INDEPENDENT COUNT · TRAINING LAB

Bar Station Trainer

Practice the decisions that reduce unnecessary bar movement. Train in 3D

Module 1 — Build the station

The orders stay fixed. Build the well AND back bar, and arrange movable equipment around the installed fixtures.

Station layout · 12 speed-rail positions

Select or drag a bottle to a well or back-bar position. Bottles have fixed sizes; only those up to 85mm fit the well. Select a filled well position to return it to a free back-bar position.

GLASSES
ICE
MIXERS
POS
Every bottle has an explicit well or back-bar homeBartender faces this rail

Back bar · explicit shelf positions

Movable work equipment

Available spirits

Same orders · before and after

Work time—
Distance walked—
Back-bar fetches—
Run the workload to create a baseline. Change one placement and run it again.
Movement replay map appears after simulation.

Demand briefing

Illustrative shift demand. Each scenario uses an identical order manifest across all layout attempts.

Demand is synthetic and should be replaced with validated POS counts for actual operations.

What to learn

Rail positions are scarce. Prioritize often-used spirits, but consider where ice, glassware and mixers are located.

A fast placement is not merely the bottle nearest the center: each drink causes a particular sequence of movements.

Challenge: Beat your first layout with the same orders. Try moving one heavily used bottle at a time.

Module 2 — Sequence the drinks

The station stays fixed. Reorder preparation tasks to reduce repeated visits and unnecessary walking.

Four tickets · one workload

Demonstration tickets. Recipe correctness, pour quantity, and ingredient identity are held constant.

Arrange the work

Use arrows to reorder tasks, then simulate. Precedence requirements are enforced; invalid sequences cannot run.

Workflow analysis

Elapsed work—
Travel distance—
Zone changes—
Run the baseline, then move tasks. Compare with the best-found sequence.
Work sequence path will appear here.

Why order matters

Getting every glass, icing them together, and completing repeated pours may reduce duplicated visits. But not every reorder is valid, and the shortest path is not always acceptable.

The learning target is the most efficient valid sequence—not skipping a task or compromising the drink.