A Digital Twin-Based Approach with a System-Agnostic Integration Method to Enable Intelligence Capabilities and What-If Scenario Orchestration

In Industry 4.0, digital twins are transforming decision-making, operations optimization, and outcome prediction. However, implementing digital twins remains challenging, particularly in managing diverse intelligence capabilities defined by the Digital Twin Consortium’s Periodic Table of Capabilities, including orchestration, alerts, analytics, simulation, and AI. Current technology landscape lacks open-source solutions for designing, orchestrating, and executing “what-if” scenarios, as well as real-time monitoring, decision support, and interoperability.We propose an open-source framework addressing diverse intelligence capabilities, with a focus on openness, interoperability, and integration. Building on prior work in core data management using the Asset Administration Shell standard, we detail its approach, architecture, implementation, and a generic integration method applied to three industrial use cases to validate the framework’s feasibility and potential.