Artificial Intelligence solutions and AI use cases | Schneider Electric Global

Artificial intelligence is a vital part of our solutions that address business challenges. We deliver AI-based solutions leveraging our EcoStruxure^TM architecture and platform to our four end markets — buildings, data centers, infrastructure, and industry.

AI inside our solutions

Industry

AI enables the management of critical quality parameters, stock management, automated visual inspection, industrial safety, and “self-healing” supply chain.
Building

AI is embedded in our thermal model, HVAC, gH2 flow, electrical load management, and building automation solutions.
Data center

AI is used in our solutions encompassing smart cooling, live sensor data, predictive analytics, and smart alarms in data centers.
Infrastructure

AI makes predictive maintenance possible with anomaly detection for resiliency in infrastructure.
Microgrid

AI plays a crucial role in electrical demand and supply management to empower microgrids.
Renewables and EV charging

AI empowers our customers to make data-based buying and selling decisions and manage demand peaks efficiently.

Industry

AI enables the management of critical quality parameters, stock management, automated visual inspection, industrial safety, and “self-healing” supply chain.

Building

AI is embedded in our thermal model, HVAC, gH2 flow, electrical load management, and building automation solutions.

Data center

AI is used in our solutions encompassing smart cooling, live sensor data, predictive analytics, and smart alarms in data centers.

Infrastructure

AI makes predictive maintenance possible with anomaly detection for resiliency in infrastructure.

Microgrid

AI plays a crucial role in electrical demand and supply management to empower microgrids.

Renewables and EV charging

AI empowers our customers to make data-based buying and selling decisions and manage demand peaks efficiently.

Featured AI-based solutions for customers

EcoStruxure Resource Advisor

A solution to manage your energy and sustainability footprint. It aggregates all cross-enterprise energy and sustainability data in a single, cloud-based platform and transforms it into actionable insights.

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EcoStruxure Microgrid Advisor

A cloud-based solution that allows you to dynamically control on-site energy resources and reduce CO₂ emissions. It seamlessly connects to your distributed energy resources to forecast and optimize how and when to consume, produce, and store energy.

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EcoStruxure Autonomous Production Advisor

An open platform that allows you to deploy and manage Machine Learning-based applications at the industrial edge. It leverages existing automation and control architecture and enables real-time analytics to eliminate latency, bandwidth, and connectivity constraints.

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Our AI success stories and testimonials

Blackstone

The Blackstone Group^TM, one of the world’s largest private equity groups, uses EcoStruxure Resource Advisor to track sustainability progress.

Key highlights:

Tens of millions of dollars in energy savings.
15% reduction in CO₂ emissions.
20 portfolio companies tracked.

Read the success story

Oil and gas company

Our customer needed to capture expertise from their senior operators and apply it to more assets.

Key results with EcoStruxure Autonomous Production Advisor:

13% increase in production.
34% reduced energy consumption.
Reduced frequency of abnormal events.
Extended equipment lifetime.
Increased accuracy of event detection through continuous training of the machine-learning models by experts.

AI solutions at Schneider Electric

Jo Virtual Agent is an AI-powered chatbot designed to help you find the best self-service support on Schneider Electric online platforms in just a few clicks. When needed, Jo will seamlessly connect you with our live agents, providing all information from your chat history.

At Schneider Electric, we have customer care centers that receive around 7.5 million questions (tickets) a year from our customers. Until now, a person analyzed the ticket to guide the request (a question on price, product range, connected offers, etc). This first step is now automatically done thanks to AI. AI improves the quality of service, the user experience, the execution of projects, and of course, significantly reduces costs. Our employees also have more time to focus on activities related to customer relations that are less tedious and more valuable.

Virginia AI Sales Assistant is a connected toolset that boosts sales efficiency with valuable data-driven insights and actionable alerts. This AI assistant offers custom insights such as product recommendations, visits, and opportunity reminders, or product end-of-life alerts. Our sales teams can access customer and product information and report visits quickly, and save up to 3 hours weekly.

Our “self-healing” supply chain platform uses adaptive machine learning, big data, and IoT to optimize performance-related parameters in real-time, suggests ways to improve financial and operational performance, and predicts business outcomes. Key benefits:

6-day reduction in day-in inventory, resulting in a 10% overall inventory decrease.
Average 15% yield improvement on specific manufacturing lines.
Over €100 million generated in value and productivity improved by €30 million.
Delivery time reduced by 6 days.

Schneider Electric's data and Artificial Intelligence patents

Jon A. Bickel, Johannes Menzel (2020). Systems and Methods for Monitoring Energy-Related Data in an Electrical System.
Johannes Menzel, Jon A. Bickel (2022). Systems and Methods for Analyzing Alarms to Characterize Electrical System Issues.

Johannes Menzel, Jon A. Bickel (2022). Systems and Methods for Reducing Alarm Nuisance Behaviors in an Electrical System.
Marcel Chevalier, Didier Van Dooren (2022). Control Method of an Electrotechnical Device.

Marcel Chevalier, Laurent Buchsbaum (2021). Determination of a Reliability State of an Electrical Network.

Venanzio Ferraro, Massimo Secci, Diego Alberto (2021). Electrical Apparatus Thermal Monitoring.
Bhaskar Sinha, Venkatesh Jagannath, Amitabha Bhattacharyya, Ashish Patil, Sameer Kondejkar (2020). Automatic Extraction of Assets Data from Engineering Data Sources.

Bhaskar Sinha, Padmaja Bodanapu, Ashish Patil, Sameer Kondejkar, Rajkumar Krishnan (2020). Automatic Extraction of Assets Data from Engineering Data Sources for Generating an HMI.

Bartosz Boguslawski, Reynaldo Espana Rey, Giorgio Colangelo, Matthieu Boujonnier, Loryne Bissuel Beauvais, Fahd Saghir, Jacky Hoareau (2020). Autonomous Failure Prediction and Pump Control for Well Optimization.

Bartosz Boguslawski, Matthieu Boujonnier, Loryne Bissuel Beauvais, Fahd Saghir, Helenio Gilabert (2020). Well Site Machine Learning Based Analytics.

Fahd Saghir, Xavier Pasbeau, Bartosz Boguslawski, Matthieu Boujonnier, Loryne Bissuel Beauvais (2020). Well Site Machine Learning Based Predictions.
James W. VanGilder, Stuart M. Sheehan, Michael B. Condor (2021). Systems and Methods for Determining Liquid Cooled Architectures in an IT Room.

Alain Dutrey, Thomas Devos, François Malrait (2021). Backspinning Motor Control.

Al Kassem Jeba, Thomas Devos (2021). Variable Speed Drive and Torque Sensor.

Kamal Ejjabraoui (2021). Centrifugal Pump Operation.

Nicolas Henwood, Al Kassem Jebai, Vincent Ravier (2021). Electric Motor Control.

Thomas Devos, François Malrait (2021). Motor Soft-Starter Control.

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