Generating Consistent High Quality HAZOP and LOPA Studies Using Cloud Computing Technology

About the webinar

Process Hazards Analysis (PHA) is a well-understood necessity for understanding the hazards posed by plants and ensuring the appropriate degree of safeguards are available to ensure that risk is tolerable. PHA started in the 1970s and is now ubiquitous. Documentation of PHA started with pencil and paper worksheets, but quickly moved to desktop PC programs. Unfortunately, there has not been much progress since that time.

The current state of PHA documentation is a collection of desktop computer files that are distributed on multiple file servers and laptops of employees, contractors, and vendors. The files are usually inconsistent with each other because each facilitator or each company site utilizes different file structures and different nomenclature, making a comparison of documents, benchmarking, and dashboarding impossible. Also, the fact that so many documents have been generated with no mechanism to export data leaves customers locked into obsolete software that has continually increased maintenance costs along with decreases and flexibility in terms of service. Attempts to improve the situation using large central database systems have also failed due to these systems being slow, inflexible, and lacking the ability to perform remote work where internet access is not available.

This presentation discusses how to improve PHA quality while reducing effort and cost by changing and standardizing the technology that underpins how PHA data is stored and accessed. Instead of proprietary desktop formats or heavy, monolithic SQL databases, the modern language of the internet can be used to store, move, and manipulate data. By defining and standardizing a data “schema” in the internet standard JavaScript Object Notation (“JSON”) format, data can be effortlessly shared among multiple different applications and multiple files can be “rolled up” for dashboarding and comparison of data. All this can be done without sacrificing the ability to work offline and remotely and then synchronize with the overall database. Sophisticated cloud-based tools can then be developed which will allow for the use of templates and libraries to ensure the highest quality standardized analysis for consistent results while providing a global enterprise platform that not only makes data accessible but also secure.