REQUIREMENTS FOR IMPROVED PROCESS HAZARD ANALYSIS (PHA) METHODS: ADDRESSING WEAKNESSES IN THE HAZARD AND OPERABILITY (HAZOP) STUDY AND OTHER TRADITIONAL PHA METHODS

摘要

In order to develop better process hazard analysis (PHA) approaches, weaknesses in current approaches first must be identified and understood. Criteria can then be developed that new and improved approaches must meet. Current PHA methods share common weaknesses such as their inability specifically to address multiple failures, their identification of worst-consequence rather than worst-risk scenarios, and their focus on individual parts of a process. These weaknesses are identified and described in this paper to assist in the development of improved approaches. Knowledge of the weaknesses also allows PHA teams to compensate for them when performing studies. Conventional wisdom holds that the Hazard and Operability (HAZOP) study is the most thorough and complete PHA method. Arguably, it is the most commonly-used PHA method in the world today. However, the method is not without its own weaknesses, some of which are not generally recognized. Therefore, a critique of the method is provided to assist in developing improved methods. Among the weaknesses discussed for the HAZOP study method are the extent to which design intent is defined and considered, completeness of parameter selection, efficiency in identifying hazard scenarios, the counter-intuitive inductive / deductive starting point, and the difficulty in focusing on specific hazard types. Key criteria to guide the development of improved methods are proposed and discussed in the context of newer PHA methods, such as Major Hazards Analysis, that have been developed to address the limitations of traditional methods such as the HAZOP study. These key criteria include a structure that facilitates meaningful brainstorming of scenarios, ease of understanding and application of the method by participants, ability to identify scenarios efficiently, completeness of scenario identification, exclusion of extraneous scenarios, ease of updating and revalidating studies, and ease of meeting regulatory requirements. Proposals are made for moving forward with the development of improved methods including the semi-automation of studies and improvements in the training of team members.