AI-Suggested Failure Modes

When you create or edit a PFMEA, FailModeLens can suggest failure modes specific to your manufacturing process. Describe your process step — for example, ‘spot welding of B-pillar reinforcement to inner panel, 12-point weld pattern, robotic, mild steel 1.2mm + HSLA 1.5mm’ — or select from a process type taxonomy covering stamping, injection molding, CNC machining, assembly, welding, painting/coating, heat treatment, casting, forging, additive manufacturing, PCB assembly, and wire harness manufacturing.

The AI generates 3-8 failure mode suggestions per process step, each with a complete failure chain: failure mode, effects at three levels (local, next-higher, end-user), root causes, recommended prevention controls, and recommended detection controls. Terminology matches what practitioners actually use — ‘insufficient nugget diameter’ rather than ‘weld quality issue.’

AI suggestions appear in a review panel alongside your FMEA. For each suggestion, your team can:

**Accept**: Adds the failure chain to your FMEA with attribution (‘AI-suggested, accepted by [user] on [date]’).

**Modify and Accept**: Edit any field before adding. This is the most common path — the AI provides the starting point, your team refines based on your specific process context.

**Reject**: Dismiss with an optional reason. Rejection feedback improves future suggestions for similar processes.

**Flag for Discussion**: Bookmark the suggestion for your next FMEA team session when the full cross-functional group is present.

The AI does not assign final S/O/D ratings, make risk acceptance decisions, or bypass team review. It accelerates the brainstorming portion of FMEA sessions — typically the most time-consuming part.

On higher tiers, AI suggestions incorporate your organization’s own failure mode library and historical FMEAs from similar processes. The more FMEAs your organization builds, the more relevant the AI suggestions become for your specific manufacturing environment.