Maplesoft’s Digital Twin solutions use advanced modeling and simulation tools to create virtual representations of physical assets. These digital twins are connected to real-world data sources, enabling real-time monitoring, predictive analysis, and optimization of manufacturing systems throughout the product lifecycle.

Key Features

Model-Driven Digital Twin Creation Develop high-fidelity, physics-based models of machines and systems using Maplesoft’s MapleSim platform.

• Accurately represent mechanical, electrical, and control systems.
• Integrate with real-world sensor and operational data for real-time feedback.

Simulation and Predictive Analytics Run simulations to predict system behavior and optimize performance before implementing changes in the real world.

• Test scenarios and operating conditions virtually.
• Identify potential failures and maintenance needs in advance.

Integration with Manufacturing Operations Connect digital twins to live manufacturing equipment and processes for continuous monitoring and improvement.

• Enable real-time data feeds from physical assets.
• Support virtual commissioning and system validation.

Support for Product Lifecycle Management (PLM) Apply digital twins across all phases of the product lifecycle, from design and prototyping to operation and maintenance.

• Facilitate design validation, production planning, and asset management.
• Improve decision-making with data-driven insights.

Benefits

Reduced Development Risk Shorten time to market and minimize costly errors by validating designs virtually before physical implementation.

• Detect design flaws early.
• Reduce the need for physical prototypes.

Optimized Performance and Maintenance Enhance operational efficiency and reliability through predictive maintenance and real-time optimization.

• Minimize unplanned downtime.
• Extend equipment lifespan.

Cost Savings and Increased Efficiency Streamline manufacturing processes and improve resource utilization.

• Lower operational costs.
• Achieve faster, more informed decision-making.