Demand & Recipe Mapping
We ingest sales forecasts and map each product to its recipe, fermentation time, tank requirements, and packaging specifications.
Beer Production
The machine plan for when which machine does what, brewed to perfection.
Optimise brewery schedules to maximise throughput, minimise downtime, and ensure every batch is produced at the right time on the right equipment.
The Challenge
Brewery scheduling is complex, and spreadsheets do not scale.
Breweries juggle dozens of recipes across fermenters, bright tanks, filtration lines, and packaging equipment, each with different capacities, changeover times, and cleaning cycles.
When planning is manual, machines sit idle while others are overloaded, batches get delayed, and rush orders throw the entire schedule into chaos.
Idle machines
Equipment sitting empty while other lines are bottlenecked
Delayed batches
Production falling behind demand commitments
Changeover chaos
Unnecessary cleaning cycles eating into production time
No overview
No clear view of what runs where and when
The Approach
From demand forecast to optimised machine schedules.
Demand ForecastRecipe MappingMachine ConstraintsSchedule OptimisationChangeover MinimisationProduction Plan
Constraint Modelling
Model each machine's capacity, availability windows, cleaning requirements, and changeover times between different beer styles.
Optimised Production Plan
Generate a detailed schedule (which machine runs which batch, when) minimising changeovers and maximising overall throughput.
Outcomes
What optimised production planning delivers.
Higher throughput
More batches from the same equipment
Less downtime
Fewer unnecessary changeovers and cleaning cycles
On-time delivery
Production aligned with demand commitments
Full visibility
See the entire production plan at a glance
In Practice
What this looks like
Illustrative scenario
Belgian brewery
A Belgian brewery producing multiple beer types across a shared set of fermentation tanks was scheduling production manually. Tank assignments were based on experience and habit, which worked until demand shifted or a tank went offline, at which point conflicts cascaded through the week's plan.
RivNox modelled the brewery's tank compatibility rules, fermentation durations, and bottling constraints into an interactive simulator. Planners could test different tank assignment strategies side by side, seeing the impact on throughput, service levels, and safety stock before committing to a policy change.
8 policies
Compared in the same session
Zero risk
Policy tested before production change
Short PoC
From first meeting to working demo
Ready to optimise your brewery schedule?
Let's explore how an AI-driven production plan can help you get more out of your equipment.
Book a 30-minute discussion to see if there's a match