-364.
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Yan Wang & Rui Tuo. (2020) Semi-parametric adjustment to computer models. Statistics 54:6, pages 1255-1275.
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Ahmed Aziz Ezzat, Arash Pourhabib & Yu Ding. (2018) Sequential Design for Functional Calibration of Computer Models. Technometrics 60:3, pages 286-296.
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Bianca M. Colosimo, Qiang Huang, Tirthankar Dasgupta & Fugee Tsung. (2018) Opportunities and challenges of quality engineering for additive manufacturing. Journal of Quality Technology 50:3, pages 233-252.
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Heeyoung Kim, Justin T. Vastola, Sungil Kim, Jye-Chyi Lu & Martha A. Grover. (2017) Incorporation of engineering knowledge into the modeling process: a local approach. International Journal of Production Research 55:20, pages 5865-5880.
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Matthew Plumlee. (2017) Bayesian Calibration of Inexact Computer Models. Journal of the American Statistical Association 112:519, pages 1274-1285.
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Heeyoung Kim, Justin T. Vastola, Sungil Kim, Jye-Chyi Lu & Martha A. Grover. (2017) Batch Sequential Minimum Energy Design with Design-Region Adaptation. Journal of Quality Technology 49:1, pages 11-26.
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M. T. Pratola & D. M. Higdon. (2016) Bayesian Additive Regression Tree Calibration of Complex High-Dimensional Computer Models. Technometrics 58:2, pages 166-179.
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V. Roshan Joseph. (2016) Space-filling designs for computer experiments: A review. Quality Engineering 28:1, pages 28-35.
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V. Roshan Joseph & Huan Yan. (2015) Engineering-Driven Statistical Adjustment and Calibration. Technometrics 57:2, pages 257-267.
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Arash Pourhabib, Jianhua Z. Huang, Kan Wang, Chuck Zhang, Ben Wang & Yu Ding. (2015) Modulus prediction of buckypaper based on multi-fidelity analysis involving latent variables. IIE Transactions 47:2, pages 141-152.
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Chia-Jung Chang & V. Roshan Joseph. (2014) Model Calibration Through Minimal Adjustments. Technometrics 56:4, pages 474-482.
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Justin T. Vastola, Jye-Chyi Lu, Michael J. Casciato, Dennis W. Hess & Martha A. Grover. (2013) A Framework for Initial Experimental Design in the Presence of Competing Prior Knowledge. Journal of Quality Technology 45:4, pages 301-329.
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MatthewT. Pratola, StephanR. Sain, Derek Bingham, Michael Wiltberger & E. Joshua Rigler. (2013) Fast Sequential Computer Model Calibration of Large Nonstationary Spatial-Temporal Processes. Technometrics 55:2, pages 232-242.
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Chao-Hsi Tsai, Chia-Jung Chang, Kan Wang, Chuck Zhang, Zhiyong Liang & Ben Wang. (2012) Predictive model for carbon nanotube–reinforced nanocomposite modulus driven by micromechanical modeling and physical experiments. IIE Transactions 44:7, pages 590-602.
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V. Roshan Joseph & Lulu Kang. (2011) Regression-Based Inverse Distance Weighting With Applications to Computer Experiments. Technometrics 53:3, pages 254-265.
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Tirthankar Dasgupta, Benjamin Weintraub & V. Roshan Joseph. (2011) A physical–statistical model for density control of nanowires. IIE Transactions 43:4, pages 233-241.
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Lening Wang, Xi Wang, Qinglei Ji, Lihui Wang & Ran Jin. (2024) Mutual Active Learning for Engineering Regulated Statistical Digital Twin Models. IEEE Transactions on Industrial Informatics 20:4, pages 6167-6176.
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Chih‐Li Sung & Rui Tuo. (2024) A review on computer model calibration. WIREs Computational Statistics 16:1.
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Rubén Moliner-Heredia, Ignacio Peñarrocha-Alós & José Vicente Abellán-Nebot. (2023) A methodology for data-driven adjustment of variation propagation models in multistage manufacturing processes. Journal of Manufacturing Systems 67, pages 281-295.
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V. Roshan Joseph. (2022) Optimal ratio for data splitting. Statistical Analysis and Data Mining: The ASA Data Science Journal 15:4, pages 531-538.
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Zhen Chen & Dongbin Xiu. (2021) On generalized residual network for deep learning of unknown dynamical systems. Journal of Computational Physics 438, pages 110362.
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Deepak Kamal, Huan Tran, Chiho Kim, Yifei Wang, Lihua Chen, Yang Cao, V. Roshan Joseph & Rampi Ramprasad. (2021) Novel high voltage polymer insulators using computational and data-driven techniques. The Journal of Chemical Physics 154:17, pages 174906.
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K. Sham Bhat, Kary Myers, Earl Lawrence, James Colgan & Elizabeth Judge. (2020) Structured discrepancy in Bayesian model calibration for ChemCam on the Mars Curiosity rover. The Annals of Applied Statistics 14:4.
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Ahmed Aziz Ezzat, Jiong Tang & Yu Ding. (2020) A model-based calibration approach for structural fault diagnosis using piezoelectric impedance measurements and a finite element model. Structural Health Monitoring 19:6, pages 1839-1855.
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Yue Chen, Jian Shi & Xiao-jian Yi. (2020) A New Reliable Operating Region Design Method. Mathematical Problems in Engineering 2020, pages 1-12.
