Pinnacle R&D Roundtable: The Premise
Pinnacle is actively working to advance the mechanical integrity industry alongside our customers, partners, and other industry leaders. We value collaboration and believe there is a lack of effective knowledge sharing, networking, and the free flow of ideas in the market. For that reason, Pinnacle is hosting exclusive roundtables, where leading-edge ideas related to better using data-driven approaches to mechanical integrity can be explored in confidence with like-minded MI leaders.
Participants:
Are Mechanical Integrity leaders, that have shown a desire to move the industry forward
Have financial responsibility for inspection or plant integrity/reliability for fixed equipment
Have an ability to evaluate historical data and prioritize inspection using data analytics
Desire to optimize piping and pressure vessel CML inspection
Desire to quantify the value of inspection and incident avoidance in financial terms
CML Optimization
The traditional approach to CML Optimization has been the elimination of CMLs. We believe that the focus should first and foremost be on effective risk management (maintain or reducing risk) and production impact. Condition Monitoring Optimization is a new, data-driven methodology for developing inspection scope, techniques, and intervals that are dynamically updated as information becomes available. Optimization enables facilities to confidently prioritize inspection of CMLs and identifies where additional data is required, where inspection adds little or no value, or when corrective maintenance is needed. A case study will be provided where an optimized monitoring program for was developed for an energy company identifying CML inspection that reduces risk and increases availability. The program prioritizes CML inspection schedule and scope while extending intervals for over 50% of the total population. In addition, remaining risk and downtime contributors were mitigated by identifying other inspection and monitoring techniques to further reduce loss potential.
The program does the following:
- Identifies CMLs that fail a specific risk criteria within the plan time.
- Identifies CMLs that potentially reduce production reported in terms of availability.
- Evaluates the circuit data statistically to characterize thinning type behavior (general versus local).
- Identifying CMLs with high POF/risk but low uncertainty.
- Localized CML circuit inspection targets a specific statistical confidence desired through inspection.
- Generalized CML circuit inspection targets the % coverage desired to achieve the desired confidence.
In addition, we will discuss how we are analysis using minimum required thickness (tmin) as our failure criteria (critical thickness) as well as exploring the option of using a fitness for service (FFS), rerated minimum thickness, and reduced safety factors.