Ali Kashi, Business Development Manager | Downstream & Chemicals
Extracting AI value and dispelling AI hype is not an easy journey for asset-intensive companies to take. Yet, when employed correctly, AI provides the ability to boost asset-intensive operations to new heights – making the journey worth it, if they follow the right path.
Demystifying Hybrid AI
In a relatively brief time, AI technology at Radix has grown from using a simple language model only capable of responding to if/then statements into a deep learning program capable of solving complex problems using large language models that contain a vast amount of human knowledge. This includes using new, generative AIs that baseline knowledge to foster connections and make predictions that elude many human users.
At Radix, we first started combining the 1st principal equations with Machine Learning (ML) algorithms to help us develop tools to leverage physics with the ability to monitor and find trends in vast amounts of data. This “hybrid AI” lead to tools that could be used to predict failures, thereby, allowing users to get away from dependence on manual maintenance programs for equipment.
Being able to predict potential failures is important when dealing with hazardous operations. In addition, maintaining accurate models can be a time-consuming task. A person can build optimization models in spreadsheets using tools such as Solver, but it can be a challenge to devote enough time and people to build the models within the required period. This is of course before you factor in maintaining the model and distributing the information to those who need it the most. Leading to a spaghetti bowl of custom spreadsheets throughout the operations of an organization.
In some cases, it's easier because you have online and connected instruments or continuous processes in the process. But when you go to, for example, what is the deactivation time for that specific catalyst, it is an extremely hard problem or variable to predict – and one made more accurately and effectively by AI and ML.
Radix + AI = Peace of Mind Operations
Asset-intensive companies operate a wide variety of equipment and machines with complex parts, and Radix is always looking for ways to help them protect their capital investments. By utilizing AI to better understand the condition of the various parts and their potential failure points, we have helped prevent downtime, optimize maintenance schedules, and develop ways to use less fuel or energy. With Radix and AI, you can avoid the 3:00 AM phone calls to come into the plant to perform maintenance or perform calculations.
As a side note: the safety benefits, which AI provides, are also a real benefit for downstream companies. For example, there are programs we run at Radix where we utilize image processing to ensure that operators are wearing the correct personal protective equipment in restrictive areas. If the AI detects that an employee is not wearing all the right equipment, or is wearing it incorrectly, it can trigger an alert or an alarm until that employee fixes their gear. The same AI-based image processing software also ensures that escape routes and emergency access points are free of debris in case of an emergency.
Despite AI still having a long development road ahead of it, companies like Radix are already using it to improve both safety and operational efficiency. Additionally, AI has given engineers in downstream and beyond more understanding over complex processes that have a substantial chance for error if mixtures or parameters are not precise and correct.
Given its impressive early gains and the massive potential to help with future operations, we can expect many companies to follow Radix’s lead in AI application development and implementation. To get started today contact me at Connect with us | Radix (radixeng.com)
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