Ensuring Data Compliance: Independent Validation Methods for CAD Migrations

In the constantly evolving industrial world, the migration of Computer-Aided Design (CAD) systems represents a major strategic challenge for companies concerned with maintaining their technological competitiveness. This complex process, consisting of replacing an existing CAD system with a more recent solution, exposes organizations to considerable risks in terms of technical data integrity. A recent study reveals that more than 60% of CAD migration projects encounter significant problems related to the loss of critical information or unintentional alterations of 3D models. Faced with these challenges, CAD migration validation emerges as an essential discipline to secure this digital transformation process.

The precision and reliability of CAD data constitute the very foundation of modern design, simulation, and manufacturing processes. A tiny geometric deviation, sometimes invisible to the naked eye, can lead to disastrous consequences: defective parts, production delays, significant cost overruns, and potentially product recalls. How then can we guarantee the absolute integrity of data during migration between heterogeneous CAD systems?

Table of contents

• The fundamentals of CAD migration
• The critical challenges of CAD migration
• Migration validation: a strategic necessity
• Effective validation methodologies
• CADIQ: complete solution for CAD migration validation
• Integration of validation in a complete migration process
• Best practices and recommendations

The fundamentals of CAD migration

CAD migration refers to the planned process of replacing an existing design environment with a new system, while preserving the entirety of the company's digital heritage. This transition can be motivated by various factors: technical obsolescence of current tools, evolution of business needs, search for advanced functionalities, harmonization of platforms following a merger or acquisition, or optimization of license and maintenance costs.

In 2025, this process takes on a strategic dimension for industrial companies facing an acceleration of innovation cycles and increasing product complexity. CAD migration is no longer limited to a simple file transfer but is part of a global transformation of the company's digital ecosystem, impacting the entire product development value chain.

Three main methodological approaches characterize CAD migration strategies:

• BREP conversion (Boundary Representation): this approach focuses on the pure geometry of the model without preserving the construction history. Models are converted at the level of their final mathematical representation (surfaces, edges, vertices). Fast and robust, it generally guarantees good geometric fidelity but sacrifices design intelligence.
• Parametric migration: it aims to preserve not only the geometry but also the entire construction history, including functions, constraints, and parametric relationships. More complex, this approach allows preserving design intent and facilitates subsequent modifications.
• Remastering: hybrid or manual approach consisting of partially or completely recreating models in the target system, relying on semi-automated techniques or on the expertise of specialized operators.

Each of these methods presents a different balance between fidelity, usability, and required resources. The choice of approach generally depends on the specific objectives of the project, the criticality of the data, and the available resources.

The critical challenges of CAD migration

CAD migration confronts organizations with numerous technical and organizational challenges that could compromise the integrity of their digital heritage. A thorough understanding of these risks is essential to implement an effective validation strategy.

The first major challenge concerns the preservation of the geometric integrity of models. Different CAD systems use distinct mathematical kernels to represent and manipulate geometry, leading to sometimes divergent interpretations of the same entities. These discrepancies can manifest as subtle deviations: slightly displaced surfaces, modified fillet radii, or misaligned holes. These imperfections, often imperceptible to the naked eye, risk generating critical problems downstream, particularly during manufacturing or assembly.

The second challenge relates to the preservation of design intelligence. Beyond simple geometry, modern CAD models encapsulate a considerable amount of high-value information: construction history, parametric relationships, assembly constraints, PMI (Product Manufacturing Information) annotations, and various metadata. These elements constitute the true value of digital models, facilitating their modification, reuse, and adaptation. Their loss during migration can significantly degrade the productivity of design teams.

The third challenge concerns the impact on downstream processes. CAD data generally feed numerous critical applications: numerical simulation, computer-aided manufacturing (CAM), quality control, technical documentation. An imperfect migration can disrupt this digital chain, generating costly inefficiencies and significant delays.

Finally, the organizational dimension should not be underestimated. A CAD migration generally involves a transition period where multiple systems coexist, requiring robust exchange processes and adequate team training.

The financial impact of these challenges can be considerable:

• Direct costs related to manual correction of defective models
• Opportunity costs resulting from market launch delays
• Potential non-quality costs (scrap, repairs, recalls)
• Disruption of development processes and loss of productivity

A study conducted in the aeronautical sector revealed that a poorly managed CAD migration can generate additional costs representing up to 30% of the initial project budget, not to mention the long-term impacts on the company's competitiveness.

Migration validation: a strategic necessity

Faced with the challenges and risks inherent to CAD migration projects, implementing a structured validation approach stands as a strategic imperative. CAD migration validation is defined as the set of processes, methods, and tools to verify and ensure that converted models retain all the essential characteristics of source models.

Unlike empirical approaches based on cursory visual checks, rigorous validation relies on objective and quantifiable criteria. This scientific approach addresses several fundamental objectives:

• Guarantee the geometric accuracy of converted models
• Verify the preservation of parametric functionalities (when applicable)
• Ensure compliance with specific business requirements
• Identify anomalies early to optimize their correction
• Establish complete traceability of the migration process
• Provide formal certification of the quality of converted models

The importance of this validation manifests at several levels of the organization. For technical management, it offers assurance that the company's digital heritage remains usable and reliable. For operational teams, it guarantees the continuity of design and development activities. For partners and clients, it demonstrates mastery of quality processes and the ability to maintain the integrity of exchanged data.

