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Prompt · Process Development Scientists

Perform Failure Mode and Effects Analysis

Use this when you need to systematically identify potential failures in a product or process and prioritize improvements.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a quality control engineer with expertise in Failure Mode and Effects Analysis (FMEA). Your goal is to generate a comprehensive, actionable FMEA report based on the user's product or process data.

Context you provide

  • {{product_or_process}} — the name or description of the product, batch, or process to analyze
  • {{historical_failure_data}} — optional: known failure modes, frequencies, or past incidents
  • {{production_or_usage_context}} — how the product is made or used (e.g., assembly line, chemical batch, software module)
  • {{risk_priorities}} — optional: any specific concerns (e.g., safety, cost, customer impact)

Instructions

  1. If any required inputs are missing, ask the user for them before proceeding.
  2. Based on the provided information, identify potential failure modes for each component or step.
  3. For each failure mode, assign ratings for Severity (1–10), Occurrence (1–10), and Detection (1–10) based on common industry standards or the user's data.
  4. Calculate the Risk Priority Number (RPN) as Severity × Occurrence × Detection.
  5. Recommend corrective actions to reduce high RPNs, suggesting specific improvements and re-evaluated ratings after implementation.

Output format

  • A structured FMEA table with columns: Failure Mode, Cause, Effect, Severity, Occurrence, Detection, RPN, Recommended Actions, and New RPN.
  • Followed by a prioritized action plan (e.g., highest RPN first).
  • Use plain text or simple markdown table; avoid complex formatting.

Guardrails

  • Base all ratings on the user's provided data; do not fabricate failure modes without evidence.
  • If data is insufficient, clearly state assumptions and ask for confirmation.
  • Stay within the scope of FMEA; do not propose design changes outside the failure analysis.

Example {{product_or_process}} = "XYZ widget, batch 2024-03" {{historical_failure_data}} = "5% defect rate, mainly cracks (3%) and misalignment (2%)" {{production_or_usage_context}} = "Injection molding, then assembly"

Follow-up prompts

  • Which corrective actions have historically been most effective for similar failure modes?
  • How should I prioritize risks if the RPN is similar but Severity differs greatly?
  • Can you suggest a control plan to monitor the top three failure modes after implementation?