Additive Manufacturing at GE Aviation – Advancing Aerospace with 3D Printing

Begin with a two-track pilot: deploy additive manufacturing on non-critical assemblies first while maintaining existing supply chains. This cannot be delayed because early, verifiable results drive confidence, and a program seeking performance gains in throughput and product families yields measurable improvements in reliability and cost per part, supported by data-driven decisions.

Adopt a concept-driven plan that links design-for-AM, process controls, and qualification. The initial phase should define the between-design and legacy parts, and a clarifying nucleation-focused tolerance plan will help reduce variability in builds. Establish a policy for data capture and traceability that an agency can audit, with roles mapped to arranging responsibilities and meetings.

Concrete gains come from validated components like the fuel nozzle: GE Aviation, which specializes in high-performance propulsion components, printed nozzle condenses nearly twenty parts into one, cutting assembly steps and enabling known improvements in reliability. Build rates rise as printing economies of scale kick in and post-processing steps become shorter through automated workflows. Track the rates, defect rates, and yield to guide the transition from prototype to production.

GE Aviation should engage with known firms and research bodies worldwide to share lessons. A stockholm-based initiative led by matthias illustrates how cross-disciplinary collaboration tightens feedback loops and aligns policy with manufacturing realities. A lack of standardized data handling can slow progress; to counter this, arranging regular meetings with suppliers, customers, and internal agencies to align objectives and publish results. We track every milestone to inform decisions.

Recommendations for the 12- to 18-month horizon include: formalize a cross-functional steering committee; establish a robust data-readiness plan; invest in materials characterization to understand nucleation behavior in nickel-based alloys; define part selection criteria with a clear production-readiness gate; implement staged production releases; set up an internal and external channel for policy and standard updates by arranging ongoing meetings with agencies and industry groups.

Global AM Networks and GE Aviation’s Collaborative Framework

Implement a standardized cross-network data exchange and governance framework within 90 days to boost acceptance across industries. This framework will support country-to-country collaboration and anchor GE Aviation’s alabama campus as a model node.

Global AM Networks and GE Aviation’s Collaborative Framework coordinate through a core data hub, sector-specific working groups, and a steering committee.

Data categories include 3d-printing build logs, process parameters, material lots, post-processing steps, and inspection results. The framework requires standardized data formats and traceability.

To create a practical formation, appoint a country-level manager for each region and seed the alabama facility as a pilot node; collaborate with a partner such as riedel to ensure robust communications.

Mechatronics and software SMEs will help categorize parts by sector and sized for risk; this approach clarifies QA checks and speeds approval.

Procedures cover data access, change control, and qualification steps; anyone can request access via the manager, with escalation to the steering committee if needed.

Across industries, the framework enables rapid onboarding of suppliers and accelerates learning in the aviation sector; measured improvements include 15-20% faster qualification cycles and 18% lower scrap in the Alabama pilot.

Next steps include expanding the network to additional countries, categorizing partners by capability, and aligning with regulators to ensure compliance.

Material Qualification and Certification for GE Aviation AM Parts

Adopt a formal material qualification and certification plan for GE Aviation AM parts, aligned with FAA/EASA statutes, and appoint a body of participants from materials science, manufacturing, QA, and certification to govern the process. Use a risk-based strategy that categorizes parts by criticality, ensuring traceability from raw material lot through final part. The plan should address known data gaps and present clear acceptance criteria for each material/process pair.

Define the initial material set and capnor codes as an internal reference for a material family with shared microstructure and performance targets. For capnor, document assumed properties, tested correlations, and alignment with legacy alloys to enable direct comparisons. Emphasize that the known properties inform build windows, post-processing needs, and inspection plans, while the sector learns from cross-program data gathered by the body.

Develop a process qualification approach that specifies initial process windows, build orientation considerations, heat treatment, surface finishing, and post-build treatments. Establish quantitative acceptance criteria for porosity, grain structure, and residual stress, plus explicit NDE methods such as CT and high-resolution radiography. Require representative coupons and flight-like specimens for every material/process pair, with an assumed correlation between lab results and in-service performance.

Build a rigorous testing plan that includes static and fatigue properties, fracture toughness, creep if relevant, and environmental exposure effects. Create a body of evidence that documents material behavior across temperatures and load spectra, and define data-management standards to ensure traceability from each lot to final aircraft parts. Include an experiment log to capture learnings quickly and turn them into actionable revisions of the qualification plan.

