The Foundation of Your Risk-Based Assessment Model

The importance of accurate data

As an asset owner, would you prefer having three data points you are 100% confident in or a thousand points you cannot trust? This question is critical when assessing the integrity of plants, refineries, or pipelines, where thickness loss measurements are collected periodically.

The Consequences of Unreliable Data

When asset owners lack trust in their data, they constantly face uncertainty. Without accurate data, it’s impossible to determine if corrosion mechanisms are accelerating. Decisions about maintenance and inspection schedules become reliant on predictive models that might incorporate flawed data.

In risk-based inspection (RBI) and asset integrity management, unreliable data can skew risk assessments. This can lead to either overly optimistic or overly conservative evaluations of corrosion risk. As a result, maintenance may be either unnecessarily frequent or dangerously insufficient, leading to increased costs or a heightened risk of equipment failure and accidents.

The High Stakes of Inaccurate Assessments

Not prioritising repairs on critical assets due to inaccurate data has significant consequences. Fires, explosions, toxic releases, fines, penalties, and legal liabilities are potential outcomes. Delaying repairs can also lead to more severe damage over time, resulting in higher long-term repair costs or even complete replacement of irreparable assets.

Therefore, asset owners must prioritise accurate data collection and rely on human-independent measurements. If you are navigating the uncertainty of unreliable data, this blog is for you.

Understanding Complex Corrosion Mechanisms

The rate of thickness loss due to corrosion varies based on material, environment, and protective measures. Corrosion can be linear, but often, it accelerates over time, leading to non-linear thickness loss. This is common in pitting corrosion, where pit depth increases the corrosion rate.

Since corrosion kinetics are complex and seldom fit neatly into linear models, regular inspections and traceable techniques are essential to accurately assess corrosion rates and predict thickness loss.

Advanced Predictive Maintenance

Asset integrity predictive models forecast the breaking points of physical assets using data trends, engineering principles, and statistical methods. These models help prioritise maintenance based on corrosion rates—steeper slopes indicate a higher priority for repairs.

By accurately predicting breaking points, organisations can optimise maintenance schedules, reduce downtime, and improve safety.

Critical Thickness and Industry Standards

The American Petroleum Institute (API) provides guidelines for inspecting, maintaining, and repairing refinery equipment to prevent failures due to corrosion. The concept of critical thickness or minimum required thickness (MRT) is vital. It ensures structural integrity and safe operation under expected conditions, including pressure, temperature, and corrosive environments.

For example:

– API 510 covers pressure vessel inspection and specifies minimum thickness based on corrosion rates, design conditions, and material properties.

– API 570 pertains to piping systems, considering design pressure, corrosion allowance, and material properties.

When thickness reaches critical levels, immediate action is required to maintain safety and compliance.

The Impact of Aberrant Data

Aberrant data can significantly distort corrosion rate calculations. Outliers can skew the fitted curve away from the overall trend, leading to incorrect thickness loss estimates. This can either understate or overstate actual material loss, affecting maintenance planning and prioritisation.

Inaccurate data can lead to unsafe operating conditions or unnecessary shutdowns, repairs, or replacements, increasing costs and inefficiencies. It also risks non-compliance with industry standards, resulting in penalties or legal issues. Therefore, it is crucial to use reliable, accurate, and traceable data independent of human influence.

Ensuring Trust in Data

Creaform 3D scanners, combined with VXintegrity software, offer metrology-grade accuracy, traceable data over time, and human-independent results. This ensures measurement consistency and eliminates doubts related to aberrant data. Unlike pit gauges and advanced techniques like phased array, radiography, and eddy current, Creaform provides reliable damage evolution analysis you can fully trust.

Accurate Data Leads to Reliable Models

To maintain asset integrity over the long term, especially with data collected every 1-2 years, measurements must be accurate and free from human error. Inaccuracies can corrupt the database, making it unreliable for maintenance decisions.

Asset owners must rely on accurate, traceable, and human-independent data sources to develop effective and reliable predictive models. This ensures resources are allocated to the most critical needs, balancing short-term constraints with long-term operational and safety objectives, thus preventing disasters and maintaining safety.

Learn more about Creaform NDT solutions and VXintegrity, to discover how to ensure your risk-based assessment model is based on the most accurate data available.