A modular method for hazard and operability studies of process plant
The identification of hazards in chemical plants has become increasingly important. Not only have chemical plants become larger and more complex, but some countries now have regulations requiring that some form of formal hazard identification be carried out. With the increased speed of many other parts of the design process, hazard identification is becoming the log-jam in attempts to speed up the design of new plants still further. One of the most popular techniques for hazard identification is a hazard and operability study (HAZOP), in which a group of people attempt to identify creatively the possible hazards by applying a methodical process whereby the effect of deviations to every process variable is considered in every part of the plant. The aim of this thesis is to explore methods of improving hazard identification through the development of the HAZOP technique. This thesis examines possible improvements that can be made through a better understanding of activities and how they are carried out in HAZOP, discusses the possibilities of automated hazard identification based on HAZOP, and in particular presents a novel, modular HAZOP methodology. Modular HAZOP is based around identifying the modules that make up a chemical plant and then using previously generated HAZOP results associated with each of the modules. The hazards associated with these modules will therefore be known and rules are required to deal with the interconnections between modules. Application of these rules determines any additional hazards that might arise from the interconnection of modules. A number of important principles have been identified including, the level of decomposition required, the use of interchangeable sub-modules within modules, the fact that the majority of cause-consequence scenarios exist in adjacent modules, and the categorisation of locally and remotely propagated effects. These provide for a procedure which is adaptable to different plant configurations, but can also be quickly and easily applied. The latter principles enable the simpler fault paths, which make up most of the cause-consequence scenarios, to be identified quickly, leaving a much reduced number of fault paths which require a more thorough analysis.