Address under-researched topics such as anisotropy introduced by layer-by-layer fabrication, the impact of build orientation on joint strength, and the interaction between post-processing cycles and microstructure. Schedule targeted experiments to fill gaps, then update the categorization of risk and the qualification strategy accordingly. Perceived risks should be reassessed as new data arrive, with dynamic prioritization that drives improvement without slowing program cadence.

Align the regulatory and compliance path with statutes and industry norms, recording all decisions in a transparent, auditable body of documentation. Ensure full lot traceability, material provenance, process-parameter tracking, and change-control workflows that satisfy both internal standards and external certification gates. Engage regulators early to define acceptable demonstration samples and reproducible test results for parts from the capnor family.

Future collaboration across the sector will help harmonize expectations, reduce duplication of effort, and accelerate time to service. Engage cross-industry partners such as Equinor to share best practices on life-cycle data, simulation-informed testing, and qualification workflows while maintaining GE Aviation’s dream of safer, more sustainable aircraft propulsion. Maintain a disciplined cadence of experiments and reviews to keep the program adaptive to new materials, new processes, and evolving statutes.

Implement the plan with a concrete timeline and measurable gates: complete the initial qualification for a targeted set of materials within 12–18 months, certify the first parts for flight-representative scenarios, and publish the qualification package to support future program reuse. Address known weaknesses promptly, iterate on process windows, and expand the approvals as the evidence grows, ensuring the approach remains practical, defensible, and aligned with the future needs of the aviation sector.

DfAM Guidelines for Jet Engine Components

Adopt a DFAM workflow that begins with a mandated manufacturability assessment and uses 3dstep models to compare alternative geometries before locking the final geometry. Those models should be grounded in background data from prior tests, loading histories, and flight profiles, presented by managers and design teams, and provided to a shared repository for rapid review during establishing phase. This foundation saves design cycles and accelerates the path to a printable product.

Leverage topology optimization to cut part counts and weight for turbines, housings, and combustor liners. Favor conformal cooling channels and lattice cores where appropriate, and present comparative results as a unique path toward higher capacity and reliability. Expect 15-40% weight reduction in cooled components when a single print replaces multi-piece assemblies, while keeping geometry within printer capability and post-process feasibility.

Set concrete geometry rules to balance printability with performance. Target minimum wall thickness values of 0.8–1.0 mm for Ni-based alloys in powder bed processes; internal cooling channels should be at least 0.8–1.2 mm in diameter to enable cleaning and post-processing. Avoid overly acute overhangs, and plan supports only on nonfunctional surfaces with clearly defined removal methods that do not compromise critical features.

Outline clear process steps for orientation, supports, and post-processing. Favor build orientations that expose flat, measurable surfaces to inspection and reduce support mass by 40–70%. Require post-build HIP at 1120–1200°C for 2–4 hours for Ni-based alloys, followed by finishing to achieve surface roughness around Ra 1.5–2.0 µm on critical faces. Define acceptance criteria for porosity (<0.5% by volume) and verify through non-destructive evaluation, such as X-ray CT, on a subset of parts to confirm channel integrity and material density.

Governance and collaboration drive consistent results. Share keywords and reference models across teams to speed decision making, and align with governments and suppliers on certification expectations. Establishing DFAM champions, training programs, and feedback loops helps those programs scale, sustains capacity, and protects jobs. After each build, feed results back into 3dstep models to refine design rules, supporting a closing loop that improves product reliability and reduces development time.

Process Validation, QA, and Part Traceability in 3D Printing

Adopt an end-to-end process validation framework that links design intent to final part data and uses a single, auditable traceability record across all 3D-printed components.

The strategy emphasizes eight critical controls, an organized data structure, and an explicit theory-backed approach to qualification and production. The initiative takes clear motives into account and supports transitions from design, build, and inspection while remaining open to improvement; energy is directed toward concrete outcomes across various platforms and projects.

