Purdue University School of Chemical Engineering Prof. Warren D. Seider Department of Chemical & Biomolecular Engineering University of Pennsylvania "Risk Analysis Using Large Alarm Databases" April 3, 2012 9:00-10:15 a.m. FRNY G140 Reception at 10:15 in FRNY Atrium Abstract: In most industrial chemical plants, hundreds of variables monitor the dynamics of their processes. When the variables move out of their normal operating ranges, alarms are triggered to notify the operators. Often, vast amounts of alarm data are recorded in databases associated with their distributed control and emergency shutdown systems that often remain "under-utilized". In this work, these large databases are utilized efficiently to: (a) project probabilities of occurrence of shutdowns and accidents, (b) assess the real-time safety and operability performances of processes and improve their alarm systems, and (c) develop leading indicators to forewarn operators of approaching incidents several hours in advance. Abnormal events, which occur when process and quality variables depart from and return to their normal operating ranges, are recognized as near-misses - as they could have propagated into incidents. Consequently, vast amounts of near-miss data are available for analyzing the performances of the regulating (process control) and protection (emergency shutdown) systems. A novel dynamic risk assessment methodology is introduced that uses the alarm databases to calculate the failure probabilities of regulating and protection systems, and the probabilities of the occurrence of incidents. The methodology consists of three steps: (i) tracking of abnormal events over an extended period of time, (ii) event-tree and set-theoretic formulations, and (iii) Bayesian analysis. New event-trees and set-theoretic formulations are introduced to compact the massive numbers (millions) of abnormal events, over several months of operation, leading to significant improvements in the efficiency of the probabilistic calculations and permitting Bayesian analysis of large databases in real-time. The Bayesian model accounts for the interdependences among the regulating and protection systems using copulas, which occur due to the nonlinear relationships between the variables and behavior-based factors involving human operators. As a case study, the methodology is applied to an industrial, fluidized-catalytic-cracking unit (FCCU) at a major petroleum refinery. A new leading indicators methodology using the alarm data is introduced to help identify an escalation in the probability of the occurrence of incidents - permitting the system to alert the operator(s) of a major problem likely to occur in the near future. Bio: Warren D. Seider is Professor of Chemical and Biomolecular Engineering at the University of Pennsylvania. He received a B.S. degree from the Polytechnic Institute of Brooklyn and M.S. and Ph.D. degrees from the University of Michigan. For many years, he has contributed to the fields of process analysis, simulation, design, and control. In process design, he coauthored FLOWTRAN Simulation - An Introduction (with J.D. Seader and A.C. Pauls) and Product and Process Design Principles: Synthesis, Analysis, and Evaluation (with J. D. Seader, D. R. Lewin, and S. Widagdo). He has coordinated the design project course for over 30 years involving projects provided by many practicing engineers in the Philadelphia area. He is recognized for research contributions in phase and chemical equilibria, azeotropic distillation, heat and power integration, Czochralski crystallization, nonlinear control, and safety and risk analysis. He has authored or coauthored over 110 journal articles and authored or edited seven books. Professor Seider was the co-recipient (with Professor J. D. Seader) of the AIChE Warren K. Lewis Award in 2004, and the recipient of the AIChE Computing in Chemical Engineering Award in 1992. In 2011, he received the AIChE F. J. Van Antwerpen Award, and in 2008, he was recognized by the AIChE Centennial Committee as one of "Thirty Authors of Groundbreaking Chemical Engineering Books." He was elected as a Fellow of AIChE in 2005 and as a Director of AIChE in 1983, and has served as chairman of the CAST Division and the Publication Committee. He helped to organize the CACHE (Computer Aids for Chemical Engineering Education) Corporation in 1969 and served as its chairman. Professor Seider is a member of the Editorial Advisory Board of Computers and Chemical Engineering.