Planning · Integrated · Optimized

Better planning.
Better production.

Automated production planning for the beverage industry, built on a digital twin of your plant.

Lots of raw materials, multi-stage processes and one-off products. That calls for a plan you can build and rebuild fast.

Problem

Planning beverage production is uniquely hard.

Variety & batch sizes

Hundreds of SKUs, recipes and pack formats compete for the same tanks and lines, each with its own batch size and changeover.

Volatile demand

Seasonality, promotions and short-notice orders move the target every day. A plan can be outdated the moment it is finished.

Cross-department dependencies

Processing, blending, filling, warehouse and purchasing are tightly coupled. A change in one ripples through all of them.

Knowledge-dependent planning

The plan often lives in the head of one experienced planner. When they are away, quality and speed go with them.

These don't resolve in isolation. Only a holistic model of the plant resolves them together.

Solution

From data to decisions, automatically.

01

A digital twin

One living model of your plant: its processes, resources and constraints, in sync with reality. Expertise that used to live with a few key people becomes structured and easy to trace.

02

Optimization & simulation

Optimization searches millions of options for the best plan. Simulation tests every change risk-free, so you see the what-if long before it reaches the floor.

03

Decision proposals

Clear, ready-to-run plans for every department, each with the reasoning behind it. When something shifts, you re-plan in minutes rather than days.

One connected cycle. Model, optimize, decide, then re-run it whenever something changes.
LOOP

Optimization loop

1Digital twin2Optimize3Decisions
TWIN

What the twin captures

Processes

Processing, blending, conditioning, filtration and filling, with their durations, sequences and dependencies on one another.

Resources

Tanks, lines, staff and materials, each with its own capacity, availability and shift pattern.

Constraints

Shelf life, changeovers, cleaning windows and delivery dates, plus the quality rules every plan has to respect.

NETWORK

One model for the whole production network

Raw materialsProcessingBlendingConditioningFiltrationFillingWarehouse
MODULES

A filling core, plus the modules you need

FillingCore
CellarPlug-in
Tank managementPlug-in
PurchasingPlug-in
LabPlug-in
WarehousePlug-in
Managerial insightsPlug-in
Demand planningPlug-in

We model only what matters for planning. Which modules you switch on depends on your processes and your data.

Outcomes

Plans you can execute, at lower cost and less effort.

Cost-minimal plans

The optimizer searches the whole solution space for the cheapest plan that still meets every constraint.

Less planning effort

Hours of manual scheduling turn into a single automated run you can rely on.

Lower operating costs

Smarter sequencing trims changeovers, waste and overtime across the line.

Higher utilization

Lines, tanks and crews run closer to their real capacity, with less idle time.

Fast reaction to change

Re-plan in minutes when demand jumps, a machine breaks down or supply slips.

Stable, person-independent

Planning logic lives in the model, not in one person's memory, so it holds when they are away.

About

A boutique consultancy where method meets implementation.

Some problems are too complex for off-the-shelf tools. We find the structure underneath and build what actually fits, handling analysis, modeling and implementation in one place. Beverage is most of what we do, but not all of it: we also plan crowd flow and large-scale warehouse logistics.

PhD-level mathematicians, computer scientists and engineers with more than 30 years of combined experience. We spun out of the University of Hamburg, are based there, and belong to the Hamburg Analytics Network .

How we start, low-risk

01

Scoping

Define the planning problem and the value at stake together, in days.

Decision point
02

Data

Connect the data that already exists and check it is enough to model the plant.

Decision point
03

Feasibility / MVP

Prove the optimization works on your real plant with a minimal twin.

Decision point
04

Pilot & Go-Live

Run it in production, measure the gains, and scale module by module.

Decision point

Plan your production efficiently, with Planningio.

Booking a meeting is easy. At the push of a button, naturally.