Generic Markov models for availability estimation and failure characterization in petroleum refineries

Chemical process plant decision making is ongoing during operation based upon availability both of components and of the entire system. These decisions include repair policies, maintenance strategies, and inspection routines. The industry state-of-the-art in availability analysis is a Petri Net simulation. It produces confidence intervals on availabilities. In this paper, we present an alternative – generic Markov models. Our models produce exact results in the case of exponential failure and repair times, are at least as easy to use during model building, and reduce computational effort by orders of magnitude. A case study of a reactor regenerator system in a Fluid Catalytic Cracking Unit in a petroleum refinery is presented.