Alcoa Improves Operational Efficiency And Asset Reliability With Predictive Maintenance

Published 21 July 2020 by Hugo Fuller & Malavika Tohani &
Asset Integrity Asset Performance Management Software Operational Excellence Predictive Maintenance Case Study Market Insight

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Executive Summary

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 contents

Asset 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 

Organisations mentioned

Oracle, OSIsoft, Senseye

About the authors

Hugo Fuller

Senior Analyst
Hugo is a Senior Analyst in the Verdantix Operational Excellence practice. His current research agenda explores the technologies within the industrial asset management software market, with a focus on enterprise asset management software and computerized maintenance management systems. In Advisory, he focuses on go-to-market, thought-leadership and market-sizing work. Prior to joining Verdantix, Hugo worked in PR analytics and studied English at University College London.

Malavika Tohani

Research Director, Operational Excellence
Malavika leads the Verdantix Operational Excellence practice. Her current research agenda focuses on digital technologies for Operational Excellence including digital twins and software solutions for industrial risk and asset management. Malavika has over 15 years’ experience in research and strategy consulting. Malavika previously worked at Frost & Sullivan, managing and delivering advisory projects for clients involving expansion, acquisition, benchmarking and product development strategies. Malavika holds a MSc in Economics from Madras School of Economics.

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