Chemical engineers, researchers, the chemical process industries, and regulators have focused on improving the safety of chemical plants since the accidents at Flixborough, Seveso, and Bhopal.  In addition, due to terrorism concerns since 9/11, the EPA, the American Chemical Council, Sandia National Laboratories, the U.S. Coast Guard, and the Department of Homeland Security, have added security standards to existing safety regulations [OSHA Process Safety Management (PSM), EPA Risk Management Plan (RMP)] that apply to the chemical and petrochemical industries.  The potential for the loss of thousands of human lives and huge economic losses which may jeopardize companies’ existence, in addition to social and legal complications, have increased the desire to have dynamic risk assessment and reliability and leading indicators as vital ingredients in the operations and control of chemical plants.

My research aims to develop new techniques for plant-specific, dynamic risk assessment to estimate the probabilities of various critical incident scenarios, associated with a chemical process, using the latest developments in statistical analysis, including copulas and Bayesian analysis.  It focuses on development of new mathematical frameworks to integrate the two important dimensions of process, safety and product quality, and improve them in a synergistic way to reduce the associated risk levels.  The framework utilizes product quality measurements, together with safety measurements, to project better the probabilities of accidents (low-probability, high-severity events), as well as costly product-quality lapses.  Vast amounts of data track the process dynamics, particularly quality defects, which are high-probability, low-severity events, to yield much information on the actions of the various safety and quality systems – helping to identify near-misses information associated with the process.  A modeling framework involving event-trees and set theory, which utilizes extensive distributed control system (DCS) and emergency shutdown (ESD) databases has been developed.  The results of preliminary calculations show their great potential – and the advantages of using quality with safety data.  In addition, my current work is on development of new methodologies involving near-miss utilization and management to identify escalations in the probability of the occurrence of trips – permitting operator(s) to be alerted to major problems likely to occur in the near future.