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Modeling, synthesis, & diagnosis for large manufacturing systems

(1) Stream-of-Variation Modeling:
This involves developing models to analyze and predict variation in manufacturing systems, particularly in multi-station assembly processes.

Representative Papers:

  • Kong, Z.J., Huang, W., and Oztekin, A.*, 2009. Variation Propagation Analysis for Multi-Station Assembly Process with Consideration of GD&T Factors. ASME Transactions Journal of Manufacturing Science and Engineering, Vol. 131, No. 5, p. 051010.

  • Huang W., Lin J., Bezdecny M., Kong Z.J., and Ceglarek D. "Stream-of-Variation Modeling I: A Generic 3D Variation Model for Rigid Body Assembly in Single Station Assembly Processes." ASME Transactions Journal of Manufacturing Science and Engineering, Vol. 129, No. 4, pp. 821-831, 2007. DOI: 10.1115/1.2714580.

  • Huang W., Lin J., Kong Z.J., and Ceglarek D. "Stream-of-Variation Modeling II: A Generic 3D Variation Model for Rigid Body Assembly in Multi Station Assembly Processes." ASME Transactions Journal of Manufacturing Science and Engineering, Vol. 129, No. 4, pp. 832-842, 2007. DOI: 10.1115/1.2714581.

  • Kong, Z.J., and Ceglarek, D., 2006. Stream of Variation Analysis for Multiple Station Assembly with Various Tolerance Modes", Transactions of NAMRI/SME, Vol. 34, pp. 469-476.

(2) Fault Diagnosis:

This research focuses on developing methods to identify and diagnose faults in complex manufacturing systems.

Representative Papers:

  • Kong Z.J., Huang W., and Ceglarek D. "Multiple Fault Diagnosis Method in Multi-Station Assembly Processes using State Space Model and Orthogonal Diagonalization Analysis." ASME Transactions Journal of Manufacturing Science and Engineering, Vol. 130, No. 1, p. 011014, 2008. DOI: 10.1115/1.2784280.

  • Bastani K., Kong Z.J., Huang W., Huo X., and Zhou Y. "Fault Diagnosis Using an Enhanced Relevance Vector Machine (RVM) for Partially Diagnosable Multi-Station Assembly Processes." IEEE Transactions on Automation Science and Engineering, Vol. 10, No. 1, pp. 124-136, 2013. DOI: 10.1109/TASE.2012.2214383.

(3) Bayesian Analysis and Statistical Modeling: The application of Bayesian methods for decision-making and process control in manufacturing systems.

Representative Papers:

  • Chung J., and Kong Z.J., 2024, "A Sparse Bayesian Learning for Diagnosis of Nonstationary and Spatially Correlated Faults with Application to Multistation Assembly Systems." IEEE Transactions on Automation Science and Engineering (conditionally accepted)

  • Chung, J.*, Shen, B.* and Kong, Z.J., 2023. A Novel Sparse Bayesian Learning and Its Application to Fault Diagnosis for Multistation Assembly Systems. IISE Transactions, accepted. DOI: 10.1080/24725854.2023.2199813

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