This Service Foundation is Built on Two Key Ingredients:
• A Reliability Key Performance Indicator called Ri, using a prediction algorithm to verify and validate if a proposed control valve will be fit for the given application. Ri has been introduced in 2012 and proven accurate since day one. Accurate means Ri predicted it correctly for 95% of the used cases.
• A Tool called CAT, to capture, analyze and validate bulk-engineering data against this prediction algorithm. The tool analyses control valve process data as generated by the EPC contractor. Whenever the process data has been analyzed and “approved”, the tool analyzes the valve vendor data to validate a fit for the application valve selection.
The Driving Force
Traditionally unfit for the application issues most often appear during commissioning and startup. The cost and schedule impact can be substantial! For one it can directly impact the startup cost and schedule because replacing the valve with a fit for application one takes time! Schedule impacts are very costly, especially for major petrochemical startups. For two those replacement activities are costly as well, because one needs to interrupt the normal process to make such fast deliverables possible. For three it can be frustrating, really frustrating. This is the time when the instrument folks come on the plant manager’s radar screen, not the ideal place to be too long.
How we Derived this Approach?
Back a decade ago we had several control valve reliability prediction initiatives at Valve World
• In 2005 the WIB Final Element Workgroup organized a 3 day CVRP (control valve reliability prediction) seminar at
Valve World Maastricht. 60 to 80 valve specialists caucused together to better address control valve controllability and reliability. It triggered me to comeup with a KPI to quantify reliability.
• Between 2006 and 2010 the WIB Final Element Workgroup members conducted several workshops to address controllability and reliability. We focused on failure modes and effects to comprehend where reliability is at stake.
• Between 2009 and 2013 FIRST, the developer of CONVAL, developed the Reliability Index (Ri) KPI based on a prediction algorithm. We focused on traffic lights (green, yellow, red) to identify challenging applications for the process designers. We also focused on a KPI curve over the full valve travel. As a coincidence the prototype Ri was applied on the non fit for the application control valves for a major petrochemical expansion project in Asia, and proved robust.
The process designer view of the Reliability Index, using traffic lights to flag or highlight the reliability challenges.
All challenging valves turned RED! A trigger for the End User to convince Management to apply the Algorithm not at the end, but at the beginning of major projects. The cost/benefit ratio is so high that it was a no-brainer. However convincing projects organizations to apply this as a service, i.e. as an upfront cost, takes time.
• Between 2013-2014 FIRST developed a bulk engineering prototype, called Conval Adapter Tool (CAT) for potential
use as a service on major projects.
The CAT Consult Approach
In 2014 we piloted the service on a major US fracking project, engineered out of Europe to get a proof of concept. In 2015-2017 we applied it during detailed engineering on a major hydrocracker upgrade project in Europe. The startup happened early this year and the approach was 100% successful and worth every penny!
In the meantime (2018-2019) we are concurrently applying the approach on major projects in NA, in Europe and in Asia.
Some of the valve analyst/specialist views of the Reliability Index to guide the analyst in mitigating those process design challenges:
FIRST, the CONVAL developer, predominantly a strong IT organization, used their talents to develop engineering tools especially around sizing and selection! Together with the End User input on how to realize effective engineering
tools their talents proved very effective to realize such tools. CONVAL taught us to understand valve fluid dynamics!
The Reliability Index Ri algorithm enabled us to quantify challenging application combinations like cavitation, flashing, outgassing, outlet velocities, saturation, noise. It also provided us with the precise recommendations to mitigate those application challenges.
CAT gave us the IT skill set to better manage bulk engineering data exchanges between EPC process design, EPC instrumentation and Valve vendor experts. There are tons of roadblocks why those exchanges do not work as it should. Concurrent engineering is causing challenges for everyone to work with the master data. CAT is the spider in the web to enable effective engineering data exchange so we can analyze, verify, validate and realize fit for the application control valves.
We are exploring avenues to extend CAT Consult beyond control valves. More at the Valve World Americas workshop!