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In the rapidly changing landscape of power generation, companies are searching for smart solutions to stay competitive, meet sustainability goals, and open up new revenue streams.

Right at the heart of these solutions is Asset Performance Management (APM), which helps manage and improve the performance of physical assets as part of a broader, more holistic move to contribute to overall company goals. APM is shaping a more sustainable and diversified future for energy, utility, and resource (EU&R) organizations. 

Understanding APM  

APM optimizes the role of physical assets in meeting long-term corporate objectives by analyzing data from company-wide sources and identifying the most efficient and effective repair or replace strategies. APM looks at the company’s unique asset strategy and uses predictive analytics and a continuous feedback loop to move towards optimized maintenance—a game-changer capable of driving operational efficiencies, ensuring equipment longevity, and enabling smarter, data-informed decisions. 

The Power of Data 

We’re living in a data-rich world, and APM knows how to leverage this data for impactful decision making. In 2019, technologies such as the Internet of Things (IoT) generated 13.6 ZB of data, a number expected to skyrocket to 79.4 ZB by 2025. This influx of data, coupled with technologies like Geographical Information Systems (GIS) and Light Detection and Ranging (LiDAR), will cause the data pile to grow ever larger. 

APM’s true strength lies in its ability to make sense of this volume of data – whether data lakes or warehouses, generating insights and predictions that allow for more precise and accurate decisions about asset maintenance and how it will impact overall performance and strategic goals.   

Diversification and Revenue Generation Opportunities  

APM provides power generation companies with opportunities to diversify their energy portfolios and identify alternative revenue streams. It uncovers hidden efficiencies and untapped potential in current operations, providing companies with the means to explore alternative energy resources like wind and solar. 

Achieving Environmental, Social, and Governance (ESG) Goals  

But it’s not all about the bottom line. APM also has a vital role to play in the environment, helping power companies operate more sustainably. It provides insights about how to improve energy efficiency and cut down emissions, ticking off regulatory requirements and sustainability targets. In essence, APM provides a concrete path for power generation companies to meet their ESG commitments while remaining profitable. 

Risk Management and Resilience 

APM’s predictive capabilities help foresee and mitigate risks, leading to a more resilient power infrastructure. As the industry transitions towards renewable energy, it’s imperative to manage and coordinate a broad range of assets owned by various customers. This introduces complex, bi-directional grid systems that generate, use, and sell energy, highlighting the need for APM’s efficiency and risk management abilities. 

Artificial Intelligence, Machine Learning, and APM 

This year, at least 75% of companies in the energy, utilities, and resources (EU&R) sector are expected to rely heavily on AI and ML to drive operational efficiencies and meet broader objectives. 

In the world of APM, AI and ML play key roles. These technologies help get the most out of data, delivering insights, predictive analytics, and automated workflows. The combo of APM, AI, and ML is transforming the power generation sector, offering solutions for fault prediction, disaster recovery, energy demand management, and much more. 

In addition, AI’s role in grid management is paramount, enabling a shift from infrastructure-heavy legacy models to a more resilient and flexible grid system. 

IFS for Advanced APM 

IFS offers a rich suite of features to optimize APM: 

  • Time series analysis: IFS captures data at regular intervals throughout a predefined duration, allowing for precise tracking of asset performance trends. 
  • Anomaly Detection: IFS’s machine learning algorithms can detect anomalies or deviations in asset performance, flagging potential issues before they escalate. 
  • Failure Prediction: The platform can predict potential equipment failures, providing insights into the rate of equipment degradation and the most economical time for repairs or replacements. 

As an asset’s performance declines, the quality of its output also decreases, while energy use and other costs increase. Once the APM program determines an imminent asset failure, it suggests an action at the appropriate time: repair (creating a work order) or replace (creating a purchase order). The results of these actions, even if initially incorrect, are fed back into the AI, continually refining the accuracy of its predictions. 

IFS Cloud EAM tracks and surfaces this information as asset-related metrics like mean time to repair (MTTR), asset longevity, cost, and measures that address health, safety, and the environment (HSE). It can also tie these things back to the assets’ contribution to the company from a production standpoint through both financial and non-financial metrics. 

A more sustainable future 

APM, backed by AI and ML, is paving the way for power companies to explore new opportunities, become more resilient, and make a positive impact on the environment. As the power generation landscape evolves, APM will continue to play a key role not only in more efficient asset maintenance, but in moving EU&R organizations towards a more sustainable future overall. 

To learn more about the transformative power of APM, download our white paper: Unlock the next level of asset management efficiency with APM. 

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