Webinar: Combining Subject Matter Expertise and Data Science to Optimize CML Inspection

CML Optimization Pilot Project Helps Refinery Reduce Risk and Identify Minimum Reduced Inspection Spend of $384K

CML Prioritization as presented in this case study is a new CML Optimization methodology that predicts future thinning based on past performance from a single CML across repairs and replacements, ranking CMLs by the risk posed to safety and production prior to the next scheduled action (repair/replacement/inspection/turnaround) taken on that CML. This project identified CMLs that indicated asset failure within the next one to two years, prior to the next inspection event, and required immediate attention by the facility. The estimated business impact to the facility resulting from the optimization analysis and resulting prioritization scheme is a minimum of $384,000 over six circuits in reduced inspection spend over the next two turnaround cycles. The savings are due to deferment of non-value-adding inspection activities and inspection scope, resulting from the reduction in recommended CML monitoring as well as a decrease in inspection frequency.

Read the full case study: CML Optimization Pilot Project Helps Refinery Reduce Risk and Identify Minimum Reduced Inspection Spend of $384K