A KNOWLEDGE-BASED FRAMEWORK FOR AUTOMATING HAZOP ANALYSIS

被引:64
|
作者
VENKATASUBRAMANIAN, V
VAIDHYANATHAN, R
机构
[1] Laboratory for Intelligent Process Systems, School of Chemical Engineering, Purdue University, W. Lafayette, Indiana
关键词
D O I
10.1002/aic.690400311
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Hazard and operability (HAZOP) analysis is the study of systematically identifying every conceivable abnormal process deviation, its abnormal causes and adverse hazardous consequences in a chemical plant. HAZOP analysis is a difficult, time-consuming, and labor-intensive activity. An automated HAZOP system can reduce the time and effort involved in a HAZOP review, make the review more thorough and detailed, and minimize or eliminate human errors. Towards that goal a knowledge-based system, called HAZOPExpert, has been proposed in this article. In this approach, HAZOP knowledge is divided into process-specific and process-independent components in a model-based manner. The framework allows for these two components to interact during the analysis to address the process-specific aspects of HAZOP analysis while maintaining the generality of the system. Process-general knowledge is represented as HAZOP models that are developed in a process-independent manner and are applicable to a wide variety of process flowsheets. The important features of HAZOPExpert and its performance on an industrial case study are described.
引用
收藏
页码:496 / 505
页数:10
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