How to Achieve REAL Results with Artificial Intelligence (AI) in Enterprise Asset Management

In today's fast-paced asset management world, maintaining peak efficiency and reliability of assets is more critical than ever. Enterprise Asset Management (EAM) systems have long supported asset intensive industries such as oil & gas, mining & metals, manufacturing, utilities, and pharmaceuticals that aim to streamline maintenance and operations and extend the lifespan of their assets.  

However, traditional EAM approaches can be time consuming and inefficient, making it challenging to keep up with current industry demands. In response, Artificial Intelligence (AI) has accelerated digital transformation, promising unprecedented improvements in predictive maintenance, operational efficiency, and overall asset performance. But, for each beneficial AI innovation, there is an equal amount of ineffective AI hype.  

So how do organizations cut through the hype of AI and harness the true potential of AI to produce real results?  

In this blog, we will delve into ways businesses can take advantage of artificial intelligence in enterprise asset management (while avoiding the hype), the challenges associated with not embracing AI, and the results organizations can achieve by leveraging AI.

 
Be Cautious of Misleading Artificial Intelligence (AI) Hype in EAM  

Before you begin to evaluate how you can start incorporating AI into your enterprise asset management, you should be aware of how to avoid the misleading AI hype.  

“‘AI-powered’ is tech’s meaningless equivalent of ‘all natural.’” – Devin Coldewey, TechCrunch 

As the rise of AI is becoming larger, many organizations add the label “AI powered” to their solutions without explaining how the AI features will help you achieve real results.  

“'AI’ suffers from an unrelenting, incurable case of vagueness — it is a catch-all term of art that does not consistently refer to any particular method or value proposition.” – Eric Siegel, Harvard Business Review  

To combat this trap, you need to remain focused on the “how.” As you are looking into a new “AI powered” solution, ask vendors about the practical results the solution will help you achieve with its AI capabilities.  

Check out our on-demand webinar “How to Achieve REAL Results with AI in Enterprise Asset Management” where we dive into this topic.  

How Businesses Can Leverage AI in EAM 

Asset Performance Management (APM) and Master Data Management (MDM) are essential components of EAM, focused on optimizing the performance and data integrity of physical assets throughout their lifecycle. Leveraging AI in these areas significantly enhances operational efficiency, cost savings, productivity, and data accuracy. 

AI solutions can help organizations achieve predictive maintenance more easily by using historical and real-time data to forecast equipment failures, enabling proactive maintenance and reducing downtime. Real-time monitoring and diagnostics can also be streamlined with AI, using predictive data models to identify issues early.  Large Language Models can then provide diagnostics guidance leveraging historical issues and maintenance records to get to the root of the problem quickly.  With the ability to analyze large amounts of sensor and asset data, organizations can make more informed and timely decisions regarding asset utilization and resource allocation. 

For master data management, AI-driven Optical Character Recognition (OCR) technology helps streamline data collection by extracting critical information from asset tags and labels. Machine learning algorithms improve data consistency and accuracy by validating new entries and maintaining clean, accurate master data through robust governance.

 

The Different Layers of AI 

To achieve this, organizations can take advantage of different layers of AI, including large language models (LLM), Generative AI (GenAI), Deep Learning, Neural Networks, Machine Learning, and Artificial Intelligence. Prometheus Group solutions Master Data as a Service (MDaaS) and Asset Performance Management (APM) leverage AI capabilities like machine learning, neural networks, and large language models:  

• APM Recommended actions (machine learning)
• APM Predictive Analytics (neural networks)
• APM Diagnostics (large language models)  
• MDaaS BOM Analysis (large language models)
• MDaaS Material Cleansing and Enrichment (large language models)  

Not embracing artificial intelligence and digital transformation in EAM can lead to increased costs, limited data insights, poor asset performance, and competitive disadvantage. To achieve real results and thrive in today’s business landscape, organizations must prioritize digital transformation and harness the power of AI and other advanced technologies. 

How AI Can Be Used in Enterprise Asset Master Data Management  

Effective management of asset master data is crucial for the smooth operations and maintenance of enterprise assets. AI technologies can significantly enhance the accuracy, consistency, and governance of asset master data, ensuring that organizations have reliable and actionable information.  

