Digital twin
OEESCRAPENERGY
Industrial example

A bottling line, piece by piece.

Shift OEE, stops and scrap by cause, energy per machine, recipes and changeover, condition-based maintenance and the end-of-shift forecast. Simulated data; one second is one minute. Try stopping a machine.

With AI predictive analytics estimates batch end, recognises recurring micro-stops and anticipates failures before they stop the line.

Loading the digital twin…
Bottle infeed—
Filler—
Capper—
Labeler—
Inspection—
Shrink packer—
Palletizer—
Line 2 · — · simulated data · —
In production—Recipe — · batch —
Next—
Shift OEE—
Availability —Performance —Quality —
Good pieces——
Speed——
Scrap——
Energy——

Machines

Every machine is a plant model: states, counters, stop causes, ready-made tags, pages and rules. The Andon light in the 3D view shows the same state.

Stops this shift

    —

    Scrap by cause

      Scrap is ejected by the pusher after inspection: you can see it land in the orange bin.

      Energy per machine

        The shrink tunnel stays hot even during short stops: it's the biggest item when the line is down.

        Condition-based maintenance

          Production order

          From the ERP—
          —
          Production reports to the ERP
          —
          Pallets completed
          —

          Orders, batches and production reports go through Studio's REST API.

          Shift production · good pieces, now and end-of-shift forecast

          Good piecesShift targetForecast▶ running ‖ minor stop ■ breakdown ⟳ planned

          Expected plan

          Formats, changeovers and cleaning as scheduled; maintenance is what the counters recommend.

          Forecast

          The plan with the line's average performance: minor stops and scrap at historical rates.

          Good pieces forecast per hour

            What the Industrial vertical does

            States, stops and OEE by machine and by shift, with the Andon page and stop causes.

            Process recipes: format, product and batch, with approved versions and guided changeover.

            Condition-based maintenance: hours, cycles and thresholds, with the intervention recommended before the failure.

            Quality and traceability: scrap by cause, batches and orders linked to the pieces produced.

            Energy: energy per machine and kWh per 1,000 pieces, by shift and by batch.

            ERP/MES integration: incoming orders and outgoing production reports with Studio's REST API.

            Let's bring your line
            to these numbers.