AI Capabilities in Siemens Software
Below you will find a library of resources related to AI in Siemens Software:
Copilot
Copilot is a powerful AI-driven tool that continues to evolve as it learns from real-world engineering data and usage patterns. By understanding the terminology, workflows, and context that engineers rely on every day, it becomes increasingly effective over time. Embedded directly within the software, Copilot goes beyond answering questions—it proactively surfaces relevant resources, links, and shortcut commands, helping users save time and work more efficiently.
Available in:
- Designcenter X Solid Edge
- Designcenter X
- NX X for Manufacturing
Resources:
Copilot: Solid Edge
Copilot: Designcenter
Performance Predictor
Performance Predictor in Designcenter uses intelligent data analysis insights to help engineers understand how designs and manufacturing processes are likely to perform before issues occur. By learning from simulation results, operational data, and historical project trends, it can identify potential bottlenecks, performance risks, and optimization opportunities earlier in the workflow. Embedded directly within Designcenter, Performance Predictor helps teams improve product reliability, reduce rework, and make faster, more confident engineering decisions.
Available in:
- Designcenter X
- Designcenter
- NX X for Manufacturing
Resources:
Performance Predictor: Designcenter
Command Prediction
Command Prediction in Designcenter X Solid Edge and Designcenter X uses AI to learn your design workflows and anticipate the tools you will need next. By surfacing relevant commands based on your current task and usage patterns, it reduces time spent searching through menus and helps engineers stay focused on designing. Embedded directly within the Designcenter and Designcenter Solid Edge interfaces, Command Prediction creates a faster, smarter, and more intuitive design experience.
Available in:
- Designcenter X Solid Edge
- Designcenter Solid Edge
- Designcenter X
- Designcenter
- NX X for Manufacturing
Resources:
Command Prediction: Solid Edge
Command Prediction: Designcenter
AI Drawings
Available in:
- Designcenter X Solid Edge
- Designcenter Solid Edge
Resources:
AI Drawings: Solid Edge
Magnetic Snap
- Designcenter X Solid Edge
- Designcenter Solid Edge
Resources:
Magnetic Snap: Solid Edge
Selection Prediction
Selection Prediction intelligently recognizes patterns and relationships within your model to dramatically speed up the selection process. Instead of manually clicking dozens or even hundreds of similar faces, holes, edges, or components, engineers can make a single selection and allow the system to predict and gather related geometry automatically. This is especially valuable when working with mirrored features, repetitive patterns, fastener groups, or consistent design elements across large assemblies. By reducing repetitive manual work, Selection Prediction helps designers stay focused on engineering decisions, improve workflow efficiency, and accelerate model preparation for downstream operations such as editing, simulation, or manufacturing.
Available in:
- Designcenter X
- Designcenter
Resources:
Selection Prediction: Designcenter
Select Similar Components
Select Similar Components streamlines assembly management by instantly identifying and selecting components that share matching characteristics, geometry, or attributes within a design. Instead of manually searching through complex assemblies, engineers can quickly isolate identical or comparable parts with a single action, making it easier to apply edits, assign properties, analyze groups, or prepare models for manufacturing. Whether working with repeated hardware, patterned assemblies, or standardized components, Select Similar Components reduces repetitive selection work, improves consistency across the design process, and helps teams work more efficiently in large-scale assemblies.
Available in:
- Designcenter X
- Designcenter
Resources:
Select Similar Components: Designcenter
Select Similar Faces
Select Similar Faces provides intelligent, real-time recognition of matching geometric regions across parts and assemblies, allowing engineers to quickly locate, select, and manipulate similar faces with minimal effort. Instead of manually identifying repeated features one by one, users can instantly find matching regions across multiple components, dramatically reducing repetitive selection work and improving workflow efficiency. Engineers can also create custom validation checks for similar regions and build reusable libraries of commonly searched face conditions, making it easier to standardize design verification processes across projects. By accelerating precise region recognition and enabling Design for Manufacturability (DFM) validation on repeated features, Select Similar Faces helps improve product quality, reduce errors, and streamline engineering operations with fewer clicks and faster decision-making.
