Petri net-Digraph models for automating HAZOP analysis of batch process plants

Abstract

Hazard and Operability (HAZOP) analysis is the study of systematically identifying every conceivable deviation, all the possible abnormal causes for such deviation, and the adverse hazardous consequences of that deviation in a chemical plant. HAZOP analysis is often carried out by a group of experts poring over the process flowsheets for weeks or months. Thus, it is a labor-and time-intensive process that would gain by automation. Previous work has addressed the issue of automating HAZOP analysis for continuous chemical plants. However, the HAZOP methodology of continuous processes cannot be applied to batch and semi-continuous plants as such because they have two additional sources of complexity. One is the role of operating procedures and operator actions in plant operation, and the other is the discrete-event character of batch processes. To represent these characteristics of batch operation, high-level Petri nets with timed transitions and colored tokens are used. The causal relationships between process variables are represented using subtask digraphs. This Petri net-Digraph model based framework has been implemented in G2 for a pharmaceutical batch process case study. The salient aspects of this framework are discussed with the aid of this case-study.