Rong Pan, Ph.D.

Affiliations: 
2002 Pennsylvania State University, State College, PA, United States 
Area:
Industrial Engineering, Operations Research, Statistics
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"Rong Pan"

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Enrique del Castillo grad student 2002 Penn State
 (Statistical process adjustment methods for quality control in short -run manufacturing.)
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Publications

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Fang G, Pan R, Hong Y. (2020) Copula-based reliability analysis of degrading systems with dependent failures Reliability Engineering & System Safety. 193: 106618
Sun H, Pedrielli G, Zhao G, et al. (2020) Cyber coordinated simulation for distributed multi-stage additive manufacturing systems Journal of Manufacturing Systems. 57: 61-71
Zhao X, Pan R, Castillo Ed, et al. (2019) An adaptive two-stage Bayesian model averaging approach to planning and analyzing accelerated life tests under model uncertainty Journal of Quality Technology. 51: 181-197
Mancenido MV, Pan R, Montgomery DC, et al. (2019) Comparing D-optimal designs with common mixture experimental designs for logistic regression Chemometrics and Intelligent Laboratory Systems. 187: 11-18
Subramaniyan AB, Pan R, Kuitche J, et al. (2018) Quantification of Environmental Effects on PV Module Degradation: A Physics-Based Data-Driven Modeling Method Ieee Journal of Photovoltaics. 8: 1289-1296
Lee D, Pan R. (2018) A nonparametric Bayesian network approach to assessing system reliability at early design stages Reliability Engineering & System Safety. 171: 57-66
Seo K, Pan R. (2018) Planning accelerated life tests with random effects of test chambers Applied Stochastic Models in Business and Industry. 34: 224-243
Sanchez LM, Pan R. (2017) Obtaining Reliability Insights during a ProductâÂÂs Conceptual Design Process through Bayesian Network Modeling Industrial Engineering and Management. 6: 1-15
Pan R, Yontay P. (2017) Reliability Assessment of Hierarchical Systems With Incomplete Mixed Data Ieee Transactions On Reliability. 66: 1036-1047
Chen Z, Pan R, Cui L. (2017) An economic off-line quality control approach for unstable production processes Quality Engineering. 29: 1-20
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