FXNL
Projects

Project / Aerospace / Engineering Traceability

Turning Engineering Requirements Into Connected Evidence.

FXNL built a centralized engineering traceability system connecting requirements, verification activities, tests and evidence across an aerospace development environment.

Industry
Aerospace
Solution
Requirements + Verification Traceability
Integrations
DOORS · Azure DevOps · SharePoint · SQL · PLM
Scope
End-to-End

The Impact

From manual reconciliation to controlled traceability.

Instead of reconstructing engineering relationships across spreadsheets, documents and separate systems, teams can work from a connected traceability layer built around controlled engineering records.

Before · Manual Reconstruction

  1. Export Data
  2. Reconcile Identifiers
  3. Locate Evidence
  4. Compare Revisions
  5. Build Traceability Matrices

After · Exception Review

  1. Generate Current Traceability
  2. Identify Missing Links
  3. Surface Affected Artifacts
  4. Review Exceptions
  5. Approve Changes

Operational Impact

Less manual reconciliation · Faster traceability reviews · Better verification visibility · Clearer change impact · Stronger auditability

The Challenge

The relationships existed. They just didn’t exist in one place.

Requirements, verification activities, test procedures, results and supporting evidence lived across different engineering systems, documents and teams. Excel often became the connective layer.

Before reviews and verification milestones, engineers had to reconcile identifiers, locate evidence, compare revisions and determine whether every requirement had appropriate verification coverage.

Changes created another problem: when a requirement was revised, engineers needed to determine which tests, verification records and downstream artifacts might also require review.

The Traceability Layer

Every requirement connected to its evidence.

FXNL created a normalized traceability layer across the organization’s existing engineering systems, allowing relationships to remain visible as requirements, tests and evidence evolve.

Systems of Record

  • DOORS
  • Azure DevOps
  • SharePoint
  • SQL
  • PLM

Normalized Traceability Layer

Controlled identifiers · Revisions · Relationships · Provenance

Controlled Relationships

Requirement

SYS-1042

Rev C

Verification

VR-1042

Rev B

Test Procedure

TP-284

Rev D

Test Result

TR-284

Evidence

Controlled Record

Synthetic identifiers shown for illustration. Relationships are maintained bidirectionally and stay current as requirements, tests and evidence are revised.

Change Impact

When one requirement changes, the system shows what may follow.

A requirement revision does not automatically invalidate every downstream artifact. The system identifies the connected records that may require review so engineers can assess the impact without starting a manual investigation from scratch.

  1. RequirementSYS-1042

    Rev C → Rev D

  2. VerificationVR-1042

    May require review

  3. Test ProcedureTP-284

    May require review

  4. Test ResultTR-284

    May require review

  5. EvidenceSupporting Evidence

    May require review

Controlled Engineering Data

Traceable. Versioned. Auditable.

Every engineering record carries controlled identity, relationships and workflow state—so traceability holds up under review rather than being reassembled by hand.

Identity

  • Unique identifiers
  • Record ownership
  • Controlled revisions
  • Source-system references

Traceability

  • Requirement relationships
  • Verification methods
  • Test procedures
  • Test results
  • Supporting evidence

Workflow

  • Change review
  • Approval routing
  • Gap detection
  • Status tracking
  • Audit history

Integration

Connect the engineering environment. Don’t replace it.

The objective was not to replace every engineering system already in use. FXNL integrated the existing environment—including DOORS, Azure DevOps, SharePoint, SQL and PLM systems—and established a normalized traceability layer between them.

That architecture allows each system to continue serving its intended purpose while creating a connected view of requirements, verification activities, tests, results and evidence.

Existing Systems

  • DOORS
  • Azure DevOps
  • SharePoint
  • SQL
  • PLM

Traceability Layer

Normalized relationships across systems

Engineering View

Requirements, tests, results and evidence in one place

Implementation

The Hard Part Wasn’t Storing the Requirements.

The difficult part was establishing reliable relationships across engineering systems that were never designed to operate as one traceability environment.

The same engineering record could appear under different identifiers, document formats or revisions. A relationship could be logically correct while still pointing to an outdated revision.

The system therefore had to account for identity, revision control, permissions, provenance, workflow state and audit history—not simply connect records with links.

The goal wasn’t another requirements database. It was trustworthy relationships between engineering records.

FXNL’s End-to-End Role

  1. Discover
  2. Map
  3. Architect
  4. Build
  5. Integrate
  6. Deploy

FXNL handled the project end-to-end, including discovery, process mapping, architecture, development, integrations, deployment, training and ongoing support.

What’s Next

A foundation for AI-assisted engineering traceability.

With structured relationships, controlled revisions and source provenance in place, a future phase can introduce AI where semantic interpretation is useful. Potential future capabilities include analyzing requirements and test descriptions to suggest possible verification relationships, identifying potentially missing connections, and helping engineers navigate larger bodies of engineering evidence.

AI can recommend a relationship. An engineer decides whether it becomes engineering truth.

Future Phase
  1. AI Suggestion
  2. Source Evidence
  3. Engineer Review
  4. Accept / Reject / Modify
  5. Audit Record

These capabilities describe a future phase. They are not part of the deployed system, and AI does not independently determine that a requirement has been satisfied.

Have a workflow like this?

FXNL helps organizations connect fragmented systems, data and processes into controlled technology infrastructure built for how their teams actually work.

Start a Conversation