Under-design risk
- Fatigue-critical hotspots remain invisible until field operation
- Reactive response after customer-side failures
- Warranty exposure and emergency service load
Automated Fatigue Post-Processing for Industrial Equipment
Agent-based fatigue workflow operating on existing FE results. Solver-agnostic, deterministic, and traceable by design.
15 min
target agent turnaround
3-5
pilot teams targeted
30-50%
downtime reduction benchmark range
Fatigue post-processing remains largely manual
Most machinery teams already run static and dynamic FEA, but fatigue assessment is still fragmented across manual extraction, spreadsheets, and ad-hoc scripts.
Current manual workflow
01
Extract nodal stresses from FE results
02
Identify critical locations manually
03
Look up S-N data from standards documents
04
Run rainflow counting in spreadsheets/scripts
05
Calculate cumulative damage with Miner's rule
06
Compile report manually for review
4-8h
Typical manual post-processing per analysis
0%
Built-in traceability in ad-hoc workflows
+/-30%
Analyst-to-analyst variance risk
Two failure modes from missing fatigue data
Without systematized fatigue evidence, teams are forced toward either under-design risk or costly over-design.
Over-design cost
- Conservative safety factors without fatigue evidence
- Material and mass penalties in welded structures
- Longer iteration loops due to uncertainty
Agent-based fatigue post-processing
Designed to fit existing engineering workflows while improving repeatability and review quality.
Post-processing only
Works downstream of your current FE solver. No changes to model setup workflow.
Deterministic fatigue math
Rainflow counting, S-N interpolation, and damage accumulation remain deterministic.
Traceable by design
Each result links to source files, methods, assumptions, and selected standards context.
Processing pipeline
End-to-end flow from FE result ingestion to audit-ready reporting.
STEP 1
Ingest
FE results (.op2/.h3d/.odb/.rst), load histories (CSV), and material parameters.
STEP 2
Process
Stress extraction at critical regions, cycle decomposition, and mean-stress correction.
STEP 3
Compute
Damage accumulation, life estimation, and ranked critical locations.
STEP 4
Report
PDF/Word output with audit trail, pass/fail framing, and integration-ready JSON.
FKM Guideline · IIW Recommendations · Eurocode 3 · ASTM E1049 · Goodman / Gerber / FKM R-ratio
Standards-based analysis outputs
Representative output styles for engineering review and decision support.
Hotspot map and ranking
Auto-detected critical regions ranked by cumulative damage.
Duty-cycle processing
Load-history decomposition and cycle accounting for fatigue usage.
Review-ready outputs
Traceable summaries for engineering, quality, and service teams.
System architecture
Separation of concerns between AI orchestration and deterministic fatigue computation.
Interface
Web UI for file upload, parameter configuration, and report export.
Agent layer
Method-selection guidance, input checks, and standards-aware orchestration.
Compute engine
Deterministic Python stack for parsers, cycle counting, and damage calculation.
Key constraint
AI supports workflow orchestration and method guidance. Fatigue calculations remain deterministic so outputs are reproducible and audit-ready.
Engineering governance
Every analysis run should produce a defensible, traceable audit package.
Method approval
Only validated fatigue methods are enabled in governed configurations.
Parameter bounds
Invalid ranges are rejected before compute execution.
Traceability
Inputs, model choices, curve IDs, and extraction regions are logged.
Reproducibility
Identical inputs produce identical fatigue outputs.
Audit log
Timestamped records of agent decisions and user overrides.
Version control
Method libraries and fatigue data are version-tagged for reviews.
Workflow comparison
Manual fatigue workflows versus a governed agent pipeline.
| Dimension | Manual process | Agent-based |
|---|---|---|
| Cycle time | 4-8 hours | ~15 minutes |
| Consistency | Analyst-dependent | Deterministic |
| Traceability | Implicit | Explicit and logged |
| Method selection | Manual lookup | Guided and standardized |
| Hotspot ID | Visual inspection | Ranked by damage |
| Reporting | Manual document assembly | Auto-generated with audit trail |
Supported formats
Solver and data formats prioritized for phased rollout.
.op2 .h3d
OptiStruct
Phase 1 priority
Phase 1.op2
Nastran
Shared parser path
Phase 1.odb
Abaqus
Python API integration
Phase 2.rst
Ansys
Parser integration path
Phase 2CSV
Load data
Duty cycles and spectra
Phase 1S-N lib
Material data
Standards-aligned libraries
Phase 1High-fit target scenarios
Technical use-case framing based on your deep research report for industrial machinery fatigue-monitoring deployment.
SN Maschinenbau
Strong installed-base and uptime-driven packaging operations.
Lead use case
Sealing/cutting jaw drive fatigue monitoring with strain + vibration + drive telemetry.
Expected value focus
Target: earlier intervention planning and lower unplanned line-stop risk.
B&B Verpackungstechnik
Modular bag-making and end-of-line systems with digital engineering signals.
Lead use case
Punch/perforation station fatigue monitoring for tool-holder and linkage components.
Expected value focus
Target: reduce crash events, scrap, and reactive maintenance.
NERAK Fördertechnik
Conveyor reliability business with service and remote diagnostics alignment.
Lead use case
Chain-drive and shaft fatigue monitoring from torque, vibration, and cycle patterns.
Expected value focus
Target: planned swaps before overload-driven failures.
Pilot plan (recommended target)
Suggested first pilot: one high-cycle subsystem on a representative packaging machine with measurable success metrics in 3-6 months.
M1
Weeks 1-2: select subsystem, failure modes, and data access paths
M2
Weeks 3-4: instrumentation install and baseline capture
M3
Weeks 5-8: edge pipeline and first fatigue/risk outputs
M4
Weeks 9-12: threshold tuning with engineering + service teams
M5
Weeks 13-16: replicate on second machine and ROI playbook
What should we finalize next?
Review these page decisions and tell me your choices. I will update the fatigue page in one pass.
Primary launch vertical
- Industrial machinery first
- Electronics packaging first
- Dual-track messaging
Public technical depth
- Executive-level only
- Detailed methods + architecture
- NDA-gated appendix
Pilot CTA focus
- Request pilot call
- Download technical brief
- Join waitlist + use case intake