Plan your plant's holiday shutdown with AI

Turn your shutdown dates, open orders and maintenance list into a customer notice, a crew schedule and a shutdown maintenance checklist.

The problem

Most shops slow down or close between Christmas and New Year's. When the dates, last ship day and maintenance work aren't planned early, customers get surprised, rush orders pile up the week before, and the shutdown week passes without the repairs that were supposed to happen.

Step by step

1. 1Pick your shutdown dates, last day to receive orders and last ship date, and confirm them with your owner and lead customers.
2. 2Export your open orders and due dates, and list the maintenance or repair jobs that need the machines down (PMs, rebuilds, crane or forklift inspections, cleanup).
3. 3Paste the dates and lists into the prompt below (no customer names needed) to get a customer notice, a crew and on-call schedule outline and a shutdown maintenance checklist.
4. 4Have your maintenance lead check the checklist against the equipment manuals and your safety and lockout procedures before work is scheduled.
5. 5Send the customer notice in early November and post the crew plan, so people can plan time off and parts can be ordered in time.

Copy-paste prompt

I run a [type of shop, e.g., metal fabrication / machine shop] with about [number] employees. Holiday shutdown: [dates]. Last day to take new orders: [date]. Last ship date before shutdown: [date]. First ship date after: [date]. Open orders due near the shutdown: [paste list, no customer names]. Maintenance jobs that need machines down: [paste list]. Write: (1) a short, professional customer email announcing the dates, with a placeholder for [CONTACT NAME]; (2) an outline of who works, who is on call and who is off, by day; (3) a shutdown maintenance checklist grouped by machine, with a note to follow our lockout/tagout procedure; (4) a list of parts or contractors to line up now. Use only the dates I give; don't invent lead times or maintenance intervals.

Review AI output before using it. Don’t paste confidential, customer or patient data into tools your company hasn’t approved.

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