Here’s how AI can be leveraged in Enterprise Asset Master Data Management: 

1. Utilizing Optical Character Recognition (OCR) for Data Collection:  

AI-driven OCR technology streamlines the process of collecting asset information in the field. By capturing a photograph of an asset tag, nameplate, or label, OCR can extract critical information using machine learning and pattern recognition techniques. 

2. Ensuring Data Consistency with Machine Learning:  

Machine learning algorithms play a pivotal role in maintaining the consistency and accuracy of asset master data. By analyzing existing asset records, Bills of Materials (BOMs), and other relevant documents, machine learning can establish a baseline of expected data characteristics and automatically scan and validate records. 

3. Cross-Referencing and Data Governance:  

AI facilitates robust data governance by cross-referencing records across multiple databases and upholding governance rules. Machine learning algorithms can detect duplicate or redundant records, ensuring that the master data remains clean and accurate, and automate tasks to provide a standardized method for data governance. 

By leveraging these AI capabilities in master data management, organizations can achieve more accurate, reliable, and actionable asset data, driving better decision-making and operational efficiency. 

How AI Can Be Used in Asset Performance Management  

AI technologies offer transformative capabilities for managing asset performance, enabling organizations to enhance efficiency, reduce downtime, and optimize maintenance processes. Here’s how AI can be effectively utilized in Asset Performance Management: 

1. Creating Predictive Models to Track Asset Performance and Identify Anomalies:  

AI, through machine learning and neural network capabilities, can develop predictive models that define normal operating behaviors for each asset. These models continuously monitor asset performance, detecting even minor deviations from the norm. 

2. Leveraging Historical Actions to Provide Suggested Actions:  

AI can utilize classification algorithms to analyze historical user actions in response to various asset conditions. By doing so, it can suggest appropriate actions based on past responses, such as snoozing an alert, retraining a model, or flagging an issue for further diagnosis. 

3. Utilizing Historical Behaviors to Provide Diagnostic Guidance:  

Generative AI can offer diagnostic assistance by analyzing historical data and behavior patterns of assets. This technology provides users with diagnostic suggestions, information on asset history, and mitigative actions based on similar past issues. 

These asset performance management AI capabilities enable organizations to enhance operational efficiency, minimize downtime, and optimize the performance and maintenance of their assets. 
 

4 Major Benefits of Utilizing AI in Asset Management Processes 

Incorporating Artificial Intelligence (AI) into asset management processes revolutionizes how organizations handle their physical assets, leading to numerous benefits that enhance operational efficiency, reduce costs, and improve overall performance. Some advantages of utilizing AI in asset management include:  

1. Enhanced Predictive Maintenance:  

AI-driven predictive maintenance uses historical and real-time performance data to forecast potential equipment failures. By analyzing patterns and identifying anomalies, AI enables proactive maintenance, reducing unplanned downtime, extending asset lifespan, and lowering maintenance costs. 

2. Real-Time Monitoring and Diagnostics:

AI enhances real-time monitoring by processing continuous data streams from embedded sensors. These sensors collect information on operating conditions, which AI algorithms analyze to detect deviations. This immediate diagnostic capability helps identify and address issues promptly, preventing minor problems from escalating into major failures.  

3. Data-Driven Decision Making:

AI systems process vast amounts of data from IoT devices, historical records, and external sources like weather conditions. By integrating and analyzing this diverse data, AI provides actionable insights and recommendations, aiding in informed decision-making regarding asset utilization, investment, and resource allocation.  

4. Enhanced Risk Management:

AI evaluates historical failure data and external risk factors to assess and manage risks associated with asset performance. By predicting potential hazards and suggesting mitigation strategies, AI proactively safeguards asset reliability and prevents costly incidents.  

Leverage AI Powered Technologies to Achieve REAL Results in EAM 

In the rapidly evolving field of Enterprise Asset Management (EAM), leveraging Artificial Intelligence (AI) is no longer a futuristic concept but a critical necessity. The integration of AI into EAM systems enhances predictive maintenance, real-time monitoring, decision-making, and overall asset performance.  

Organizations that embrace AI can expect significant improvements in operational efficiency, cost savings, and competitive advantage. By utilizing AI in asset management processes, companies can achieve real, tangible results, ensuring their assets are not only efficiently managed but also optimized for long-term success. 

Do you want to learn how you can leverage the power of AI with the Prometheus Platform? Reach out to us today to discover how you can streamline processes like asset performance management and master data management with advanced AI capabilities.