Incorporating Artificial Intelligence (AI) into your maintenance or reliability program may sound intimidating, but when implemented and utilized correctly, AI can help your facility achieve next level predictive capabilities. While facilities can hit first quartile reliability benchmarks without using AI, the incorporation of AI into maintenance or reliability programs can still be very valuable in a facility’s pursuit of better performance.

Before implementing any AI technologies, you should first understand what AI is. AI is the simulation of human thinking and thought processes. AI uses data and sophisticated algorithms to perform tasks previously only performed by humans such as learning, reasoning, and pattern recognition to better forecast future performance and improve decision making. Here are five ways AI can benefit your maintenance or reliability program:

AI can better predict future performance

AI can better predict future performance by using real-time data. This can help your maintenance or reliability program by identifying potential failures earlier and more accurately with process, operations, maintenance, reliability, and integrity data. When combined with a well-designed program and AI-trained employees to interpret and validate the data, you can ensure that you are making the most up-to-date and informed decisions that drive reliability for your facility

AI can detect anomalies or deviations from normal operations

AI can detect anomalies or deviations from normal operations that would otherwise be very difficult to detect. By detecting non-normal process and operating conditions, including combinations and trends not typically identified by the human eye or traditional statistics, AI can help you identify areas of concern, and in some cases, the causes or trends leading to an event. Once you are able to understand the cause of an event, you can make proactive steps towards preventing another event from happening in the future. Additionally, AI can also analyze and identify potentially erroneous historical data, improving the accuracy of prediction models. By identifying erroneous data, AI can also help declutter your Computerized Maintenance Management System (CMMS) or Inspection Data Management System (IDMS).

AI can identify correlations

AI can identify correlations across very large data sets with a multitude of variables that would otherwise be time consuming and extremely difficult to process. Identifying data correlations helps facilities gain a better understanding why certain events occur, and the overall impact that key variables can have on your facility. Additionally, facilities can use correlations to better understand the impact certain actions will have on the results you care about.

AI can classify images, data trends, languages

AI can classify images, data trends, languages and anything else that can be represented in digital form. Additionally, AI can also automatically organize that documentation and data. This can help with visual inspections performed using AI technology, as well as the classification of failures based on process, operations, maintenance, reliability, and integrity data collected.

AI can optimize decision making

AI can optimize decision making. It can turn a large amount of multi-variate data into fine-tuned probabilities of failure for individual assets and assist in decision making. This can be used to support decision making on prescribing optimal maintenance and inspection activities based on asset condition, cost, risk and the availability of resources. AI could also one day evolve to greatly enhance automated process controls, which can improve production and increase your bottom line.

Now that you have a better understanding of AI, take a look at your own facility’s maintenance or reliability program. Do you have the correct processes and tools in place to make AI work? If so, how can AI help your facility achieve next level predictive capabilities and help your facility run more reliably?

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