CAD Model Validation for Simulation and Manufacturing: Ensuring Digital Data Integrity with CADIQ

In 2023, an undetected CAD modeling error cost a European aircraft manufacturer over €1.2 million. The geometric incompatibility between two major components only became apparent during physical assembly, resulting in a 3-month production delay. This situation could have been avoided through a rigorous digital validation process. According to a recent study, nearly 30% of CAD models used in production contain geometric anomalies that could compromise their use in simulation or manufacturing, generating significant hidden costs in the industrial digital chain.

Geometric validation of digital models represents a strategic issue for manufacturing companies today. In a context where design, simulation, and manufacturing processes are increasingly integrated, the quality and integrity of 3D data become critical to ensure the reliability of numerical analyses and the conformity of produced parts.

Table of contents

• Fundamentals of validation for simulation and manufacturing
• Typology of critical geometric defects
• Effective validation methodologies
• Industrial validation standards and norms
• Measurable benefits of rigorous validation
• Sectoral case studies
• CADIQ: advanced solution for CAD model quality verification

Fundamentals of validation for simulation and manufacturing

Validation for simulation and manufacturing constitutes a systematic process of evaluating 3D digital models to ensure their compliance with technical requirements for finite element analyses and manufacturing processes. This approach is distinguished from simple visual verification by its methodical and quantifiable nature.

It is essential to differentiate three often confused concepts:

• Verification: Technical control of the intrinsic properties of the model (absence of free edges, surface continuity, etc.)
• Validation: Confirmation that the model meets the functional requirements for its intended use
• Certification: Formal attestation by an authority that the model satisfies specific standards

The geometric quality of a CAD model directly influences several critical aspects of the product development cycle:

The economic stakes are considerable: errors detected late in the development cycle can cost up to 100 times more to correct than those identified in the design phase. For an industrial company, early model validation therefore represents a strategic investment rather than a cost.

Typology of critical geometric defects

Geometric defects compromising the use of CAD models in simulation or manufacturing can be classified into several distinct categories. Their precise identification allows for the adoption of targeted and effective correction strategies.

Geometric integrity defects

These anomalies affect the mathematical consistency of the model and generally compromise any subsequent use:

• Free edges: Discontinuities in the model envelope where a face is not properly connected to adjacent faces
• Degenerate faces: Surfaces whose area is mathematically invalid or close to zero
• Degenerate solids: Volumes whose value is negative or aberrant
• Over-used edges: Segments shared by more than two faces, creating self-intersections

These defects generally prevent any subsequent operation such as meshing for simulation or G-code generation for machining.

Topological structure defects

These problems concern the organization of the elements constituting the model:

• Embedded solids: Overlapping volumes creating ambiguities of interpretation
• Superimposed shells: Duplicate open surfaces at the same coordinates
• Non-tangent faces: Tangency discontinuities between adjacent surfaces
• Non-parametric models: Geometries defined without exploitable construction history

These defects generally compromise subsequent modifications and can cause problems during format conversions.

Manufacturability defects

These characteristics, although mathematically correct, make physical manufacturing difficult or impossible:

PMI/MBD annotation defects

In the context of Model-Based Definition (MBD), semantic annotation problems can compromise interpretation:

• Non-associative annotations: PMI without links to corresponding geometric entities
• Contradictory dimensions: Incompatible nominal values on the same feature
• Inconsistent datum references: Poorly defined or conflicting reference systems
• Incomplete tolerancing: Absence of critical dimensional information

Mastering these defects is particularly critical in the aerospace and automotive industries, where digital chains are highly integrated and where each iteration involves multiple actors and systems.

Effective validation methodologies

Implementing an effective geometric validation strategy is based on adopting methodologies adapted to the industrial context and the specific requirements of business sectors.

Proactive versus reactive approaches

Validation methodologies are mainly distinguished by their positioning in the workflow:

• Proactive validation: Integrated directly into the design process, allows identification and correction of problems before they propagate
• Reactive validation: Applied to models already created, generally during transfer phases between departments or organizations

The proactive approach, although more demanding in terms of process organization, offers a significantly higher return on investment by substantially reducing iterations.

Integration into the workflow

Effective validation is strategically inserted into the product development cycle:

1. Design validation: Verification of models created by designers before sharing
2. Transfer point validation: Systematic control during changes of environment or team
3. Pre-simulation validation: Specific analysis ensuring compatibility with analysis tools
4. Pre-manufacturing validation: Verification of critical characteristics for manufacturing processes

The systematization of these controls allows for complete traceability of data quality throughout the product lifecycle.

Format conversion validation

Interoperability between CAD systems constitutes a major challenge requiring particular attention:

The ideal methodology combines automated controls based on predefined rules and targeted manual validations for critical characteristics identified upstream of the project.

Industrial validation standards and norms

The industry has developed several standards to frame and normalize geometric validation processes. These references allow the establishment of objective criteria common to contractors and subcontractors.

SASIG PDQ (Strategic Automotive product data Standards Industry Group)

Initially developed for the automotive industry, the SASIG PDQ (Product Data Quality) standard defines a comprehensive set of quality criteria for CAD models:

• Classification of defects into severity categories (critical, major, minor)
• Definition of more than 150 types of identifiable technical defects
• Quantifiable metrics for each type of defect
• Certification protocols and standardized reports

This standard is particularly relevant for data exchanges in international automotive supply chains.

