2020 Mary Kay O'Connor Process Safety Virtual Symposium

Updated: Oct 12

aeSolutions' Technical Presentations:

Day 1: Tuesday Oct 20th

Track I: Risk/Consequence Analysis & Design Aspects

Session Room A

11:00 AM – Does Your Facility Have the Flu? How to Use Bayes Rule to Treat the Problem instead of the Symptom, Keith Brumbaugh

2:45 PM – The use of Bayesian Networks in Functional Safety, Paul Gruhn


Day 2: October 21st

Track I: Risk/Consequence Analysis & Design Aspects

Session Room A

8:30 AM – Applying PHA Methodologies such as HAZOP and Bowtie to Assessing Industrial Cybersecurity Risk, John Cusimano, Tim Gale, and Jacob Morella

1:15 PM – How Can I Effectively Place My Gas Detectors, Jesse Brumbaugh


All times listed are Central Time - More info and full abstracts below:

Day 1: Tuesday Oct 20th

Track I: Risk/Consequence Analysis & Design Aspects

Session Room A

11:00 AM – Does Your Facility Have the Flu? How to Use Bayes Rule to Treat the Problem instead of the Symptom, Keith Brumbaugh

Is our industry addressing the problems facing it today? We idealize infinitesimally small event rates for highly catastrophic hazards, yet are we any safer? Have we solved the world’s problems? Layers of protection analysis (LOPA) drives hazardous event rates to 10-4 per year or less, yet industry is still experiencing several disastrous events per year.


If one estimates 1,000 operating units worldwide and industry experiences approximately 10 major incidents per year, the true industry accident rate is a staggering 10 / 1,000 per year (i.e. 10-2). All the while our LOPA calculations are assuring us we have achieved an event rate of 10-6. Something is not adding up.


Rather than fussing over an unobtainable numbers game; wouldn’t it be better to address protection layers which are operating below requirements? We are (hopefully) performing audits and assessments on our protection layers and generating findings. Why are we not focusing our efforts on the results of these findings? Instead we demand more bandages (protect layers) for amputated limbs (LOPA scenarios) instead of upgrading those bandages to tourniquets.


Perhaps the dilemma is we cannot effectively prioritize our corrective actions based on findings. Likely we have too much information and the real problems are lost in the chaos. What if there was a way to decipher the information overload and visualize the impact of our short comings? Enter Bayes rule to provide a means to visualize findings through a protection layer health meter approach; to prioritize action items and staunch the bleeding.

Keywords: Bayes, Bayes rule, Bayes theory, LOPA, IPL, SIS, SIF, SIL Calculations, systematic failure, human factors, human reliability, operations, maintenance, IEC 61511, ANSI/ISA 61511, hardware reliability, proven in use, confidence interval, credible range, safety lifecycle, functional safety assessment, FSA stage 4, health meter.


2:45 PM – The use of Bayesian Networks in Functional Safety, Paul Gruhn

Functional safety engineers follow the ISA/IEC 61511 standard and perform calculations based on random hardware failures. These result in very low failure probabilities, which are then combined with similarly low failure probabilities for other safety layers, to show that the overall probability of an accident is extremely low (e.g., 1E-5/yr). Unfortunately, such numbers are based on frequentist assumptions and cannot be proven. Looking at actual accidents caused by control and safety system failures shows that accidents are not caused by random hardware failures. Accidents are typically the result of steady and slow normalization of deviation (a.k.a. drift). It’s up to management to control these factors. However, Bayes’ theorem can be used to update our prior belief (the initial calculated failure probability) based on observing other evidence (e.g., the effectiveness of the facility’s process safety management process). The results can be dramatic.


Keywords: PSM, Process Safety Management, Bayes’ Theorem, SIS, Safety Instrumented System, SIL, Safety Integrity Level, Swiss Cheese Model, Normalization of Deviation, Drift


Day 2: October 21st

Track I: Risk/Consequence Analysis & Design Aspects

Session Room A

8:30 AM – Applying PHA Methodologies such as HAZOP and Bowtie to Assessing Industrial Cybersecurity Risk, John Cusimano, Tim Gale, and Jacob Morella

Process hazard assessments (PHA) are a well-established practice in process safety management. These assessments focus on failures (aka deviations) that are typically caused by equipment failures or human error. By design, PHAs do not consider cyber threats to industrial control systems (ICS). However, cyber threats represent additional failure modes that may lead to the same health, safety and environmental consequences identified in the PHA. Functional safety (i.e. ISA 84 / IEC 61511) and industrial cybersecurity standards (i.e. ISA/IEC 62443) recognize this issue and provide guidance on how to integrate these two disciplines to ensure that cyber incidents cannot impact process safety.


A proven methodology, called Cyber PHA, based on ISA/IEC 62443-3-2 has been developed and applied to conduct ICS cyber risk assessments throughout the process industries. This paper will describe the methodology with examples of actual applications to identify, rank and mitigate cyber risk in ICS systems. Furthermore, we will demonstrate how Bowtie Analysis can be used to visualize the results and apply degradation factors and controls related to cyber barrier assurance.


Keywords: industrial cybersecurity, ics cybersecurity, cyber pha, cyber bowtie, isa/iec 62443, cyber-risk, cyber-security


1:15 PM – How Can I Effectively Place My Gas Detectors, Jesse Brumbaugh

Several Recognized and Generally Accepted Good Engineering Practices (RAGAGEPs) exist to help someone make their selection and placement of gas detectors (e.g. ISA-TR84.00.07, NFPA 72, UL-2075). However, there are no real consistent approaches widely used by companies. Historically, gas detection has been selected based on rules of thumb and largely dependent on experience. Over the last several years there has been a growing interest in determining not only the confidence but also the effectiveness of those gas detection systems. In fact, incorrect detector placement far outweighs the probability of failure on demand (of the individual system components) in limiting the effectiveness of the gas detection system.


An effective gas detection system has three elements:

1. A comprehensive Gas Detection Philosophy

2. Appropriate Detector Technology Selection

3. Correct Detector Placement


The Gas Detection Philosophy clearly specifies the chemicals of concern and the intended purposes, i.e. detection of toxic or combustible levels, voting requirements, alarm rationalization, and control actions.


Appropriate Detector Technology Selection includes consideration of the target gas and the required detection concentration levels.


The primary approaches for Detector Placement are geographic and scenario-based coverage. Geographic coverage places detectors on a uniform grid, and sometimes areas risk ranked to reduce the number of detectors required. Scenario-based coverage has a range of leak models and places gas detectors based on the dispersion modeling results.

All three elements for effective gas detection (philosophy, technology, and placement) are interdependent but understanding their relationships is of paramount importance to design an effective gas detection system.


The intention of this paper is to present the main considerations that design engineers and process safety professionals should address for each gas detection system element in order to obtain the best return on your investment when placing your gas detectors.

Keywords: Instrumentation, Reduction of Risk, Risk Assessment, Protection, Detection System, Alarms and Operator Interventions, Detector, Gas Detection/Dispersion Prediction

Hope to see you online!


For the full agenda visit : mkosymposium.tamu.edu/agenda


Register Here: tx.ag/SymposiumRegistrationtx.ag



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