FLSmidth is a global engineering company that delivers sustainable productivity to the global mining and cement industries. Cloud Interactive develops a custom machine learning software replaces the standard multiple regression analysis models in the PX-Cal Software, and provides better predictions of raw material demands, predictive maintenance, and optimization of supply chains.
Industry: Mining, Cement
Company Size: 17,000 Employees
Revenue: $3.8 billion USD
Technology: AI, Machine Learning
Advanced Machine Learning Design and Development for Intelligent Mining & Cement Manufacture
Through Cloud Interactive’s machine learning model, this in turn led to better prediction results in the mining and cement business. The advanced ML design was integrated with the client’s legacy platform, and it now provides accurate predictions of raw material demands, predictive maintenance, and optimization of supply chains.
Developed custom solutions in 3 months.
Generated 2 new machine learning algorithms accurately predicting the laboratory test results.
145% increase in prediction accuracy.
Machine learning techniques and deep learning algorithms have become critical for predicting parameters in many fields of science and engineering.
The client came to us for a custom machine learning solution to their existing calibration software that would better predict the elements of mineral processing.
With an in-house data science team, Cloud Interactive combined the machine learning model with vast industrial data for network training.
Through algorithms, we helped FLSmidth produce a more accurate analysis system that would replace its current standard multiple regression analysis model and platform.
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