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BOAR Analysis
We go beyond the surface to analyze piping thickness data and provide valuable insights into internal corrosion. Our patented Bayesian Optimized Asset Reliability (BOAR) methodology combines AI, historical thickness data, inspection program details, and inspector expertise to deliver predictive results. We leverage AI to identify localized corrosion issues and offer customized recommendations that will optimize inspection points and lead to reduced maintenance costs.
Our approach offers clarity for every department at your plant. As your partner, we work with you to ensure everyone understands and supports the streamlined inspection plan. A BOAR analysis will give you the tools you need to make informed decisions on where to place inspection locations and how to manage overall corrosion.
CML Optimization
Our condition monitoring location (CML) optimization model allows you to shift from arbitrary inspections to a targeted and precise plan. We use our patented technologies, data analysis, and corrosion data gathered during the Build phase to identify asset degradation and potential failures. We will also suggest optimal CML locations for detecting localized corrosion issues. Our approach will give you more time to intervene and improve your maintenance strategies.
Software QA/QC
The visual reports from your BOAR assessment allow us to quickly and easily review the accuracy of the data in your IDMS software. We can rapidly identify incorrect data using the built-in AI features. Our software QA/QC service helps you focus your inspection resources on the real issues rather than ones created by contractors.
Circuitization QA/QC
Using AI and machine learning, the BOAR assessment can anticipate whether you’re comparing apples to oranges. By instantly analyzing thousands of data points and comparisons, we can review circuits created 15 years ago and recommend adjustments such as extensions, reductions, or even circuit consolidation. We recognize that your operations have evolved since those circuits were first implemented; we will use the latest technology to advance your inspection strategies.
Detailed Corrosion Reviews
We use AI to understand where and why corrosion is happening. While you can’t physically climb inside your piping, we use the BOAR assessment to help you visualize how corrosion affects each component and how it relates to the overall corrosion picture. In under five minutes, we can teach you how to interpret our visualizations by showing you how corrosion trends are overlayed onto the isometric drawings. These analysis skills will help you expertly identify localized corrosion and use this new knowledge to confidently ask for more resources or budget allocation.
CASE STUDY
CML Optimization Reduces Unnecessary Piping Thickness Inspection Activities
Industry
Downstream Oil & Gas
Type of Asset
Refinery
Location
USA
Issue
A client recently reviewed the total spending on their piping thickness program. CorrSolutions suggested conducting a high-quality assessment of the current program.
Solution
The CorrSolutions team conducted a pilot CML optimization of a small portion of the refinery where they assessed 90 circuits and 1877 CMLs. The goal of the CML optimization was to provide practical recommendations of how to focus the inspection efforts.
Result
After the assessment, the team recommended the refinery archive 957 CMLs and add 33 new CMLs. As a result, the client was able to reduce the piping thickness inspection program to 953 CMLs for an overall reduction of 50%. Over 10 years, inspecting only 953 CMLs equates to approximately $100,000 USD in savings. The assessment also reduced the CML per circuit count from 20 to 10.
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