Aerospace
Programs that run for decades, products with millions of parts, and an airworthiness authority that must be able to trace every change back to a requirement.
The Nature of the Aerospace Industry
- →Extremely long product lifecycles: aircraft, engines and structures remain in service and in support for 30 to 50 years, far longer than the systems originally used to design them.
- →Deeply layered supply chains in which risk-sharing partners design and certify major assemblies, and configuration data must be exchanged continuously across companies and nations.
- →Certification by authorities such as the FAA and EASA, which requires demonstrable traceability from requirement to design, analysis, test evidence and as-built configuration.
- →Low volumes and high mix, where every delivered tail number is effectively a unique configuration with its own effectivity, deviations and service history.
Typical Challenges in Innovation and New Product Development
Configuration and effectivity management
As-designed, as-planned, as-built and as-maintained structures diverge quickly. Without rigorous effectivity and change control, engineering releases no longer describe the aircraft actually flying, and MRO decisions are made against the wrong baseline.
Requirements and certification traceability
Certification packages are assembled late, by hand, from documents spread across requirement tools, CAD, simulation and test systems. Proving compliance becomes a document exercise rather than a by-product of engineering.
Multi-tier collaboration and data exchange
Partners work in different PLM and CAD environments, with export controls, ITAR restrictions and IP boundaries limiting what can be shared. Model translation and re-work consume engineering capacity.
Long-term data retention and obsolescence
Design data must remain readable and legally defensible for decades while authoring tools, formats and suppliers change several times over the life of the program.
Programme cost and schedule pressure
Late engineering changes ripple into tooling, certification and production, and are typically discovered only when the physical article is built.
How PLM and AI Have Benefitted Aerospace Companies
A certified digital thread
PLM links requirements, design, simulation, manufacturing planning and test evidence in one governed structure, so compliance artefacts are generated from live data instead of assembled retroactively. Certification cycles shorten and audit findings drop.
Configuration control that holds up in service
Effectivity-driven BOM management keeps as-designed and as-built aligned, giving MRO and support the exact configuration of each tail number and reducing the cost of service bulletins and retrofits.
AI-assisted requirements and compliance review
Language models review requirement sets for ambiguity, duplication and conflicts, map them to applicable regulations, and flag gaps in compliance evidence long before a certification audit.
AI in design and simulation
Generative design and surrogate simulation models explore far more structural and thermal alternatives than manual iteration allows, delivering lighter parts and fewer physical test cycles.
Predictive quality and sustainment
Machine learning on fleet and sensor data predicts component degradation, driving condition-based maintenance and feeding real service behaviour back into the next design iteration.
Outcomes We See in Aerospace
- ✓Certification evidence assembled continuously rather than in a final documentation push
- ✓Single, authoritative configuration baseline shared with partners and MRO
- ✓Fewer physical test articles through validated simulation and AI surrogates
- ✓Shorter change-cycle times on long-running programs
Discuss Your Aerospace Initiative
Tell us about your product development and PLM priorities and we will share how comparable aerospace organizations have approached them.