Can PHA be Big Data?
How to Make PHA Data Work Smarter - a Provenance Consulting Webinar
Are you interested in learning how to create consistency in process hazard analysis (PHA) facilitation, reporting and overall data generation? Could you use strategies for developing a consistent PHA structure through standardized data taxonomy and categorization? View this webinar by Managing Partner Patrick Nonhof to learn more.
This webinar provides a practical approach to better utilize the vast amount of data developed in a typical process hazard analysis (PHA) in order to reduce inconsistencies and provide better decision support for risk mitigation.
Strategies for developing a consistent PHA structure through standardized data taxonomy and categorization are presented, as well as the analytical benefits to be realized once the data is consistent.
The beginning of this presentation focuses on how the PHA process fits into the context of the “Big Data” trend. Given the thousands of man-hours spent reviewing each unit, reporting deficiencies, and correcting those deficiencies since 1990, it is time to reconsider whether facilities are utilizing this data to its full potential.
Where does PHA fit into the realm of “Big Data?” This connection is examined briefly.
In order to make PHA data work smarter, it must be structured purposefully. Strategies for creating meaningful PHA metrics and analysis are shared. These improved metrics will allow access to decision support that no one has used before.
Nonhof then expounds on the potential to facilitate improved decision-making based on these metrics across units within a single facility as well as across a company.
Finally, the future possibilities for PHA data is explored. Nonhof theorizes on how facilities’ actions toward creating consistent, accessible, usable data today will lead to a new way management views and uses PHA data in the future.
Take a look at the agenda:
- Define Big Data in the context of Process Hazard Analysis.
- See potential uses for PHA data through practical examples and case studies.
- Create structures and conditions for meaningful PHA metrics and analysis.
- Facilitate improved decision-making based on PHA reporting.
- Eliminate inconsistencies in PHA’s site-wide and across a company
- Explore PHA Big Data long term potential.
Patrick Nonhof holds a B.S. in Chemical Engineering from The University of Texas at Austin. He has nearly 20 years of experience in the petrochemical industry. He began his career with BASF and held positions in project engineering and operations.
After BASF, he worked for Berwanger, Inc., an engineering consulting company based in Houston. At Berwanger, Mr. Nonhof served in a variety of line management positions. During his tenure with Berwanger, he worked for multiple multinational oil and gas companies providing Process Safety Management (PSM) services.
In 2006, he cofounded Provenance Consulting. Provenance’s focus is implementation and maintenance of PSM systems, with a focus on data management.
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Introducing PHA Central™
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PHA Central™ is your solution for realizing the value of all of your PHA data – past and present. It’s the only advanced PHA data analytics solution that combines multiple PHA data sets into a categorized database with built-in analytics tools.
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PHA Central™ Brochure
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