FEA, CFD, and Moldflow simulation for automotive OEMs and Tier-1 suppliers — by an engineer who spent years inside Tier-1 CAE teams. We understand DVP gates, PPAP timelines, and the difference between simulation that drives decisions and simulation that generates paperwork.
Automotive programs don't have slack. DVP gates, PPAP deadlines, and SOP dates are set 18 months in advance and don't move because your simulation partner is backlogged. When your internal CAE team hits capacity — or when the physics go beyond standard linear FEA — you need an external partner who understands the urgency.
The large consultancy model is structurally incompatible with automotive timelines. They have scheduling queues, utilization targets, and a habit of rotating junior analysts onto your project mid-program. You find out at the design review when the results don't make sense — and by then you've burned 6 weeks of program time.
Eight years inside Tier-1 CAE teams means we understand your document requirements, your OEM's specification language, and the material systems you actually work with. We don't need onboarding.
Early FEA for geometry feasibility and stiffness target validation. Injection molding fill study to position gates before tooling.
Nonlinear FEA for strength and durability. Moldflow DOE to lock gate locations and predict weld-line positions.
PSD random vibration analysis to predict validation outcome before physical test. Creep and thermal cycling fatigue studies.
Analysis documentation for design record. Reanalysis if geometry changed during tooling phase. Process capability review.
Process-aware nonlinear structural analysis for PPGF30, PA66GF30, and elastomeric components. Fiber orientation tensor mapped from Moldflow into Ansys for accurate weld-line strength prediction. The analysis that prevents DVP failures before you build the prototype.
The analysis that most teams skip — and then fail DVP over. Road-load PSD profiles applied in full spectral analysis. Resonant failure modes identified before physical testing. Redesign recommendations that tune frequency, not just add mass.
3D fill, pack, warp, and fiber orientation analysis. Gate location DOE for weld-line control. Rheology studies to optimize process parameters before tooling is cut. Warpage prediction to catch dimensional issues before PPAP.
Time-dependent creep under sustained thermal-mechanical loads for connectors and underhood components. Thermal cycling fatigue for PA66GF30 parts subjected to engine bay temperature cycles. Predicts dimensional instability and stress relaxation in fastened joints.
Hyperelastic FEA for O-rings, lip seals, and molded elastomeric sealing components. Contact pressure maps for sealing function assessment. Compression set and assembly load prediction. Material coefficients fitted from supplier test data.
Coolant circuit pressure drop and flow distribution. Conjugate heat transfer for underhood component temperature mapping. Transient thermal analysis for startup and thermal shock events. Identifies components exceeding temperature specifications before validation testing.
Not general material modeling — specific experience with the polymer systems, rubber grades, and steel specifications that make up automotive components. Each has a fundamentally different failure mode and a different modeling strategy.
The most commonly mis-analyzed materials in automotive FEA. Isotropic properties from the datasheet predict 2–3× the actual weld-line strength. Process-aware modeling with Moldflow → Ansys fiber orientation mapping.
Rubber sealing components in coolant circuits, fuel systems, and HVAC. Hyperelastic formulations calibrated from compression test data. Sealing contact pressure maps to verify functional performance.
Stamped steel brackets and structural components with spot welds, laser welds, and adhesive bonds. IIW fatigue class assessment for weld toe locations. Forming effects on residual stress where relevant.
PSD analysis identified resonant failure modes in the 50–200 Hz band before physical testing. All 4 variants cleared DVP first pass.
Read case study →Moldflow DOE + process-aware FEA eliminated brittle weld-line fracture. Runner change only — no tooling geometry modification.
Read case study →Process-aware FEA on fluid transfer connector cut prototype iterations from 3 to 1. Moldflow → Ansys workflow validated within ±8% of test.
Read case study →Eight years of daily simulation work inside Tier-1 automotive CAE teams — not eight years of consulting on automotive problems. The difference is knowing that PPGF30 weld lines sit in high-stress zones by default unless you control the gate, and that DVP schedules never have the slack a consultancy's scheduling queue assumes.
PPGF30, PA66GF30, EPDM, NBR, DC04 sheet metal. Not generic isotropic constants from a datasheet — material models calibrated to the physics of each system, including the fiber orientation dependency that changes everything for injection-molded polymers.
Every report includes mesh convergence data, boundary condition justification, material model source, and sensitivity study results. Not because an OEM requires it — because a result you can't audit is a result you can't trust in a design review.
Tell us the component, the failure mode you're worried about, and the milestone date. We'll scope the analysis in 30 minutes and have a proposal to you within 48 hours.
Discuss an Automotive Project →Initial response within 24 hours · NDA available upon request