xDT: High-Fidelity Digital
Twin with Accurate Physical-Virtual Alignment
Built on precise simulations based on actual facility layouts, xDT minimizes physical robot deployment risks, enables immediate deployment of validated operational logic to the shop floor, and helps minimize trial and error during deployment.
Why DAIM’s xDT?
xDT brings DAIM's AI-powered robot orchestration module, xMS, into a virtual environment to create a high-fidelity Digital Twin that accurately reflects real-world operations.
By synchronizing actual facility layouts with operational logic, xDT provides a highly accurate validation environment that helps prevent hardware bottlenecks and interference risks before deployment. Validated operational logic can then be deployed directly to production, minimizing trial and error during deployment and enabling stable automated operations.
Key Capabilities
Digital Twin Bridging Virtual Validation and Real-World Execution
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Key Capabilities
- Logistics Robot Control Algorithms Synchronized with Real-World Operations
- DAIM's logistics robot orchestration platform, xMS, is mirrored in the Digital Twin to ensure operational consistency.
Control logic validated in the virtual environment can be deployed directly to production without modification, maximizing operational stability.
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- Comprehensive Validation for Logistics Robot Deployment
- Evaluate key deployment factors—including required robot fleet size, production KPIs, and operational strategies—before implementation.
Assess deployment feasibility in a virtual environment that mirrors actual operating conditions, reducing deployment risks.
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- Robot Utilization Planning and Route Validation
- Develop and validate robot utilization plans and operational routes based on actual facility layouts for each customer environment.
Validate proposed layouts in a virtual environment to identify and eliminate potential interference risks before deployment.
Proven Impact
Business Value, Proven by the Numbers
Case Studies
Proven Results from Global Manufacturing Leaders
Common Challenges Across Manufacturing
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Challenge
When deploying large-scale AGV, AMR, or OHT systems, it is difficult to predict whether target KPIs such as throughput and lead time can be achieved. There is also insufficient data to determine the optimal robot fleet size and operating policies for each production environment.
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Solution
A virtual logistics automation system replicates the real-world physical environment, operational logic, and communication. The system enables virtual testing under the same conditions as the production environment across a wide range of scenarios, including material flow changes and equipment failures, to identify system stability and limitations before deployment.
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Results
Simulation determined the optimal robot fleet size and specifications required to achieve target KPIs, helping avoid unnecessary investment. Multiple operating policies were evaluated to identify the most efficient operating strategy.
Elevator Manufacturing
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Challenge
Elevator group control algorithms need to be validated quickly and accurately across diverse passenger traffic patterns without testing in actual buildings.
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Solution
Used a 165× accelerated simulation engine to ensure consistent and reproducible results. Designed and validated control strategies using user-defined what-if scenarios, including building configurations, elevator models, and passenger traffic patterns.
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Results
Simulated a full day's operations in just 9 minutes, dramatically reducing algorithm testing and validation time. Performed hundreds to thousands of simulation runs that would be impossible in actual operating environments, thoroughly validating the performance and stability of new control logic.
Battery Manufacturing
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Challenge
Limited physical access to overseas factories required remote analysis and validation of production and logistics processes from Korea to identify optimization scenarios that maximize operational efficiency.
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Solution
Modeled the complex operational logic and physical constraints of core production processes in a Digital Twin, embedding operational logic from MES, ACS, and other production systems into the simulation engine.
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Results
Analyzed overseas factory operations remotely from Korea in real time, validated the feasibility of remote implementation, and used high-fidelity simulations to evaluate multiple operational scenarios, increasing productivity by up to 3.8%.
How it Works
Real-Time Synchronization Between the
Physical Environment and the Digital Twin for Optimal Planning
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- Data Collection & Input (Input Stage)
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- Facility Data Collection : Collect detailed information on facility layouts, production process data, and real-world constraints through interviews with on-site personnel.
- Environment and scenario configuration: Create a digital map of the production layout and generate order scenarios based on the collected data to represent real-world material flows.
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- Digital Twin Synchronization (Digital Twin Stage)
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- xMS (Integrated Logistics Robot Orchestration): Replicate the robot orchestration logic used in the physical environment within the Digital Twin.
- FEX (Factory Emulator for xMS): Creates a Digital Twin of the logistics environment that interacts with xMS in real time, reproducing material flows before physical robots are deployed.
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- Virtual Simulation & Visualization
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- Real-time monitoring: Monitor robot movements, traffic congestion, and equipment status in real time within a 3D virtual environment.
- Code & Log Analysis: Analyze control logic execution, simulation logs, and runtime data in real time to verify system accuracy.
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- KPI Calculation & Results Analysis (Analysis Stage)
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- Analyze simulation results to verify system fidelity and calculate KPIs such as throughput, equipment utilization, and logistics efficiency. Use the results to determine the optimal robot fleet size,
validate operational scenarios, and estimate ROI.
- Analyze simulation results to verify system fidelity and calculate KPIs such as throughput, equipment utilization, and logistics efficiency. Use the results to determine the optimal robot fleet size,
FAQ
Key Questions to Ask Before Deployment
To fully leverage xDT, the xMS logistics robot orchestration platform must be deployed first. xMS enables logistics automation, while xDT maximizes operational efficiency.
A Digital Twin without a clear objective is unlikely to succeed. xDT is designed to maximize the design and operational efficiency of xMS-based logistics automation systems. Contact us to learn more.
Yes. xDT's simulation features are available as a standalone solution called xSIM. If you'd like to start with simulation, xSIM is the ideal starting point.