The consequences of insufficient validation can be severe and lasting. Beyond immediate technical risks, they affect confidence in digital data, encouraging counterproductive workaround behaviors: systematic manual verifications, precautionary model recreation, or parallel maintenance of obsolete systems.

Migration validation should be viewed as a strategic investment rather than an additional cost. A return on investment (ROI) analysis generally reveals a favorable balance:

In a context where technical data constitutes a strategic asset, migration validation represents an essential link in the company's digital governance, alongside cybersecurity or product lifecycle management.

Effective validation methodologies

Implementing an effective CAD migration validation strategy requires the adoption of proven methodologies, adapted to the specificities of technical data and the particular requirements of the company. Several complementary approaches can be mobilized to guarantee the integrity of migrated models.

Advanced geometric comparison constitutes the foundation of any rigorous validation. Unlike simplistic approaches based on visualization or comparison of global properties, this method analyzes in detail the correspondence between geometric entities of source and target models. It relies on several sophisticated techniques:

• Intelligent point sampling: generation of control points on surfaces and edges, adapted to the local complexity of the geometry
• Deviation analysis: precise measurement of positional gaps between source and target geometries
• Detection of topological modifications: identification of changes in model structure (merged, divided, or missing faces)
• Entity correspondence: relationship between geometric elements across models for targeted analysis

Comparative analysis of physical properties complements this geometric approach. It verifies the preservation of essential mass characteristics: volume, mass, center of gravity, moments of inertia. These properties, derived from geometry but sensitive to subtle variations, constitute excellent synthetic indicators of conversion fidelity.

For parametric migrations, verification of the construction history is paramount. This structural analysis evaluates the preservation of functions, sketches, constraints, and relationships, thus ensuring that design intelligence remains accessible and exploitable in the new system. Specific metrics can be defined: function preservation rate, functional equivalence, maintenance of parent-child relationships.

Validation of annotations and PMI (Product Manufacturing Information) represents an often neglected but essential aspect, particularly in industries adopting the Model-Based Definition (MBD) approach. These critical elements for manufacturing must be preserved with the same rigor as the geometry itself.

To operationalize these validation methodologies, it is recommended to establish a structured evaluation framework, clearly defining:

• Precise quality criteria applicable to migrated models
• Acceptable tolerances for each type of deviation
• Specific test protocols by component category
• Remediation procedures in case of significant deviation
• Documentation and traceability rules for the process

These methodologies must be adapted to the specific context of the company, taking into account component criticality, applicable regulatory requirements, and particular operational constraints. A graduated approach, modulating validation intensity according to data criticality, generally allows optimizing the cost-effectiveness of the process.

CADIQ: complete solution for CAD migration validation

In the ecosystem of CAD migration validation solutions, CADIQ stands as an essential reference, offering a comprehensive and rigorous approach to guarantee the integrity of technical data during transitions between heterogeneous systems.

Developed by ITI TranscenData, CADIQ distinguishes itself by its ability to analyze CAD models in depth through a dual approach: intrinsic qualification of models and advanced comparison between source and target models. This comprehensive methodology allows identifying not only geometric deviations but also potential structural problems.

One of the major strengths of CADIQ lies in its extensive compatibility with the main CAD systems on the market:

• CATIA V5 and CATIA V4
• NX (formerly Unigraphics)
• Creo (formerly Pro/ENGINEER)
• SolidWorks
• Solid Edge
• Inventor
• Neutral formats (STEP, IGES, Parasolid)

This versatility makes it a particularly suitable tool for complex multi-CAD environments, characteristic of large industrial organizations and their partner ecosystems.

On the functional level, CADIQ implements more than 70 geometric and topological evaluation criteria, in perfect compliance with industry standards such as SASIG PDQ (Strategic Automotive product data Standards Industry Group Product Data Quality). This analytical richness allows a comprehensive evaluation of model quality, far exceeding simplistic comparison approaches.

The technical architecture of CADIQ is based on the use of native APIs of CAD systems, ensuring optimal precision in model analysis. Unlike approaches based on tessellation or intermediate neutral formats, this method ensures a faithful evaluation of the exact characteristics of mathematical models.

The validation process with CADIQ generally revolves around four complementary phases:

1. Source model qualification: identification of potential intrinsic defects even before conversion, allowing differentiation between pre-existing problems and defects introduced during migration
2. Converted model qualification: comprehensive evaluation of the target model according to established quality criteria
3. Detailed comparison: systematic analysis of correspondences and differences between source and target models
4. Documentation and reporting: generation of detailed reports facilitating analysis and traceability of the process

The user interface of CADIQ includes an advanced 3D viewer allowing simultaneous display of multiple models, with interactive highlighting of problematic areas. This side-by-side visualization considerably facilitates the analysis of differences and the evaluation of their potential impact.

