(117be) Practical Guide to Operationalize & Visualize Cumulative Process Safety Risks Perspective
AIChE Spring Meeting and Global Congress on Process Safety
2021
2021 AIChE Virtual Spring Meeting and 17th Global Congress on Process Safety
Global Congress on Process Safety
GCPS Poster Session
Wednesday, April 21, 2021 - 3:00pm to 4:00pm
The paper describes
how Process Safety Management can be seamlessly integrated with Operational
Risk Management. It demonstrates how operational processes like Permit to Work,
MOC, Job Hazard Analysis, Incident Management and Process Safety Management can
be brought together to support day-to-day decision making based on the actual
cumulative risk status of the facility.
Key thinking
is developed to answer questions such as How do we make Process Safety Risk
as visible as HSE and How can we prevent previously identified
hazardous sequences of events from reoccurring?, thus increasing the
entire system safety.
This paper
presents practical approaches in overcoming the challenges in collecting data
from disparate sources and learnings on realising Dynamic Operational Risk Management
(ORM) from various client implementations. In addition, it touches upon topics such
as How to analyze the data and Use of machine learning to predict
future risk.
The paper presents
a risk calculation methodology that calculates barrier status and visualizes cumulative
risk:
·
in a standardized
barrier model, based on IOGP 544 standard, in Swiss-Cheese view
·
geographically by
site and area/location using site graphics
·
per critical
scenario in a BowTie view
It connects and
visualizes process safety risk by automatically collecting data for Tier-1,2 and
3 safety indicators that are covered by various processes spread across the
organization.
Furthermore,
it shows how the cumulative risk status can be used in operational processes,
potential conflict detection and planning of activities to manage and minimize
the actual risk.
Keywords:
Barrier Management, Process Safety Management, BowTie Methodology, Swiss-Cheese
Model, Operational Risk Management, Project Implementation Methodologies, permit-to-work,
MOC, JHA/RA, Machine Learning
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