Like most operating companies, Honeywell operates a robust risk-based PHA process to help us manage the risks in our portfolio. The process and resulting safety-critical safeguards are key barriers against process safety incidents. Our PHA and LOPA teams make assumption about the likelihood - Initiating Event Frequency or IEF - of faults. E.g. control loops are expected to develop a fault about once per 10 years. We use vendor-data about reliability of components like transmitters when itâs available. And we use typical data sources like those available from CCPS and others about the expected reliability and failure rates of other components of our safeguards. All this information is used to calculate the expected and mitigated risk â given all the assumptions. But all the above is dependent on how valid all the assumptions are.
Also, like most operating companies, we use Process Historians to collect data about the performance of our processes â including our control and safeguard systems. We have begun using this Historian data to analyze the actual âreal-worldâ IEFs and performance of our Safety Instrumented Functions (SIFs) and other Independent Protection Layers (IPLs) in our processes. In this paper we will describe the results of one part of this work and how we are using the resulting data in four important ways: to indicate the real-time health of active risk management Safeguards; to integrate the learnings as Key Performance Indicators (KPIs); as inputs to our PHA/LOPA revalidations; and to help us comply with IEC61511/ISA-S84 for the Operation and Maintenance phase of the Safety Life Cycle.
