APMS.ai is a manufacturing data analytics plugin. It connects ChatGPT to your factory's APMS machine-monitoring data and answers questions about production, downtime, OEE, machine health and scrap with figures and charts.
Sign in with your existing APMS account and choose one production unit. Every answer covers only the machines your account can already see in APMS for that unit. To look at another unit, connect again and choose it.
What you can ask about:
- Live status: which machines are running, stopped or waiting right now
- Production: output against target, pace and shift-wise performance
- Downtime: top stop reasons, durations, recurring patterns and recent stops
- OEE (Overall Equipment Effectiveness): availability, performance and quality per machine
- Machine health parameters: current values with units, safe / reserve / critical limits, and how long a parameter has been out of range
- Stoppage forecast: likely stops for running machines or tomorrow's planned jobs, based on each machine's own history, with preventive actions
- Scrap and raw material: scrap as a percentage of raw material used
- Quality, rejections, alarms, maintenance and reliability (MTBF: mean time between failures; MTTR: mean time to repair)
- Operators: attendance, performance and PRR (Performance, Reward and Recognition) scores
- Job sheets and products
Answers include charts where useful, and you can export the underlying data or create a PDF report.
APMS.ai only reads data. It cannot start, stop or change machines, settings or production records.
Requirements: an active APMS account with access to at least one production unit. Periods follow your plant's own shift timings and time zone. You can disconnect at any time from ChatGPT settings.
How to use
- 1Add it in ChatGPT
Open APMS.ai in ChatGPT's Plugin directory (button above), select + to add it and sign in if asked.
- 2Use it in a chat
Type @ in the composer and pick APMS.ai, or start your message with its name. ChatGPT may also suggest it when it fits what you ask.
Things to ask
- “How many machines are running right now, and which ones are stopped?”
- “What were the top downtime reasons this week?”
- “Which machines are likely to stop tomorrow, and what can we do to prevent it?”