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Douglas Ray & Jose Ramirez-Marquez. (2020) A framework for probabilistic model-based engineering and data synthesis. Reliability Engineering & System Safety 193, pages 106679.
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Vinh Nguyen & Shreyes N. Melkote. 2020. Proceedings of 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing. Proceedings of 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing 144 155 .
Patxi Fernandez-Zelaia & Shreyes N. Melkote. (2019) Statistical calibration and uncertainty quantification of complex machining computer models. International Journal of Machine Tools and Manufacture 136, pages 45-61.
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José L. Meseguer-Valdenebro, Antonio Portoles & Eusebio Matínez-Conesa. (2018) Electrical parameters optimisation on welding geometry in the 6063-T alloy using the Taguchi methods. The International Journal of Advanced Manufacturing Technology 98:9-12, pages 2449-2460.
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Guillaume Damblin, Pierre Barbillon, Merlin Keller, Alberto Pasanisi & Éric Parent. (2018) Adaptive Numerical Designs for the Calibration of Computer Codes. SIAM/ASA Journal on Uncertainty Quantification 6:1, pages 151-179.
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Raymond K. W. Wong, Curtis B. Storlie & Thomas C. M. Lee. (2017) A Frequentist Approach to Computer Model Calibration. Journal of the Royal Statistical Society Series B: Statistical Methodology 79:2, pages 635-648.
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Heeyoung Kim, Sungil Kim, Jianxin Deng, Jye-Chyi Lu, Kan Wang, Chuck Zhang, Martha A. Grover & Ben Wang. (2016) An integrated holistic model of a complex process. The International Journal of Advanced Manufacturing Technology 89:1-4, pages 1137-1147.
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Hossein Sheikhi & Abas Saghaie. (2017) Developing an engineering-statistical model for estimating aerodynamic coefficients of helicopter fuselage. Chinese Journal of Aeronautics 30:1, pages 175-185.
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Kan Wang, Arda Vanli, Chuck Zhang & Ben Wang. (2016) Calibration and adjustment of mechanical property prediction model for poly(vinyl alcohol)-enhanced carbon nanotube buckypaper manufacturing. The International Journal of Advanced Manufacturing Technology 88:5-8, pages 1889-1901.
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Zhen Jiang, Paul D. Arendt, Daniel W. Apley & Wei Chen. 2017. Handbook of Uncertainty Quantification. Handbook of Uncertainty Quantification 69 127 .
Yanyan He & Dongbin Xiu. (2016) Numerical strategy for model correction using physical constraints. Journal of Computational Physics 313, pages 617-634.
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Shuai Luo, Hongyue Sun, Qingyun Ping, Ran Jin & Zhen He. (2016) A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects. Energies 9:2, pages 111.
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Rui Tuo & C. F. Jeff Wu. (2016) A Theoretical Framework for Calibration in Computer Models: Parametrization, Estimation and Convergence Properties. SIAM/ASA Journal on Uncertainty Quantification 4:1, pages 767-795.
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Rui Tuo & C. F. Jeff Wu. (2015) Efficient calibration for imperfect computer models. The Annals of Statistics 43:6.
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Zhen Jiang, Paul D. Arendt, Daniel W. Apley & Wei Chen. 2016. Handbook of Uncertainty Quantification. Handbook of Uncertainty Quantification 1 59 .
Max D. Gunzburger, Clayton G. Webster & Guannan Zhang. (2014) Stochastic finite element methods for partial differential equations with random input data. Acta Numerica 23, pages 521-650.
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O. Arda Vanli & Sungmoon Jung. (2014) Statistical updating of finite element model with Lamb wave sensing data for damage detection problems. Mechanical Systems and Signal Processing 42:1-2, pages 137-151.
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Michael J. Casciato, Justin T. Vastola, J. C. Lu, Dennis W. Hess & Martha A. Grover. (2013) Initial Experimental Design Methodology Incorporating Expert Conjecture, Prior Data, and Engineering Models for Deposition of Iridium Nanoparticles in Supercritical Carbon Dioxide. Industrial & Engineering Chemistry Research 52:28, pages 9645-9653.
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Qiang Liu, Xiaoqin Zhou, Jieqiong Lin, Pengzi Xu & Zhiwei Zhu. (2013) A Quasiphysics Intelligent Model for a Long Range Fast Tool Servo. The Scientific World Journal 2013, pages 1-12.
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Paul D. Arendt, Daniel W. Apley & Wei Chen. (2012) Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability. Journal of Mechanical Design 134:10.
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Sripati Sah, Robert X. Gao & Timothy Kurp. (2011) Model-augmented methods for estimation of contact pressure distribution. Journal of Manufacturing Systems 30:4, pages 223-233.
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Xin Wang, Binfeng Li, Kaibo Wang & Su Wu. (2011) An engineering-statistical model for synthesis process of nanomaterials. An engineering-statistical model for synthesis process of nanomaterials.
Wenjie Mai & Xinwei Deng. (2010) The applications of statistical quantification techniques in nanomechanics and nanoelectronics. Nanotechnology 21:40, pages 405704.
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Xinwei Deng, V. Roshan Joseph, Wenjie Mai, Zhong Lin Wang & C. F. Jeff Wu. (2009) Statistical approach to quantifying the elastic deformation of nanomaterials. Proceedings of the National Academy of Sciences 106:29, pages 11845-11850.
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