Process Safety Management: Enhance Your PSM Program with Data Driven Reliability

Process Hazard Analysis

The recognition and mitigation of the hazards associated with a covered process is the driving purpose behind PSM. As such, the Process Hazards Analysis (PHA) is one of the most important elements of the PSM program.  However, the complexity of the processing systems and the use of different PHA methodologies can make these analyses very labor intensive. Because QRO is designed around using data, having the correct data and analytics at your disposal is key to enhancing your PHA efforts. The data-driven reliability analytics—along with the ability to model and simulate the effects that changes to inspection and maintenance activities have on your facility—will augment your ability to evaluate mitigation plans and improve the PHA process.

Process Safety Information

Having the details of the covered process on hand and available to anyone is a primary requirement of the PSM standard. It is also one of the areas where most facilities struggle. The information must contain written and accurate details about the chemicals and process technologies. Some of the documents that are included are the Master Asset/Equipment List, P&IDs, PFD, equipment documentation, supporting engineering calculation data, and standards the engineering is based upon. The cornerstone of QRO is data. This includes not only condition data of the assets but their attributes, functional requirements, and histories. Because of this, the data-driven reliability model starts with collecting and incorporating this information into the reliability models to provide the basis for the analytics.

Mechanical Integrity

As the primary element that specifically addresses the maintenance and integrity aspects of the assets, the Mechanical Integrity element is where QRO really shines. As mentioned, QRO is an approach to reliability modeling which connects every relevant reliability data point at a complex facility to one integrated model, allowing users to do things such as:

• Understand near real-time condition of all assets.
• Understand the impact of every inspection or maintenance activity performed.
• Understand the impact of every piece of data that is currently being gathered or could possibly be gathered in the future.
• Near real-time scenario modeling, including the implications of moving a turnaround, feedstock changes, or various capital projects.
• Drive effective decisions in the event of integrity or reliability based operating excursions.