Model‐predictive safety system for proactive detection of operation hazards |
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| Authors: | Taha Mohseni Ahooyi Masoud Soroush Jeffrey E. Arbogast Warren D. Seider Ulku G. Oktem |
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| Affiliation: | 1. Dept. of Chemical and Biological Engineering, Drexel University, Philadelphia, PA;2. Delaware Research & Technology Center, American Air Liquide, Newark, DE;3. Dept. of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA;4. Risk Management and Decision Processes Center, Wharton School, Philadelphia, PA |
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| Abstract: | ![]()
A method of designing model‐predictive safety systems that can detect operation hazards proactively is presented. Such a proactive safety system has two major components: a set of operability constraints and a robust state estimator. The safety system triggers alarm(s) in real time when the process is unable to satisfy an operability constraint over a receding time‐horizon into the future. In other words, the system uses a process model to project the process operability status and to generate alarm signals indicating the presence of a present or future operation hazard. Unlike typical existing safety systems, it systematically accounts for nonlinearities and interactions among process variables to generate alarm signals; it provides alarm signals tied to unmeasurable, but detectable, state variables; and it generates alarm signals before an actual operation hazard occurs. The application and performance of the method are shown using a polymerization reactor example. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2024–2042, 2016 |
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| Keywords: | model‐predictive safety system operability analysis process safety chemical processes receding horizon proactive alarm |
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