Reading List for Student Participants of FACAM 2018 Workshop

For PhD students joining the FACAM 2018 workshop, you may read the following references for better communication with each others:

1. Huang, Q., Zhang, J., Sabbaghi, A., and Dasgupta, T., 2015, “Optimal Offline Compensation of Shape Shrinkage for 3D Printing Processes, ”IIE Transactions on Quality and Reliability, Vol. 47(5), pp. 431–441. 
2. Luan, H., and Huang, Q., 2017, “Prescriptive Modeling and Compensation of In-Plane Shape Deformation for 3-D Printed Freeform Products, ”IEEE Transactions on Automation Science and Engineering, Vol. 14(1), pp. 73–82.
3. Huang, Q., 2016, “An Analytical Foundation for Optimal Compensation of Three-Dimensional Shape Deformation in Additive Manufacturing, ”ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 138(6), 061010.
4. Sabbaghi, A., Huang, Q., and Dasgupta, T., 2017, “Bayesian Model Building From Small Sam- ples of Disparate Data for 3D Printing ,” Technometrics, in press.
5. Sabbaghi, A. and Huang, Q., 2017, “Model Transfer via Equivalent Effects of Lurking Variables in 3D Printing,” Annals of Applied Statistics.
6. Shireen, T., Shao, C., Wang, H., Li, J., Zhang, X., and Li, M., (2017), Iterative Multi-Task Learning for Time-Series Modeling of Solar Panel PV Outputs, Applied Energy. (Appear Soon).
7. Shao, C., Ren, J., Wang, H., Jin, J., & Hu, S. J. (2017). Improving Machined Surface Shape Prediction by Integrating Multi-Task Learning with Cutting Force Variation Modeling. ASME Journal of Manufacturing Science and Engineering, 139 (1), 011014.
8. Plumlee, M., 2017, "Bayesian calibration of inexact computer models,"  Journal of the American Statistical Association 112 (519), 1274-1285
9. M Plumlee, VR Joseph, H Yang, 2015, "Calibrating functional parameters in the ion channel models of cardiac cells," Journal of the American Statistical Association.
10. Plumlee, M., and Apley, D., 2017,  "Lifted Brownian kriging models," Technometrics 59 (2), 165-177.
11. Colosimo, B., 2017, "Modeling and monitoring methods for spatial and image data, " Quality Engineering,"  30:1, 94-111, DOI: 10.1080/08982112.2017.1366512.
12. M. Grasso, A.G. Demir, B. Previtali, B.M. Colosimo, 2017, "In situ monitoring of selective laser melting of zinc powder via infrared imaging of the process plume," Robotics and Computer–Integrated Manufacturing 49 (2018) 229–239.
13. M. Grasso and B.M. Colosimo, "Process defects and in situ monitoring methods in metal powder bed fusion: a review, " Meas. Sci. Technol. 28 (2017) 044005 (25pp).
14. Schleich, B., Anwer, N., Mathieu, L., Wartzack, S., 2014, Skin Model Shapes: A new paradigm shift for geometric variations modelling in mechanical engineering, Computer-Aided Design, 50:1-15.
15. Schleich, B., Wartzack, S., Anwer, N., Mathieu, L., 2015, Skin Model Shapes: Offering now potentials for modelling product shape variability, ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Volume 1A: 35th Computers and Information in Engineering Conference, ISBN: 978-0-7918-5704-5, doi:10.1115/DETC2015-46701, 2–5 August, 2015, Boston, Massachusetts, USA. 
16. Schleich, B., Anwer, N., Mathieu, L., Wartzack, S., 2016, Status and Prospects of Skin Model Shapes for Geometric Variations Management, Procedia CIRP, 43:154-159, Proceedings of the 14th CIRP Conference on Computer Aided Tolerancing (CAT 2016), 18-20 May 2016, Gothenburg, Sweden.

The access link to copies of these manuscripts might be provided upon request. (Email: qiang.huang@usc.edu)