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Standards Development
This Technical Specification defines a descriptor-driven method to evaluate shape fidelity between a physical item and its digital twin (DTw) representation.
It specifies:
- Required terminology, data models, and computation steps for using 3D shape descriptors to quantify 3D shape similarity.
- Taxonomy of descriptor classes.
- Conformance requirements for metric calculation and reporting.
Out of scope: Predictive simulation results (CFD/FEM) and non-geometric fidelity scoring such as motion or performance.
Organizations increasingly rely on digital twins to validate that as-built products conform to their asdesigned intent. Current practice is fragmented: teams use proprietary viewers, ad-hoc screenshot overlays, or model-specific neural pipelines that are difficult to reproduce and audit. There is no widely accepted, training-free method that combines 3D shape descriptors for fidelity metrics to compare evidence from CAD meshes, 3D scans/point clouds, and photographs in a consistent, vendor-neutral way.
This deliverable addresses that gap by standardizing:
- Descriptor spaces for 3D shape and view-based comparisons that are independent of object category or training data.
- Map descriptor properties (invariance, robustness, computational cost) to DTw fidelity requirements.
Expected value to stakeholders:
- Repeatability and auditability: Repeatable shape similarity scoring grounded in established 3D descriptor literature.
- Quality and cost impact: Earlier detection of deviations, reduced rework, and clearer acceptance criteria across the supply chain.
- Harmonize commonly used shape deviation measures with descriptor-based scoring for consistent reporting.
This proposal complements emerging DTw standardization (e.g., ISO/IEC 30138, ISO 24464ed2 activity on fidelity concepts) by providing a shape-descriptor method specifically for 3D shape fidelity.
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