Azima AI — How Does It Work?

Artificial intelligence (AI) has the potential to transform plant operations by minimizing downtime and saving resources. But not all AI tools can deliver the results you need. There are a few key factors that set AI tools by Azima DLI apart from others on the market.

In this piece, we’ll get into what AI can accomplish for your organization and how it operates in day-to-day operations. We’ll also explain the key differences between Azima AI and other tools.

AI is an extraordinary diagnostic tool. The right AI algorithm can analyze condition monitoring data from your key assets and then use that data to identify early warning signs of a machine fault. It can even classify defects by severity and make detailed recommendations for what your maintenance crews should be doing.

Modern plants tend to be data-rich and expertise-constrained. Most plants collect reams of condition monitoring (CM) data but don;t have enough technicians on staff to analyze it all. Leveraging the power of AI is a great way to fill the expertise gap and unlock the insights stored in your data. But to reap AI’s benefits, you need to start with the right tool.

Azima AI has data, age, and experience on its side.

The experts at Azima have been perfecting the program’s AI algorithm over several decades. That’s one of the reasons it’s so fast and accurate.

AI algorithms work best when they have tagged data, trillions of data points, and more experience. The longer they’ve been operational, and the more faults they’ve diagnosed, the more effective and precise the algorithms become.

You can compare an algorithm to an experienced technician who gets better at diagnosing machine faults every year. Just like a human expert, AI algorithms continue to learn, self-correct, and fine-tune their capabilities over time. The Azima AI algorithm has been training, fine-tuning, and learning for decades, making it one of the most experienced and trustworthy AI tools around.

Azima started as an engineering firm in 1966, named DLI Engineering. That’s when the company first began collecting data on assets, developing component-level fault definitions, and tagging content in a data lake. That data collection grew over time. Today, Azima has a hundred trillion data points stored in its data lake.

Those hundred trillion data points trained Azima AI’s algorithm. That’s why it is so powerful — it’s equipped with a huge store of institutional knowledge. The algorithm can diagnose 1200 distinct, component-level machine faults. It can make predictions about which assets will likely develop a defect, and when. It can even determine fault severity and set priorities for maintenance crews.

The result? Azima AI’s algorithm doesn’t just issue alerts when your asset’s vibration levels cross a certain threshold. Instead, the AI performs root cause analysis. It issues a detailed prescription so that your team knows exactly what to expect, how to plan for the repair, and what actions to take.

Azima AI starts out with a detailed picture of what, exactly, normal and healthy operation looks like for an asset. It’s worth stressing that the the machine’s normal operation standard is based on years of meticulous data collection — not on ISO standards or manufacturer’s descriptions.

As soon as an asset deviates from its norm in any way, Azima AI’s algorithm spots the deviation. That’s when the diagnostic engine goes into high gear, methodically examining the patterns of every other deviation from the norm from all data points in that asset. It identifies every minute factor that exceeds the normal baseline, and the algorithm compares these vibrations to determine what kind of fault is behind them. This level of detail in analysis can only be accomplished with AI, due to the volumes of data plants capture today.

The algorithm also has a wealth of data on prior machine faults to draw on. This is another key difference between Azima and other, newer AI tools. Data on equipment failure tends to be sparse, but Azima has carried out tens of thousands of machine diagnoses over the past few decades. Its algorithm can tap into institutional knowledge of exactly what machine fault patterns look like.

The value of Azima AI is demonstrated in the efficiency of the Azima professional analysis services. Azima Services have a utilization rate five times higher than traditional analysis. This efficiency comes from AI tools that fill gaps in machinery diagnostics, such as identifying pump vane rates or gear tooth counts and only flagging manual review of priority issues that need analyst confirmation in a vast trove of machine data.

Azima AI’s algorithm is trained to diagnose faults in the 50 most common types of machine components. That includes motors, pumps, fans, compressors, turbines, and generators.

The algorithm never stops learning. As new machines and components are developed, Azima AI’s algorithm is trained and brought up to date. For example, magnetic couplings, which used to be rare, are now widely used. The algorithm has been trained to diagnose faults in magnetic couplings.

In the same way, the algorithm keeps perfecting its diagnostic capabilities. It learns on the job, by observing data and by observing human technicians. The longer it operates, the more effective it becomes.

Briefly, these are the factors that set Azima AI apart from the competition:

• Data wealth — 100 trillion data points on assets, components, vibration data, and faults
• Fault knowledge — Deep expertise of trained fault patterns recognition
• Asset expertise — 6000+ rules, 1200+ fault conditions, 50+ component types
• Component details — AI automation fills diagnostic element content
• Historical relevance — Time-tested algorithms and techniques for 50+ years
• Deep bench experience — Highly-utilized diagnostic services and program management

Azima AI’s world-class algorithm is backed by a team of global experts. They are available to help in just about any capacity, from coaching plant teams at the start to providing expert second opinions when complex or costly decisions need to be made. Azima’s experts also offer full professional service to manage the plant’s program, adding visibility to every level of the organization through repair action reporting, business-level metrics, and periodic management reviews.

Expert consultants are on-call whether you’re looking for assistance in implementing AI, troubleshooting, or training your staff. Our goal is simple — to help plants reap the benefits of a data-driven maintenance approach. That means greater uptime, increased productivity, and maximizing your use of resources.