Altex Group cuts energy costs by 8% through device-level energy insights | Centrica Business Solutions
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Altex Group cuts energy costs by 8% through device-level energy insights

S2G Energy harnessed Centrica Business Solutions’ Panoramic Power™ wireless sensors and PowerRadar™ to help Altex Group take control of its energy costs.
$843k

Reduction in overall energy costs

53k Tons

Reduction in CO2 emissions

12%

Energy reduction by optimizing compressors

Altex Group is one of Mexico’s most important agro-industrial groups. Its product lines include packed and canned vegetables, frozen fruits, jams and citrus concentrates, with around 70% of its sales coming from the non-domestic market. Thirty percent of its output remains in Mexico, while 50% is exported to the USA and the remaining 20% to Europe and Japan.

Leveraging energy intelligence to control cost and mitigate risks

Due to high energy usage in the agricultural industry, Altex Group’s priorities were to digitize energy consumption data, optimize factory processes and reduce production costs. In 2018, the total energy consumption across Altex Group’s nine production sites surpassed 65,000 MWh. With energy prices rising by up to 70%, Altex Group was looking to make its operations more energy efficient, enabling it to remain competitive in the market.

 

We now have greater efficiency in the use of resources. It is easier to identify and propose specific projects to increase the efficiency of the equipment and our end customers benefit from the reduction of the carbon footprint associated with our products.
Eduardo Arechiga Calzada Operations Director, Altex Group

You can't manage what you don't measure

While Altex Group knew that its refrigeration equipment was the most energy-intensive component of its operations, it did not have the data required to make informed decisions towards reducing or reorganizing its overall energy consumption. At the same time, it was looking to improve its financial planning processes. Previously, energy forecasting was very roughly approximated – a lot of time and resources were spent towards manually capturing information on energy consumption and reconciling energy expenditure across different plants, cost centers, operations and products.

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