Alcoa Improves Operational Efficiency And Asset Reliability With Predictive Maintenance
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With the increasing adoption of asset performance management software in industrial markets during the last five years, recognition of the business potential of predictive maintenance is rising. Alcoa, a global aluminium producer and owner-operator of bauxite mines, has implemented predictive maintenance software to restructure its maintenance programme and practices. The software leverages artificial intelligence and machine learning to anticipate asset failure and send alerts to relevant personnel before failures occur. These advancements have precipitated a 30% increase in Alcoa’s operational efficiency and reduced maintenance costs by 20%.
Table of contentsAsset Failure Prediction Software Helps Alcoa Modernize Its Maintenance Approach
Alcoa Moves From Planned To Predictive Maintenance By Combining AI And Machine Learning
Alcoa Enhances Maintenance Practices And Improves Operational Efficiency By 30% Through Adoption Of Predictive Maintenance Solutions