PETRI NET-DIGRAPH MODELS FOR AUTOMATING HAZOP ANALYSIS OF BATCH PROCESS PLANTS

Hazard and Operability (HAZOP) analysis is the study of systematically identifying every conceivable deviation, all the possible abnormal ca uses for such deviation, and the adverse hazardous consequences of tha t deviation in a chemical plant. HAZOP analysis is often carried out b y a group of experts poring over the process flowsheets for weeks or m onths. Thus, it is a labor- and time-intensive process that would gain by automation. Previous work has addressed the issue of automating HA ZOP analysis for continuous chemical plants. However, the HAZOP method ology of continuous processes cannot be applied to batch and semi-cont inuous plants as such because they have two additional sources of comp lexity. One is the role of operating procedures and operator actions i n plant operation, and the other is the discrete-event character of ba tch processes. To represent these characteristics of batch operation, high-level Petri nets with timed transitions and colored tokens are us ed. 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 stu dy. The salient aspects of this framework are discussed with the aid o f this case-study.