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Enterprise Asset Management

Sarah Stewart, Jon Krome
18 Jan 2021

In this POV we discuss how more modern data gathering and analysis solutions can provide insight about an asset’s health.

Introduction – Why is asset integrity important?  

During our first session, we discussed the differences between asset reliability and asset integrity and the importance of this differentiation. Recall that reliability refers to moving assets (rotating or reciprocating assets – assets that have “heartbeats”). Integrity refers to fixed, static assets (typically without moving parts – infrastructure-type assets).  In our second discussion, we dove deeper into asset reliability, discussing the best practices an organization should follow to get started with an APM program and avoid the data paralysis trap. During today’s discussion, we will share our points of view about asset integrity and discuss how more modern data gathering and analysis solutions can provide insight about an asset’s health. This is particularly unique as these types of assets do not have “heartbeats.” As we discuss asset integrity, we will also introduce the concepts of asset risk and criticality to help your organization determine the importance of collecting the right data for the right assets.

As described in the first article, asset integrity refers to expected performance of static pieces of infrastructures such as tanks, pipelines, supports, vessels, grating, walkways, light stanchions, etc. These assets must perform their intended function while withstanding the effects of external degradation influencers such as pressure, gravity, erosion, and corrosion. Tanks and pipelines must contain the liquids and pressures within. Walkways on offshore facilities, refineries, or chemical plants, sometimes towering hundreds of feet, must confidently support the weight of humans and equipment. We expect them to retain their physical and mechanical integrity to contain their associated “hazards.” Some of the worst industrial disasters on record were the result of a loss of integrity, leading to a release that escalated into an explosion or physical collapse that led to catalyzed other, unfavorable scenarios.

Why is asset integrity such an important discipline within any organization that maintains a level of safety and security for its employees or customers? Many of the industrial structures and vessels have gotten older, with many outliving their original design life. With adequate focus on asset integrity, structures can perform their intended function well past their design intentions, but prudence must be taken to ensure they are inspected, and risk of failure mitigated if found. Consider the Golden Gate Bridge, built more than one hundred years ago, still performing its intended function safely but part of a very deliberate asset integrity program, yet other bridges fail, seemingly without the attention to their integrity.

All assets are not created equally

Like the assets within the reliability discipline, there are those integrity-related assets that are more or less important than others. While not suitable for the exact adoption of a reliability-centered maintenance approach for assets in motion, there are other techniques to determine the most critical fixed assets to be included in an integrity program.

The main factor is the need to avoid asset failure. As asset’s criticality is based on the likelihood and consequence of failure. This is also known as risk. Likelihood is a straightforward concept, though at times more difficult to quantify. It can be based on age, use, duty cycles, or the impact of weather conditions. Consequence of failure is simpler to quantify, it is based upon the cost of volumes lost or equipment that is damaged. Consequence must also consider the potential human toll. We suggest evaluating your assets using at least a simple high-medium-low index, though most companies use some form of a risk matrix that has much greater granularity.

Assets that are classified within the highest zones are critical, while equipment classified in a lower index receives less prioritization. Critical assets deserve the most attention. Organizations can use techniques such as risk-based inspection (RBI) to determine the nature and frequency of inspection and data gathering. Most process-related industries possess their own standards that assist them in defining the prescribed inspection intervals and inspection types for certain archetypes of equipment under specific conditions.

Measurements matter

After using the appropriate method to determine asset criticality, and its corresponding inspection frequency and type, it is the reliance on the analysis of the data gathered that will assist engineers and operations leaders to best manage risk. Today, many integrity-related inspections have evolved to highly specialized services. The prescribed technology to gather the measurements is so advanced, and is constantly evolving, and the inspections are infrequent, it remains very difficult for local technicians to gain and retain the required expertise to exactly perform the work. Compared to the measurements for rotating equipment which can occur automatically many times per second, measurements for integrity monitoring may only be gathered quarterly or annually or even less frequently.

Thus, these infrequent measurements are very important, and often cannot be repeated if the data gathering method was poorly executed or the data became corrupt. Once the data is correctly gathered and managed it must be analyzed to identify anomalies or defects. Pipeline pigs, cameras, and drones have more power than ever to gather data. Integrity engineers and data scientists may use vendor associated interpretation tools in conjunction with their own toolsets to analyze the data. As the ability to collect even more data evolves engineers will need the help of artificial intelligence (AI) or machine learning (ML) to sift through the voluminous data sets more quickly to identify potential risks, allowing them to take appropriate and timely actions to mitigate the potential consequences.

What’s next?

Many companies, especially those with older facilities, have lost sight of their inventory of integrity-related assets. Many organizations do not have an accurate master list of their assets. Thus, step one is truly an inventory exercise. Once complete, the asset criticality must be determined. This, like RCM for machinery in motion, is best accomplished with a cross-functional team and RBI can then be sensibly applied to define interval and nature of inspections.

How much do you really know about your integrity-related assets and their risks? If you aren’t sure, we can help. Please reach out to us directly.

To assist with the journey, an assessment should also be performed that will highlight the needed areas of focus and priority. As integrity improvements are more than just about the physical facility, this may include topics such as new designs, data management, supplier management, management consultancy, training and competence, and action/remediation implementation.

Who we are:

Sarah Stewart

The act of monitoring an asset is not new. We monitor, analyze, and predict most days without thinking about these acts. The simple surveillance of reading the gauges on our car’s dashboard or checking oil levels, or feeling how the vehicle’s suspension system reacts over potholes and tight turns is a data-gathering exercise brains act as the analysis and prediction engines. But with today’s ever-increasing equipment complexity, our minds can no longer do all the work, and we must rely upon more sophisticated technologies to help us “find a lemon before it becomes a lemon.”

Jon Krome

When I was a young engineer, in a small central California oilfield, we performed all of the analysis in “plotbooks” populated with field oil well production data from our fleet of technicians. I would get a single production value each month, and a dozen for the full year. A dozen data points on valuable assets seem unheard of by today’s standards. Measurement devices are much less costly, as are communications and data management components. How did we ever get the job done way back then?