Understanding Digital Twins
A digital twin is a virtual replica of a physical object, process, or system that simulates its behavior, characteristics, and performance in real-time. It combines data, models, and analytics to create a comprehensive representation enriched with artificial intelligence capabilities. This allows for a holistic view of industrial assets or processes, enabling better decision-making and optimization.
Key Components of Digital Twins
Digital twins rely on continuous data streams from various sources, leveraging AI and machine learning models for analysis. The collected data is integrated and transformed into dynamic models that accurately represent physical assets or processes. Role-based visualization provides tailored access to data for different stakeholders, enhancing collaboration and efficiency.
AVEVA's Approach to Digital Twins
AVEVA offers an 'intelligent twin' throughout the industrial lifecycle, starting from conceptual design to operations and optimization. With seamless integration of engineering and operations data, combined with IoT devices and AI algorithms, AVEVA's platform delivers a consolidated view of equipment, systems, and assets. This facilitates decision-making, collaboration, and efficiency across industrial organizations.
Operationalizing Digital Twins
By gathering data from automation systems, process equipment, and external sources, digital twins provide a comprehensive view of assets and processes. First principle modeling and analytics enhance this data, providing deeper insights and enabling predictive capabilities. Real-time synchronization and simulation ensure accuracy and allow for proactive decision-making and optimization.
Applications Across the Industrial Lifecycle
Digital twins offer benefits throughout the industrial lifecycle, from design and build phases to operations and optimization. They improve visibility, control, productivity, and sustainability while reducing rework and unnecessary work. By leveraging AI and machine learning, organizations can optimize their operations and drive continuous improvement.