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Digital Smelter

Reduce energy usage and raw material consumption of your potlines with digital twins for the aluminum smelting process

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Digital Smelter software from GE Digital helps mining and metals optimize production

What is Digital Smelter?

Digital Smelter from GE Digital delivers a complete analysis of all the components within a potline, providing a digital twin model that increases the efficiency of the smelting process and boosts operator productivity by helping to predict potential process anomalies and prescribe actions to optimize smelter operations.

 

Backed by machine learning and advanced analytics, the Digital Smelter technology deploys virtual sensors to deliver near real-time analysis of potline health and the condition of every pot. This modern approach to the smelting process is helping top aluminum companies create sustainable growth in a volatile industry.

 

Transforming aluminum smelting for sustainable excellence

Reduce energy consumption without sacrificing production

Reduce raw material consumption

Optimize the return on pots

Improve pot and potline health

Prevent unplanned potline outages

Our customers tell it best

"With GE’s digital smelter solutions, we are setting a global first for the aluminum industry that will contribute to our operational efficiency and set new benchmarks in the sector.”

Dimitris Stefanidis

CEO, Aluminum of Greece

 

Watch the customer story.

The digital difference maker in smelting operations

Smelter Operations using digital twin technology from GE Digital

Smelter Optimization

Navigate the entire smelter plant down to the pot level to get near real-time visibility into the health and performance of your potlines. At a glance, operators can quickly review all components of the potlines and get detailed insights into pot health and specific energy consumption. When potlines are not running optimally, the smelter optimization capability will prescribe recommendations to help the operator quickly resolve potential process and pot health anomalies before they impact operations.

 

 

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