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May 28, 2020

Shawn Rana Explains Artificial Intelligence (AI) in Control Systems for Fertilizer Production Plants

From managing irrigation and water usage to predicting weather conditions and identifying crop issues, artificial intelligence (AI) has a growing role to play in agriculture. AI has also been adopted by the fertilizer production industry. When it comes to fertilizer plants, AI can cut costs, ensure smooth operation, and increase productivity.

Shawn Rana is a seasoned Senior Executive and Consultant with 26 years of success in manufacturing, fertilizers, oil and gas, and agrichemicals. He piloted construction of the first world-scale, greenfield nitrogen fertilizer facility built in the U.S. in more than 25 years. This plant is recognized as one of the most innovative and efficient manufacturing plants in the nation. Shawn believes that as far as the future of AI and fertilizer production plants is concerned, the sky's the limit.

Speed and Efficiency

The fertilizer market is ruled by unpredictability. Demand fluctuates sharply and fertilizer plant owners have to cater for large swings in demand and prices on short notice. When it comes to various fertilizer blends, the way Shawn Rana sees it, one of the issues that fertilizer producers have to contend with is the time it takes to optimize the plant operations for safety and efficiency.

That’s where AI comes in. It helps optimize the plant which also improves safe operations in a shorter time. The idea is to have AI monitor the whole plant and deal with any problems or deviations automatically without the need for human input. This minimizes downtime, streamlines the operation of the plant, and optimizes productivity.

Maintenance on the Fly

Like any other facility, fertilizer production plants have many moving parts and multiple processes that all contribute to making the end product. However, if one of those parts goes down for some reason, the whole plant will come to a standstill which means losing business and cutting down on profits.

A plant that harnesses the power of AI can reduce such downtimes considerably. With every device in every unit fully connected to the monitoring system, AI works in conjunction with the installed control system and gathers and processes a lot of information about the operation efficiency of the plant. At the first sign of something going wrong, and even without operator intervention, the system predicts the how to respond so that other systems in the plant are not impacted and takes action to avoid a full shutdown and fixes the problem before it becomes too serious.

Shawn Rana on AI in Agriculture

On the other side of the equation, AI and machine learning algorithms help farmers get the most out of fertilizers. As every farmer knows, the quality of the soil degrades over time. With every farming cycle, the soil loses its valuable nutrients and develops defects. According to Shawn Rana, most farmers notice the weakness in their land only after they get a few less than ideal crops or spend time and money on soil samples which only examine a very small portion of the field.

“This is a serious problem,” he adds, “that can cost the farmer a lot. Luckily AI using machine learning can evaluate the state of the soil and give an accurate report of its strengths and weaknesses.” The report covers everything from the nutrient needs and pathogen aspects of the soil regarding the presence of fungi and bacteria to a full microbial evaluation and how to best remedy the situation.

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