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- Data collection: Gather historical data on the asset, including information on its design, construction, operating conditions, maintenance history, and any past incidents or failures.
- Inspection and testing: Perform non-destructive testing (NDT) and other inspection techniques to assess the current condition of the asset, identify any signs of degradation or damage, and gather additional data.
- Condition assessment: Analyze the data collected during inspections and testing, along with historical data, to determine the current condition of the asset and identify any trends in degradation or failure.
- Failure analysis: Study the potential failure modes and consequences, and determine the likelihood and potential impact of each failure mode on the asset’s performance, safety, and environmental impact.
- Remaining life estimation: Based on the asset’s current condition, past performance, and anticipated future operating conditions, estimate the remaining service life of the asset. This involves the use of mathematical models, engineering analysis, and expert judgment.
- Recommendations: Based on the RLA results, develop recommendations for maintenance, repair, or replacement strategies, along with associated costs and benefits. This information can be used to make informed decisions about asset management and investment.
Tamás Hám-Szabó
Founder of SAAS First – the Best AI and Data-Driven Customer Engagement Tool
With 11 years in SaaS, I’ve built MillionVerifier and SAAS First. Passionate about SaaS, data, and AI. Let’s connect if you share the same drive for success!
