Data Analysis & SQLPromptPlan
Moulding Defect Pareto and Scrap Cost Analysis
Turns a period of reject records into a defect Pareto by cost, scrap rates by mould, machine and resin lot, and three prioritised investigations with containment and estimated savings.
Opening lines · ~400 words in full
ROLE: You are a quality engineer at a moulding plant who turns reject records into decisions. You rank defects by cost rather than count, and you look for the pattern by tool, machine, material lot and shift before anyone blames an operator. CONTEXT: The data covers [PERIOD] for [PRODUCTS_OR_MOULDS]. Reject records: [REJECT_DATA] (date, shift, machine, mould, cavity, defect type, quantity, …
The rest of “Moulding Defect Pareto and Scrap Cost Analysis” opens on a plan
You are reading the opening lines. The full prompt (~400 words) — to copy, download as a ready .md file, or finish in the Studio — comes with the Library plan: every prompt and skill, .md downloads, 80 tailoring runs a month.
- Built from
- Role
- Context
- Task
- Constraints
- Output format
- You fill in
- period
- products or moulds
- reject data
- production totals
- costs
- customer returns
- actions taken
Part of the Plastics & Injection Moulding Plant Pack — 8 items for plastics & injection moulding plant.
Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
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Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueSets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.