Improving your operation with ANDRITZ Digital Twin Technology

What is a Digital Twin

The ANDRITZ Digital Twin represents an up-to-date digital replica of the physical asset—a process or a piece of equipment. The Digital Twin of a process plant is analogous to an MRI of the human body, providing otherwise invisible insights to assist operations with proactive and consistent decision-making.

These high-fidelity simulation/machine learning models transform the real-time process data into meaningful and actionable steps while following the changes of its physical counterpart. When connected to online plant data, the Digital Twin acts like a performance information tool, like an MRI of the human body.

Modular approach and integration with existing Automation ecosystem

Dashboards with valuable information

The ANDRITZ Digital Twin modular approach offers multiple benefits for meaningful integration depending on customers assets digital maturity. This also makes space for other digital solutions to coexist.

The applications are typically installed on-premises virtual machines within the same OT network, communicating with the plant DCS/PLC/Historian to read/write real-time plant data as an OPC Client.

ANDRITZ also provides the software, services, and process expertise to deploy and integrate Digital Twin solutions into your existing Automation ecosystem.

ANDRITZ Digital Twin solutions for Paper mills

Revolutionizing Paper Mill Operations with Advanced Digital Twins for Enhanced Efficiency and Sustainability

Paper Machine Digital Twin
Tissue Machine Digital Twin
Stock Preparation Digital Twin (Fiber GPS)

Measurable value to customers

At ANDRITZ Pulp and Paper, digitalization is all about measurable results. ANDRITZ Digital Twin delivers tangible improvements across key performance areas, helping plants operate more efficiently, reliably, and profitably.

What you can achieve:

Up to 5% cost reduction

Up to 5% quality losses reduction

Up to 5% productivity increase

Up to 5% operator actions reduction

Up to 3% increase energy efficiency

These improvements are driven by high-fidelity simulation and machine learning models acting as a digital replica of the mill, alongside continuous collaboration between ANDRITZ experts and the mill's teams. All of this aims to optimize process setpoints, anticipate failures before they become incidents, minimize the impact of disturbances, and maximize throughput, consistent product quality, and cost efficiency across the pulp mill.