Available in:
- Designcenter X
- Designcenter
Resources:
Select Similar Faces: Designcenter
Auto Dimension
Auto Dimensioning in Designcenter Solid Edge automatically generates PMI dimensions for part and sheet metal models, ensuring features are fully defined for manufacturing. It applies consistent tolerances and supports key geometry like holes, faces, slots, and cylinders to reduce manual detailing. Built-in checking tools also identify over- or under-constrained models with clear visual feedback, improving accuracy and design efficiency.
Available in:
- Designcenter X Solid Edge
- Designcenter Solid Edge
Resources:
Auto Dimension: Solid Edge
PMI Annotation Plane and Model View Prediction
PMI Annotation Plane and Model View Prediction uses domain-specific machine learning to intelligently automate the definition and organization of Product Manufacturing Information (PMI) during the authoring process. By leveraging processed training data and advanced in-house machine learning models, or by utilizing out-of-the-box deployment, the system can automatically predict and assign the appropriate PMI annotation planes and model view specifications for each PMI object. This enables engineers to generate structured, standards-based PMI faster and with greater consistency across designs. By reducing manual setup and minimizing the need for post-process cleanup, PMI Annotation Plane and Model View Prediction helps accelerate documentation workflows, improve annotation quality, and deliver more predictable results aligned with established engineering best practices.
Available in:
- Designcenter X
- Designcenter
Resources:
PMI Annotation Plane and Model View Prediction: Designcenter
NX X for Manufacturing – CAM
Machining Recommendations
Machining Recommendations in NX X acts as a smart assistant, analyzing your part’s geometry, material, and your company’s best practices to suggest optimal machining operations and tools. It intelligently scans features like holes and pockets, recommending suitable operations (e.g., drilling, milling) and appropriate cutting tools from your library. This capability can also suggest initial cutting parameters, leveraging your established manufacturing knowledge. Its core benefits include significantly reducing CAM programming time, improving consistency across parts, and empowering both new and experienced users by offering expert advice.
Feature-Based Machining (FBM)
Feature-Based Machining (FBM) elevates intelligent programming by automatically generating entire machining programs. It starts with Automatic Feature Recognition (AFR), where NX X identifies and classifies manufacturing features (like holes, pockets, and slots) directly from the 3D CAD model, understanding their shape and intent. FBM then applies predefined, customizable “machining rules” or “process templates” to dictate how each feature should be machined. This leads to the automated generation of machining operations, optimized tool paths, and even NC code for your specific machine tools. FBM’s primary advantages are massive increases in automation, faster turnaround times, reduced errors through standardized processes, and scalability for parts with recurring features.
How They Work Together
Machining Recommendations and FBM often complement each other. Recommendations can provide initial suggestions for complex or novel features where FBM rules might not yet exist, while FBM excels at automating standardized processes for common features. Insights from Recommendations can also help refine and build your FBM knowledge libraries. Together, these capabilities streamline CAM programming, minimize manual effort, enhance consistency, and ultimately accelerate the production of high-quality parts.
Available in:
- NX X for Manufacturig
Resources:
Topology Optimization
Topology Optimization helps engineers begin the design process with performance-driven insight by using simulation results to guide geometry creation and refinement. Instead of designing first and validating later, functional requirements such as strength, stiffness, weight, and load conditions directly influence how material is distributed throughout the part. This allows engineers to develop highly efficient, lightweight designs that maintain structural integrity while reducing unnecessary material usage and overall ecological impact. By providing design guidance based on real load paths, Topology Optimization enables smarter engineering decisions early in development and helps create components optimized for both additive and traditional subtractive manufacturing methods. The result is lower manufacturing costs, simplified assemblies with fewer parts, and innovative designs that deliver improved performance with greater production efficiency.
Available in:
- Designcenter X
- Designcenter
Resources:
Topology Optimization: Designcenter