After implementing comprehensive CAD validation automation across our test data management system, I can share detailed approaches covering PX scripting for validation, SDK automation, and compliance checks that have proven highly effective.
PX Scripting for Validation:
PX scripts provide the first line of automated validation, executing immediately when test engineers attach CAD files to test objects. We implemented event-based validation that intercepts the attachment workflow before files are committed to the system.
Our PX validation framework includes four core validation modules. The format validator checks file extensions against approved CAD formats and verifies file integrity by attempting to read file headers. The naming convention validator uses regex patterns to ensure filenames follow our standardized format including part number, revision, and test identifier components.
The metadata validator is particularly powerful. It extracts CAD file properties and verifies that required metadata fields are populated with valid values:
CADFile cadFile = (CADFile) attachment;
if (cadFile.getProperty("Author") == null) {
throw new ValidationException("Author required");
}
The geometry validator performs basic checks like verifying that assemblies contain components and that part files have non-zero volume. For complex geometry validation requiring CAD kernel operations, PX scripts queue files for deeper analysis by the SDK-based validation service.
Critical to user experience is providing immediate, actionable feedback. Our PX scripts return detailed validation messages that specify exactly what failed and how to correct it. This eliminated the frustration of generic error messages and reduced resubmission cycles.
We implemented validation result caching to avoid redundant checks. If a CAD file has been validated previously and hasn’t changed, the PX script retrieves the cached result rather than re-running validation. This significantly improved performance for frequently used test data files.
SDK Automation:
The Agile SDK enables sophisticated validation automation that would be impractical in PX scripts due to complexity or processing time. We built a validation service that runs as a scheduled job and processes CAD files queued by PX scripts or submitted directly by test engineers.
The SDK service architecture uses a plugin model where individual validation modules register with the core framework. This extensibility allows us to add new validation types without modifying the core service. Each module implements a standard interface:
// Pseudocode - Validation module interface:
1. Initialize validator with configuration parameters
2. Accept CAD file input and validation context
3. Execute validation logic (geometry analysis, standards checking)
4. Return validation result object with pass/fail status and detailed findings
5. Log validation metrics for reporting
// See SDK Developer Guide Section 12.3
For geometry validation, we integrated third-party CAD libraries that provide access to geometric properties and analysis functions. The SDK service extracts CAD files from Agile, passes them to the CAD library for analysis, and evaluates results against our standards. This enables validations like checking for minimum wall thickness, verifying assembly interference, and detecting duplicate geometry.
The SDK automation handles batch validation scenarios efficiently. Test managers can submit entire test data sets for validation, and the service processes files in parallel using a thread pool. Validation results are written back to Agile as attachment properties, making them searchable and reportable.
We implemented retry logic for transient failures and comprehensive error handling. If CAD file extraction fails due to network issues, the service retries with exponential backoff. If a specific CAD file causes the validation module to crash, the service isolates the failure, logs details for investigation, and continues processing remaining files.
Compliance Checks:
Compliance validation ensures CAD files meet industry standards, regulatory requirements, and internal design guidelines. We implemented a rule-based compliance engine that evaluates CAD files against configurable rulesets.
Compliance rules are defined in XML configuration files that specify validation criteria, severity levels, and remediation guidance. This configuration-driven approach allows quality engineers to update compliance requirements without code changes. When standards evolve, we update the rule definitions and deploy new configurations.
Our compliance framework includes rule categories for design standards (material specifications, dimensional tolerances), regulatory requirements (safety certifications, environmental compliance), and test-specific criteria (fixture compatibility, measurement point accessibility).
The compliance checker generates detailed reports showing which rules passed, failed, or generated warnings. Reports include visual annotations highlighting problem areas in CAD viewables, making it easy for engineers to understand and address issues.
For critical compliance failures, the validation system automatically routes CAD files to quality engineering for review rather than allowing them into test data. This ensures non-compliant files never reach test execution where they could invalidate results.
Integration and Workflow:
The complete validation framework integrates PX scripts and SDK automation into a seamless workflow. When test engineers attach CAD files, PX scripts perform immediate validation of format, naming, and basic properties. Files passing initial validation are queued for comprehensive SDK-based geometry and compliance validation.
Test engineers receive real-time feedback on initial validation and email notifications when background validation completes. The test object status reflects validation state, preventing test execution until CAD files pass all validation checks.
We built validation dashboards using Agile analytics that show validation metrics, identify common failure patterns, and track processing times. This visibility helped optimize validation rules and identify CAD quality issues requiring engineering attention.
The combination of immediate PX validation, thorough SDK automation, and configurable compliance checking has reduced manual validation effort by 85% while improving consistency and quality of test data. Start with basic format and naming validation in PX scripts, then progressively add SDK-based geometry and compliance validation as your automation matures.