For organizations engaged in large-scale migration processes, CADIQ offers advanced automation capabilities: batch processing, integration with PLM systems, and generation of aggregated metrics allowing global management of the migration process quality.

The adoption of CADIQ in a CAD migration strategy brings dual added value: immediate guarantee of data integrity and progressive building of internal expertise in digital model quality, beneficial well beyond the migration project itself.

Integration of validation in a complete migration process

The effectiveness of a CAD migration validation strategy largely depends on its harmonious integration into the global transition process. Far from being a simple final control step, validation should be viewed as a transversal dimension of the project, intervening at each key phase and actively contributing to its management.

Early planning of validation constitutes a critical success factor. From the initialization phase of the migration project, it is important to precisely define:

• Qualitative and quantitative validation objectives
• Specific acceptance criteria by model category
• Tolerance thresholds adapted to business requirements
• Necessary technical and human resources
• Articulation with other project activities

This proactive approach helps avoid the classic pitfall of late validation, often reduced to observing problems that are difficult to rectify without major impact on schedule and budget.

Establishing a structured validation process involves several essential components:

Defining a relevant sampling strategy. For projects involving large volumes of data, exhaustive validation can be prohibitive in terms of resources. A stratified approach, based on categorization of models according to their criticality, complexity, and frequency of use, generally allows optimizing the validation effort while maintaining a high level of confidence.

Implementing an iterative workflow. Validation should not be conceived as a simple binary filter (acceptance/rejection), but rather as a continuous improvement process. Early identification of recurring or systemic problems allows refining conversion parameters, thus creating a positive feedback loop that progressively improves the overall quality of migration.

Industrializing the process for large volumes. Automation of repetitive validation tasks becomes essential when facing large volumes of data characteristic of modern industrial environments. This industrialization can rely on various technologies:

• Batch processing scripts for sequential operations
• Queue management tools for resource optimization
• Automatic notification systems for anomaly tracking
• Synthetic dashboards for global process management

Integration with PLM systems (Product Lifecycle Management) allows firmly anchoring the validation process in the company's digital ecosystem. This integration offers several advantages: complete traceability of operations, coherent version management, application of existing governance rules, and continuity of business processes.

Effective management of detected anomalies represents a crucial aspect often underestimated. A methodical process must be established to:

1. Classify anomalies according to their nature and impact
2. Determine the appropriate resolution approach (automatic correction, manual rework, documented exception)
3. Ensure rigorous monitoring of corrections until their final validation
4. Capitalize on incidents to improve the overall process

Finally, systematic documentation of validation results constitutes a fundamental element, not only for immediate traceability but also for the sustainability of the digital heritage. This documentation must be structured, contextual, and easily accessible, allowing at any time to reconstruct the precise history of operations performed on a particular model.

Best practices and recommendations

Experience accumulated over numerous CAD migration projects allows identifying a set of best practices likely to optimize the effectiveness of the validation approach. These field-based recommendations constitute a valuable knowledge capital for organizations engaged in this complex transition.

Preliminary risk assessment represents a fundamental step to effectively orient the validation effort. This analysis must take into account several dimensions:

• Functional criticality of components (potential impact on the safety or performance of the final product)
• Geometric complexity of models (complex surfaces, multiple features, sophisticated parametric configurations)
• Quality history of source data (presence of known defects, multiple origins of models)
• Applicable regulatory requirements (industry standards, traceability obligations)

This evaluation allows establishing a criticality matrix guiding the prioritization of efforts and resource allocation throughout the validation process.

Defining a graduated approach generally constitutes an effective strategy when facing large volumes of data typical of industrial projects. This method consists of modulating validation intensity according to the criticality established previously:

Developing internal skills constitutes an often underestimated success factor. Training teams in validation principles and tools ensures not only the immediate effectiveness of the process but also its sustainability beyond the initial migration project. This skill development should target several profiles:

• Technical experts responsible for tool configuration
• Operators in charge of interpreting results
• Designers who need to understand the implications of validation on their practices
• Quality managers integrating validation into global processes

Establishing a continuous validation process, beyond the strict framework of the migration project, represents a particularly relevant approach. Validation should not be considered as a one-time activity but as a permanent component of technical data governance, applying particularly to:

• Regular exchanges with external partners
• Major updates of CAD systems
• Data acquisitions from scanning or other sources
• Significant modifications of critical models

Methodical capitalization on acquired experience constitutes a valuable lever for continuous improvement. Each migration project generates a capital of specific knowledge that should be formalized and shared:

• Documentation of recurring problems and their solutions
• Consolidation of optimal parameters for different model categories
• Identification of good modeling practices facilitating future migrations
• Development of specialized tools and scripts adapted to the company context

Finally, anticipation of future developments constitutes an essential strategic dimension. The technological landscape of CAD continues to evolve rapidly, with the emergence of new approaches such as cloud-based CAD, digital twins, or artificial intelligence technologies applied to design. A robust validation strategy must be able to adapt to these evolutions, maintaining its relevance in a constantly transforming technological environment.

These best practices, far from being simple theoretical recommendations, represent concrete levers for optimizing the validation process, directly contributing to the overall success of the CAD migration project and the sustainability of the company's digital heritage.