Rueil-Malmaison, Fra--(뉴스와이어)--Schneider Electric, the leader in the digital transformation of energy management and automation, has launched the latest solution to its EcoStruxure™ Plant Advisor platform specifically for the mining and cement industries. EcoStruxure™ Plant Advisor - Process Intelligence uses Artificial intelligence (AI), Industrial Internet of Things (IIoT), and an open platform philosophy to improve sustainability and operational effectiveness in mining and cement enterprises.

These industries are under increased pressure to adapt process workflows to reduce their carbon footprint, while also increasing throughput and optimizing value chain efficiency. According to McKinsey, mining alone is responsible for 4-7% of greenhouse gas (GHG) emissions globally, with about half coming from the comminution process and the other half from the fleet.

Schneider Electric, named the world’s most sustainable corporation in 2021 by Corporate Knights Global 100 Index, has developed an open, scalable, and natively cybersecure solution to support data-driven, multi-site operations, providing a range of benefits. From real-time AI-based, application-specific analytics to optimize (sub) processes, to a service bureau expert function able to determine the root causes of (potential) issues, EcoStruxure™ Plant Advisor - Process Intelligence directly addresses the key challenges of sustainability and efficiency in mining and cement enterprises.

EcoStruxure Plant Advisor - Process Intelligence helps to:

· Improve asset and process efficiency - Targeting areas with payback time under one year

· Empower the workforce - Through the reporting function, incidents can be resolved 2-4x faster

· Implement an agile value chain - Productivity improvements of up to 5% have been seen in pilot projects

Plant controllers can now simultaneously manage multiple control variables to optimize the plant’s performance. EcoStruxure Plant Advisor - Process Intelligence goes beyond a standard business intelligence (BI) dashboard by incorporating self-learning to recommend appropriate actions to help optimize a process. As a result, mining and cement plants can improve their overall equipment effectiveness (OEE) and water and energy consumption, while also increasing throughput.

Rob Moffitt, President of Mining, Minerals and Metals, Schneider Electric, said “We are delighted to incorporate Process Intelligence within our EcoStruxure™ Plant Advisor platform. We have a strong track record of working with our customers to deliver tangible results through solutions and services in mining, minerals and metals operations. Process Intelligence represents the next generation of digital tools for the industry.”

“We are constantly striving to develop a set of valuable and repeatable process models that can be used to predict and improve future process performance in key markets like mining or cement. The industry is striving to meet sustainability targets, and this solution is designed specifically to help mining and cement companies meet those challenges,” Moffitt continued.

About Schneider Electric

Schneider’s purpose is to empower all to make the most of our energy and resources, bridging progress and sustainability for all. We call this Life Is On.

Our mission is to be the digital partner for Sustainability and Efficiency for our clients.

We drive digital transformation by integrating world-leading process and energy technologies, end-point to cloud connecting products, controls, software and services, across the entire lifecycle, enabling integrated company management, for Industry but also do this for homes, buildings, data centers, and infrastructure.

We are the most local of global companies. We are advocates of open standards and partnership ecosystems that are passionate about our shared Meaningful Purpose, Inclusive, and Empowered values.

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Related resources:

· Blog: Process intelligence solutions help mines improve sustainability and operational effectiveness

· Whitepaper: Improve sustainability by applying AI and IIoT to optimize mining processes