AI project triples Unipar’s return on investment in Argentina – BNamericas

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Petrochemical company Unipar revealed that one of its artificial intelligence (AI) projects generated a financial return equivalent to three times the investment made, as part of a strategy that already includes more than five AI initiatives across its operations.

Headquartered in Argentina and Brazil, Unipar produces chlorine and caustic soda and ranks among the largest PVC producers in South America.

“The strategy is to keep expanding the use of AI across our operations, both through new predictive solutions and by developing agents focused on automation and customer service,” Ignacio Garriz, Unipar Argentina’s production manager, told BNamericas. “We also see an opportunity in the ability of these models to anticipate the dynamic behavior of the plants and to keep advancing in process optimization, quality, consumption and reliability.”

The first AI project rolled out in Argentina, known internally as Electrolyzer Performance, was a solution to monitor 500 variables tied to caustic soda and chlorine production during the electrolysis process.

For Garriz, one of the main shifts was moving from a corrective approach to a preventive and predictive one, anticipating potential problems and optimizing maintenance resources.

According to the company, the system managed to preemptively detect more than 85% of the unplanned stoppages recorded historically. The higher availability of electrolyzers, from consistently operating at an optimal state, also translates into an estimated 1,300-tonne annual increase in caustic soda production.

At the chlor-alkali unit in Bahía Blanca, the company also rolled out a predictive membrane monitoring system that learns the normal behavior of each element and flags potential failures in advance.

“The project generated a financial return in 2024 equivalent to three times the investment made,” Garriz added.

The company also implemented an advanced process control (APC) system at its VCM production plant – a compound used as a raw material for PVC – aimed at optimizing consumption, stabilizing quality and operating with maximum profitability and safety. “We moved from manual adjustments and controls that depended on lab results to an inferential scheme that anticipates compositions, with systems that make automatic adjustments to meet targets and optimize consumption,” he added.

The company estimates savings of around US$1 million a year, while also helping cut waste generation and the carbon footprint associated with the process.

Garriz said the experience with the AI project at the VCM plant showed that the benefits go beyond each project’s original goal: alongside optimizing consumption, the company identified opportunities in reducing waste and venting, as well as in quality and operational standardization.

At the Santo André plant in Brazil, meanwhile, a project called Fish Eyes uses AI to anticipate changes in raw materials that could affect the quality of the finished PVC.

The company worked with Made in Web as its technology partner for the Electrolyzer Performance and Fish Eyes projects. For the VCM project, it partnered with Optiment, an AspenTech partner.

The Membrane Monitoring project, meanwhile, was developed in-house by Unipar’s digital transformation team.

(The original version of this content was written in Spanish)

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