846
Views
10
CrossRef citations to date
0
Altmetric
Quality & Reliability Engineering

Holistic modeling and analysis of multistage manufacturing processes with sparse effective inputs and mixed profile outputs

&
Pages 582-596 | Received 27 Feb 2020, Accepted 14 Jun 2020, Published online: 13 Aug 2020

References

  • Ahmed, N., Natarajan, T. and Rao, K.R. (1974) Discrete cosine transform. IEEE Transactions on Computers, 100, 90–93.
  • Apley, D.W. and Shi, J. (1998) Diagnosis of multiple fixture faults in panel assembly. Journal of Manufacturing Science and Engineering, 120, 793–801.
  • Boyd, S., Parikh, N., Chu, E., Peleato, B. and Eckstein, J. (2011) Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends® in Machine Learning, 3, 1–122.
  • Buckley, M. (1994) Fast computation of a discretized thin-plate smoothing spline for image data. Biometrika, 81, 247–258.
  • De Witte, H., Passefort, S., Besling, W., Maes, J., Eason, K., Young, E., Rittersma, Z. and Heyns, M. (2003) In-line electrical metrology for high-K gate dielectrics deposited by atomic layer CVD. Journal of the Electrochemical Society, 150, F169–F172.
  • Ding, Y., Ceglarek, D. and Shi, J. (2000) Modeling and diagnosis of multistage manufacturing processes: Part I: State space model, in Proceedings of the 2000 Japan/USA Symposium on Flexible Automation, American Society of Mechanical Engineers, New York, pp. 23–26.
  • Fazel, M., Hindi, H. and Boyd, S.P. (2001) A rank minimization heuristic with application to minimum order system approximation, in Proceedings of the American Control Conference, Citeseer, Arlington, VA, pp. 4734–4739.
  • Gahrooei, M.R., Yan, H., Paynabar, K. and Shi, J. (2020) Multiple tensor-on-tensor regression: an approach for modeling processes with heterogeneous sources of data. Technometrics, 62(1), 1–23.
  • Huang, C.Y., Chiu, C.F., Wu, W.B., Shih, C.L., Huang, C.C.K., Huang, H., Choi, D., Pierson, B. and Robinson, J.C. (2012) Overlay control methodology comparison: field-by-field and high-order methods. In Metrology, inspection, and process control for microlithography XXVI, Vol. 8324, pp. 832427-1–832427-9. International Society for Optics and Photonics. San Jose, California.
  • Jin, R. and Shi, J. (2012) Reconfigured piecewise linear regression tree for multistage manufacturing process control. IIE Transactions, 44, 249–261.
  • Lee, T.Y., Lee, B.H., Chin, S.B., Cho, Y.S., Hong, J.S., Hong, J.S. and Song, C.L. (2006) Study of critical dimension and overlay measurement methodology using SEM image analysis for process control, in Metrology, Inspection, and Process Control for Microlithography XX, International Society for Optics and Photonics, San Jose, pp. 61522E-1–61522E-8.
  • Li, J. and Shi, J. (2007) Knowledge discovery from observational data for process control using causal Bayesian networks. IIE Transactions, 39, 681–690.
  • Li, Y., Sun, H., Deng, X., Zhang, C., Wang, H.-P. and Jin, R. (2020) Manufacturing quality prediction using smooth spatial variable selection estimator with applications in aerosol jet® printed electronics manufacturing. IISE Transactions, 52, 321–333.
  • Nishi, Y. and Doering, R. (2000) Handbook of Semiconductor Manufacturing Technology, CRC Press, Boca Raton, FL.
  • O'Sullivan, F. (1991) Discretized Laplacian smoothing by Fourier methods. Journal of the American Statistical Association, 86, 634–642.
  • Parikh, N. and Boyd, S. (2014) Proximal algorithms. Foundations and Trends® in Optimization, 1, 127–239.
  • Ramsay, J.O. (1988) Monotone regression splines in action. Statistical Science, 3, 425–441.
  • Ramsay, J.O. (2005) Functional data analysis. Springer Series in Statistics, Springer, 2nd ed., New York, p. 426.
  • Shi, J. (2006) Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes, CRC Press, Boca Raton, FL.
  • Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological), 58(1), 267–288.
  • Tibshirani, R., Saunders, M., Rosset, S., Zhu, J. and Knight, K. (2005) Sparsity and smoothness via the fused lasso. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67, 91–108.
  • Wahba, G. (1990) Spline Models for Observational Data, SIAM, Philadelphia, PA.
  • Yan, H., Paynabar, K. and Shi, J. (2014) Image-based process monitoring using low-rank tensor decomposition. IEEE Transactions on Automation Science and Engineering, 12, 216–227.
  • Yan, H., Paynabar, K. and Shi, J. (2017) Anomaly detection in images with smooth background via smooth-sparse decomposition. Technometrics, 59, 102–114.
  • Yuan, M., Ekici, A., Lu, Z. and Monteiro, R. (2007) Dimension reduction and coefficient estimation in multivariate linear regression. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 69, 329–346.
  • Yuan, M. and Lin, Y. (2006) Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society Series B-Statistical Methodology, 68, 49–67.
  • Yue, X., Park, J.G., Liang, Z. and Shi, J. (2020) Tensor mixed effects model with application to nanomanufacturing inspection. Technometrics, 62(1), 116–129.
  • Zhang, C., Yan, H., Lee, S. and Shi, J. (2018a) Dynamic multivariate functional data modeling via sparse subspace learning. arXiv preprint arXiv:1804.03797.
  • Zhang, C., Yan, H., Lee, S. and Shi, J. (2018b) Multiple profiles sensor-based monitoring and anomaly detection. Journal of Quality Technology, 50, 344–362.

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.