Enterprise Asset Management
Blog: Capgemini CTO Blog
Over the next few months, we will be sharing our insights and points of view into the best ways to tackle the ever-evolving but conceptually long-standing, field of asset management. Specifically, regarding asset reliability and asset integrity. We believe there is a significant distinction between asset reliability and asset integrity. Most of the new, complex, and “wow factor” technologies today focus on monitoring, analyzing, and predicting an asset’s reliability while not considering its integrity. We believe the differentiation between the two fields is essential to understand to best select the most appropriate methods and technologies to “find a lemon before it becomes a lemon,” ultimately maintain throughput, and decrease maintenance both costs and risk.
We begin our discussion by offering what we believe is the difference between asset reliability and integrity, and why this differentiation is important. We will share examples in both areas throughout our discussion and will try to keep these examples industry agnostic. We will use some of our industry-specific experience to illustrate the differences, but trust you will translate these examples to your specific assets and use cases.
In subsequent discussions, we will dive deeper into asset reliability and asset integrity and the foundational elements necessary to move your organization towards an enhanced asset management level, if desired. We will conclude our discussions by proposing an opinion on how we believe the convergence between these typically distinct disciplines and methodologies may be a better option for your assets and your organization. Let’s start by exploring the differences.
Asset reliability (monitor, analyze, predict)
Asset reliability focuses on rotating, reciprocating, or assets that move in one or many ways. These assets have “heartbeats,” and their rhythms can be measured. Technologies today allow us to measure the heartbeats with a device or sensor, allowing us to monitor critical performance variables to look for a “healthy” or “unhealthy” pattern. Some of these assets include integrated sensors that can send data to be measured, and some assets require retrofitting with “aftermarket” sensors. Even a simple pump or a compressor has many heartbeats with unique variables that define its performance. Monitoring these variables can help identify anomalies within the assets’ prescribed or designed operating parameters. Examples of sensible variables are pressure, temperature, throughput, or vibration.
These types of assets typically have a designed life expectancy based on a few critical components, such as their seals or their bearings. These assets operate within defined parameters, which include environmental conditions and routine maintenance schedules. Consider automobiles or consumer goods – the designers have made assumptions about how these assets will be used and under what conditions to determine their advertised life expectancy. It is the same principle for pumps, compressors, and other industrial assets. Assuming these industrial assets are used under the recommended conditions, the asset will perform its intended function throughout its design life. Ideally, before the asset is put into use, maintenance practices such as reliability-centered maintenance (RCM) and failure mode and effects analysis (FMEA) can be used to identify the most important variables to monitor (the heartbeats). These variables provide the most meaning to help determine the health of an asset. Adopting these practices and tools can also lead the most appropriate maintenance strategy to be selected, distinguishing between prevention, prediction, condition-based, or run-to-fail.
Asset integrity (non-destructive testing and inspections for prediction)
Unlike asset reliability, asset integrity refers to the ability of a fixed asset (non-moving, static) to sustain the effects of pressure, temperature, pH, vibration, erosion, or gravity. Consider tanks, pressure vessels, load-bearing structures, walkways, pipelines, or even bridges. These assets aren’t (typically) moving on their own, yet they still need to be monitored, analyzed, and their failure predicted. Monitoring and analyzing these types of assets are less useful in real time versus the monitoring of rotating assets. The effects of corrosion or wear (and other factors) that occur over more extended periods cause the need for the assets to be monitored. The monitoring of fixed assets is VERY different from that of monitoring rotating assets. We typically rely on infrequent visual inspections and non-destructive testing, such as ultrasonic testing or pulsed eddy currents. This data collected from these means must be considered just as critical as data collected from sensors on moving equipment. The data is typically analyzed using fit-for-purpose tools instead of enterprise-wide asset performance monitoring tools and dashboards. These assets differ from rotating assets because their actual failure or degradation likely took months or years to develop. Still, their failure may result in a more dramatic outcome, such as a release of hazardous, combustible, or flammable fluids.
We hope that our explanations and examples have resonated with you and that your most valuable asset, your brain, is still reliable and integral. We love to discuss these subjects and the potential for technologies to support their unique heartbeats and influencers. In our next discussion, we will take a much deeper dive into asset reliability and talk about the impact of data hoarding and data silos on an organization. If you have any questions, we’d love to spend time with you to discuss them. Please don’t hesitate to contact us.
WHO WE ARE:
Sarah Stewart is a Principal within Capgemini Invent and leads the NA Enterprise Asset Management practice. She has been involved with maintenance systems since she was a “butter bar” Platoon Leader in the US Army, where she first learned the importance of documenting maintenance history in PMCS books. She has spent most of her career implementing EAM systems within discreet and process manufacturing companies and across the Electric and Gas Utility domains. She merges her technical and functional expertise to help companies develop a strong EAM foundation that will support our connected reality opportunities. She is an IBM Certified Maximo Solution Advisor.
Jon Krome is a Principal with Capgemini Invent’s Energy, Utilities, and Chemicals practice. He has thirty years’ experience in Exploration and Production. He has also spent time in Midstream, managing pipelines and processing plants. He has a proven track record of delivering complex, value-added reliability and integrity improvement projects. He began his career in Bakersfield, California, US. He spent twelve years in Mobil and Aera Energy LLC (a joint venture of ExxonMobil and Shell) in various engineering, business, and management roles. Jon then spent nine years as a management consultant, delivering to multinational Oil and Gas companies with Big 6 consulting companies. Jon joined BHP Billiton Petroleum in March 2009 in the Trinidad & Tobago Production Unit as Operations Manager and then onto the UK in June 2011 as Country Manager. He arrived in Houston in 2013, serving as Operations Manager in Eagle Ford. His final role in BHP Billiton was as the Global Head of Operations, Maintenance, and Improvement.