VDA 4955

The German VDA 4955 standard, developed by the German automotive manufacturers' association, defines:

• Quality criteria for CAD data in automotive manufacturing
• Specific requirements for model exchange between manufacturers and suppliers
• Format conversion validation procedures

LOTAR (LOng Term Archiving and Retrieval)

The LOTAR standard, particularly important in aerospace and defense, defines requirements for long-term archiving of digital data:

• Validation criteria to ensure model durability
• Protocols for verifying geometric and semantic integrity
• Certification methods for regulatory archiving
• Validation of validation properties for neutral formats

ISO 10303 (STEP)

The ISO 10303 standard, known as STEP (Standard for the Exchange of Product Model Data), incorporates specifications for data exchange validation:

• AP 242: Specification for managing annotated 3D models (MBD)
• Validation protocols for geometric properties and PMI
• Standardized mechanisms for comparison between native and derived models

The adoption of these standards allows companies to implement objective and reproducible validation processes recognized by all industrial stakeholders.

Measurable benefits of rigorous validation

The implementation of a systematic CAD model validation process generates quantifiable benefits at several levels of the industrial organization.

Reduction of revision cycles

Early detection of geometric problems eliminates many iterations in the development cycle:

• 30% to 50% decrease in the number of revisions related to geometric quality issues
• Significant reduction in delays between initial design and final validation
• Acceleration of approval cycles between departments and organizations

Optimization of direct and indirect costs

The financial impact of rigorous validation is manifested through several indicators:

Digital chain reliability

Beyond direct savings, systematic validation strengthens the overall integrity of the digital process:

• Increased confidence in the results of numerical simulations
• Reduced risks associated with decisions based on defective data
• Complete traceability of model quality throughout the lifecycle
• Standardization of practices between different teams and sites

This increased reliability translates into better predictability of deadlines and costs, facilitating strategic planning and reducing production contingencies.

Sectoral case studies

The impact of validation methodologies can be observed through several concrete cases in different industrial sectors.

Aerospace: MTU Aero Engines

The German engine manufacturer MTU Aero Engines deployed a systematic process for validating NX models and STEP conversions for its critical turbine components.

Results measured after 18 months of implementation:

• 83% reduction in geometric non-conformities detected in the manufacturing phase
• Acceleration of certification cycles from 12 weeks to 8 weeks
• Estimated savings of €1.2 million on one engine program

The key to this success was the integration of validation from the earliest design phases, rather than in final control.

Automotive: Ford Motor Company

Ford implemented a Six Sigma Quality validation strategy for its CAD models, with a particular focus on conversion between native formats and neutral formats.

The structured approach allowed:

• Early identification of more than 4,500 potentially critical defects in one year
• 72% reduction in time spent on modeling rework
• Significant improvement in collaboration with suppliers thanks to more reliable models

Defense: NAVAIR (Naval Air Systems Command)

The transition to Model-Based Definition (MBD) for American naval aviation programs required the implementation of a rigorous model validation process including geometry and PMI annotations.

Documented benefits:

These case studies demonstrate that investment in structured validation processes generates a significant return, particularly when integrated into a global digital transformation strategy.

CADIQ: advanced solution for CAD model quality verification

Facing the challenges of validation for simulation and manufacturing, CADIQ stands out as a comprehensive technical solution enabling the automation and standardization of geometric validation of CAD models.

Main features

CADIQ offers a comprehensive set of tools dedicated to validating digital models:

• In-depth geometric analysis: Detection of more than 150 types of potential technical defects, grouped by categories (integrity, exchange, simulation, etc.)
• Conversion validation: Comparison between native and derived models to ensure geometric and functional equivalence
• Revision control: Precise identification of changes between successive versions of a model
• Complete PMI/MBD support: Analysis of semantic and graphic annotations to ensure their consistency
• Interactive reports: Detailed documentation of validation results with 3D visualization

Technical architecture

The modular architecture of CADIQ is built around several integrated components:

Multi-format compatibility

CADIQ supports a wide range of native and neutral formats, ensuring its integration into heterogeneous environments:

• Native CAD systems: CATIA V5/V4, NX, Creo Parametric, Inventor, SOLIDWORKS, Solid Edge
• Neutral formats: STEP, JT, Parasolid, ACIS, IGES, QIF, 3D PDF (PRC and U3D)

This extended compatibility allows validation of model integrity at each conversion stage in complex digital chains.

Specific diagnostics

The analytical capabilities of CADIQ cover all categories of potential defects:

• Integrity diagnostics: Free edges, degenerate faces, invalid solids, etc.
• Tooling diagnostics: Thin walls, sharp angles, narrow spaces, non-standard radii
• Structure diagnostics: Hidden entities, broken constraints, inconsistent model properties
• Simulation diagnostics: Tiny edges, fragmented surfaces, narrow regions
• Annotation diagnostics: Non-associative PMI, conflicting dimensions, missing notes
• Comparison diagnostics: Geometric modifications, feature additions/deletions

Industrial applications

The CADIQ solution addresses several critical use cases in industrial processes:

For industrial organizations engaged in a digital transformation process, CADIQ constitutes an essential link to guarantee the integrity and reliability of digital models throughout their lifecycle, from initial design to manufacturing and long-term archiving.

Conclusion

The validation of CAD models for simulation and manufacturing represents a critical process for manufacturing industries today. The economic and technical stakes are considerable: reduction of development costs, acceleration of innovation cycles, reduction of scrap, and overall improvement in quality.

The adoption of a structured validation methodology, supported by specialized tools such as CADIQ, allows companies to secure their digital chain and fully exploit the potential of advanced design, simulation, and manufacturing technologies.

In an industrial context where the exploitation of digital data is becoming a determining factor of competitiveness, investment in the geometric quality of models is no longer an option, but a strategic necessity. Organizations that implement rigorous geometric validation processes benefit from a significant competitive advantage in terms of responsiveness, quality, and cost control.