• Design release and geometry validation: verify manufacturability, feature fidelity, and tolerance maps against the CAD model using a structured checklist that defines the level of risk for each feature and keeps teams aligned.
• Material qualification and supply data: maintain material lot numbers, supplier certificates, and thermal properties in a unified system; provide traceability from receipt to final part, even for mixed-material builds in various programs.
• Process parameter management: define parameter windows with guard bands; implement cusing in-situ analytics to detect deviations and trigger stops before part distortion occurs.
• Printer calibration and maintenance: incorporate routine calibration, printer health metrics, and a documented maintenance history; managers review dashboards at a set energy level each week to confirm readiness.
• In-process QA and metrology: deploy inline sensors, dimensional checks, and real-time SPC dashboards; capture results to the part-specific data structure to enable rapid feedback and root-cause analysis.
• Post-processing and finishing: standardize cleaning, heat treatment, and surface finishing steps; ensure post-processing data remains part of the traceability lineage and is auditable.
• Final inspection and acceptance: use CMM measurements, surface roughness, and non-destructive methods; archive measurement results and compare to nominal tolerances within the same systems for easy retrieval.
• Governance, roles, and improvement: define responsibilities for design engineers, process engineers, QA, and production managers; implement a closed-loop improvement process with recorded actions taken and results achieved.

This framework ties performance signals to actions, and the eight controls become the baseline for continuous improvement. It leverages open data structures and a strategy that draws on innovation insights. The provided data supports audits, recalls, and performance improvements found across multiple aircraft projects.

Engagement with external venues strengthens capability. Salmi conferences offer practical insights from operators and suppliers, while collaborations with partners such as usken and equinor validate the approach across different ecosystems, including energy and aerospace programs. The initiative keeps energy focused on concrete outcomes and avoids hidden motives, ensuring the motive behind each design change is explicit and verifiable.

Production Ramp and Supply Chain Integration in AM Clusters

Recommendation: establish a centralized AM ramp plan with a primary owner and a steering committee that directly links funding to milestone deliveries, onboarding suppliers, and validating part readiness by january. The plan assigns siavash as grounding lead, davis as data and models coordinator, and usken as supplier integration liaison, ensuring involved individuals stay aligned across eight sites. This structure creates a single source of truth for manufacturing readiness and reduces handoffs.

Structure the supply chain around modular AM clusters that share standardized structures, common data models, and digital twins for each part family. Develop eight baseline models of capacity, cycle times, yield, and scrap; use these models to forecast at-risk components and reallocate capacity in real time. Align primary suppliers, material vendors, and contract manufacturers under a single steering framework and establish a cadence of weekly reviews for involved parties and a monthly steering meeting to approve funding adjustments.

Implementation steps include appointing cross-functional product owners, mapping each part family to a primary AM path, and implementing a common bill-of-materials. Launch pilots starting in january and scale best practices to other sites. Eight pilot parts validate design-to-print, build, and post-processing models, grounding decisions in real data. The effort relies on a digital backbone that links design data, process parameters, and inspection results, enabling researchers and involved teams to compare performance across clusters and accelerate enhancement efforts. This approach should enhance throughput, reduce lead times, and strengthen resilience in the supply chain.

Global AM Groups: Collaboration Models, Governance, and Knowledge Sharing

Establish a Global AM Groups Council by Q4 2025 to coordinate collaboration across six countries, with a rotating head and a professional manager, and a charter that defines funding, decision rights, and a calendar of cross-border initiatives. Taken together, this governance foundation signals stability and unlocks shared investments in equipment, testing, and digital tools.

Adopt a three-tier collaboration model: a central authoring hub for standards and templates; regional chapters that run joint projects; and project circles tied to engine programs and supplier ecosystems, facilitating cross-border initiatives. This structure keeps decisions fast while ensuring consistency across aerospace programs from design to build, and it helps develop standardized workflows that teams can reuse in different countries.

Knowledge sharing hinges on a secure, social platform and a data lake that hosts design files, test results, and lessons learned. Sharing should protect IP while promoting openness; provide differentiated access by role, and document knowledge in a way that improves perceived reliability across teams and countries. Include guidelines on publication where appropriate to protect IP. This setup helps reduce rework and accelerates transitions.

Governance and risk management: align with governments and regulators; set IP terms, data rights, and access controls; require consent for publication; implement audits of equipment usage and safety compliance. The head of the council should report to a steering committee with representation from manufacturers, airlines, and governments; this reduces risk and improves the image of the AM community. Involved teams worked together to harmonize standards across countries, easing transitions for suppliers and customers alike.

Implement pilots in two or three regions across North America, Europe, and Asia to test the model; measure impact with metrics such as time-to-first-part, cost reductions, and lead-time smoothing; publish annual results and case studies authored by managers and engineers. Ensure cusing on reducing friction between disciplines and partners, yielding a differentiated capability across aerospace where engine programs rely on shared processes and equipment. The result is a professional image that governments, customers, and suppliers perceive as reliable and responsive to transitions in demand.