AI Station
AI Station Line

See why your line is behind target, and what to fix first.

AI Station Line connects the machine events, production counts, scrap and downtime records you already collect. It ranks your losses by impact and explains the likely cause in language your supervisors can act on.

Shift replayLine 3, Tuesday shift B
Sample data
Shift time14:00
Availability79.6%
Performance96.3%
Quality97.4%
OEE74.7%Target 75%
C/OC/OC/O
Pattern found

6 of 8 filler jams this shift started within 20 minutes of a changeover. Check the guide-rail settings on the station 2 changeover checklist.

Add to maintenance listShow the 8 jams
Illustrative example: an 8-hour shift timeline showing running time, three changeovers, 8 filler jams and two slow-running periods. OEE is 74.7% against a 75% target. 6 of the jams started within 20 minutes of a changeover.

What it is

AI Station Line is production-loss and OEE (overall equipment effectiveness) software for small and mid-sized plants, starting with food and packaging. It reads your existing data without changing anything, finds the losses that cost the most, and recommends what to fix first. It never controls machines.

What it does

One workflow, handled end to end, with your team approving the result.

Loss breakdown by line and shift

Availability, performance and quality losses in one view, comparable across lines, shifts and products.

Fix-first ranking

Losses ranked by minutes and dollars, so the weekly meeting starts with the one that matters most.

Root-cause suggestions

Finds patterns people miss, such as jams that cluster after changeovers or one shift's slower ramp-up.

Works with imperfect data

Handles free-text downtime reasons, missing codes and handwritten sheets that have been typed up.

Shift handover summaries

A short written summary of what happened, what's still open and what to watch next shift.

Room to grow

The same data foundation extends into maintenance, quality and energy once the first win is proven.

Connects to what you already use

No rip-and-replace. Line reads from your current systems.

  • PLC and SCADA exports (CSV)
  • Historian data
  • MES or ERP production records
  • Downtime spreadsheets
  • Quality and scrap logs
  • Maintenance work orders (CMMS)

Read-only. If your downtime isn't digital yet, we start with the sheets your supervisors already fill in.

How the pilot is measured

Top-loss minutes per week and OEE on the pilot line, measured before and during the pilot.

Pricing model: Monthly subscription per plant, plus a one-time integration and setup fee. Pilots are paid, fixed-scope and quoted after the discovery call.

See how pilots work

Is it a good fit?

Built for

  • Plants with 1–10 lines and no data science team
  • Food, beverage and packaging operations with older equipment
  • Teams that log downtime but can't tell what to fix first
  • Managers who want a weekly answer, not another dashboard

Not built for

  • Closed-loop machine control or automatic setpoint changes
  • Enterprises already running a full MES analytics suite
  • Sites with no production records at all (we'll suggest where to start)

Questions about Line

Other products

  • AI Station Supply: material shortage and supplier delivery tracking for plants and distributors
  • AI Station Dispatch: ai dispatching assistant for 5–50 technician service companies
What is OEE?

Overall equipment effectiveness compares what a line actually produced with what it could have produced in the planned time. It multiplies three ratios: availability (running time versus planned time), performance (actual speed versus ideal speed) and quality (good units versus total units).

Do we need to install new sensors?

Usually not. Most plants already have enough data in machine logs, production counts and downtime sheets to find the biggest losses. Sensors can come later if a specific question needs them.

Will AI Station Line change machine or PLC settings?

No. It is read-only and advisory. It never writes to PLCs, SCADA or any control system.

How quickly will we see results?

Most of the value comes from the first clear ranking of losses. Pilots are designed to show a measurable change within 30–60 days.

Our downtime reasons are inconsistent. Is that a problem?

That's normal, and it's one of the things the AI is good at. It groups free-text and inconsistent reasons into a short list you can act on, and shows you which codes to clean up.

Run a Line pilot.

Tell us about the problem in a few sentences. We reply within two business days.