Mary Kay O'Connor Process Safety Center

Texas A&M Engineering Experiment Station

List of Center Publications for Abnormal Situation Management

Optimal Alarm Identification and Management:

  1. Safety-centered process control design based on dynamic safe set: Venkidasalapathy, Joshiba Ariamuthu, and Costas Kravaris. “Safety-centered process control design based on dynamic safe set.” Journal of Loss Prevention in the Process Industries (2020): 104126. https://www.sciencedirect.com/science/article/abs/pii/S0950423019303614
  2. A quantitative approach for optimal alarm identification:
    Venkidasalapathy, Joshiba Ariamuthu, M. Sam Mannan, and Costas Kravaris. “A quantitative approach for optimal alarm identification.” Journal of loss prevention in the process industries 55 (2018): 213-222. https://www.sciencedirect.com/science/article/abs/pii/S0950423017306204
  3. A data-driven alarm and event management framework
    Goel, Pankaj, et al. “A data-driven alarm and event management framework.” Journal of Loss Prevention in the Process Industries 62 (2019): 103959.
    https://www.sciencedirect.com/science/article/abs/pii/S0950423019303638
  4. Mannan, M.S. and H.H. West, “Process Alarm Management,” Instrument Engineers’ Handbook, Process Control and Optimization, 4th edition, Editor-in-Chief: B.G. Liptak, pp. 59-63, CRC Press, Boca Raton, Florida, 2006.

Fault Diagnosis and Detection:

  1. Zhou, Y., J. Hahn, and M.S. Mannan, “Process Monitoring Based on Classification Tree and Discriminant Analysis,” Reliability Engineering and System Safety, vol. 91, no. 5, pp. 495-626, May 2006. https://www.sciencedirect.com/science/article/abs/pii/S0951832005001079
  2. Rajaraman, S., J. Hahn, and M.S. Mannan, “Sensor Fault Diagnosis for Nonlinear Processes With Parametric Uncertainties,” Journal of Hazardous Materials, vol. 130, no. 1-2, March 2006, pp. 1-8.
    https://pubmed.ncbi.nlm.nih.gov/16298476/
  3. Rajaraman, S., J. Hahn, and M.S. Mannan, “A Methodology for Fault Detection, Isolation, and Identification for Nonlinear Processes with Parametric Uncertainties,” Industrial and Engineering Chemistry Research, vol. 43, no. 21, 2004, pp. 6774-6786.
    https://pubs.acs.org/doi/10.1021/ie0400806
  4. Zhou, Yifeng, Juergen Hahn, and M. Sam Mannan. “Fault detection and classification in chemical processes based on neural networks with feature extraction.” ISA transactions 42.4 (2003): 651-664.
    https://www.sciencedirect.com/science/article/abs/pii/S0019057807600135
  5. Zhou, Y., W.J. Rogers and M.S. Mannan, “A Sensor Fault Detection Scheme Using a Semi-Independent Process Model,” Proceedings of the 4th Annual Mary Kay O’Connor Process Safety Center Symposium – Beyond Regulatory Compliance: Making Safety Second Nature, College Station, Texas, October 30-31, 2001, pp. 693-701.
  6. Rajaraman, S. and M.S. Mannan, “Issues in Fault Diagnosis and Isolation,” Proceedings of the 4th Annual Mary Kay O’Connor Process Safety Center Symposium – Beyond Regulatory Compliance: Making Safety Second Nature, College Station, Texas, October 30-31, 2001, pp. 703-716.
  7. Zhou, Y., N. Kazantzis, H.H. West, W.J. Rogers and M.S. Mannan, “Abnormal Situation Management: A Process Dynamics Approach,” Proceedings of the 3rd Annual Mary Kay O’Connor Process Safety Center Symposium – Beyond Regulatory Compliance: Making Safety Second Nature, College Station, Texas, October 24-25, 2000, pp. 228-230.