A Brewpub Plans Kegging and Bottling
The Tanks, Not the New Lines, Set the Limit

A brewpub wants to add kegging and bottling equipment to sell its beer off-premise, and it expects sales to grow, which means significant capital. A model of the brewery shows that either line would overrun the fermenting and serving tanks unless more tank capacity goes in too. After comparing several simulated scenarios, management is more confident about the return on the investment.

The business

A brewpub with its own brewhouse, fermenting and serving tanks

The question

Can the brewery keep up if it adds kegging or bottling, and is the capital worth it?

The model

Bulk flow through every tank, with ale and lager times and costs tied to each change

What it is worth

Found the tank shortfall before the purchase; more confidence in the return

Source

Published paper, Andrew J. Siprelle, Simulation Dynamics

What the brewery is up against

Craft brewers often start as brewpubs, selling on the premises for a quick return. As they succeed, they add kegging and bottling to sell their own brands off-premise, and some take on contract brewing for other breweries. Growing that way calls for a more flexible operation that can switch quickly between flavors and packages.

Beer moves through a chain of tanks. Grain and hot water are mashed in the mash/lauter tun, and the wort goes to the kettle for hops and a boil, then to a whirlpool to clear out solids. It’s cooled through a heat exchanger into one of several fermenting tanks. After fermentation the yeast is blown down, and the beer ages in the same tank for days. It’s then filtered into a serving tank that feeds the bar, a kegging line or a bottling line.

Each beer spends very different amounts of time in those tanks. Ales ferment for about 5 days and age about 5 more. Lagers ferment for about 10 days and can age for as long as 14. In this brewpub about 18 barrels of wort go into the kettle, and about 14.5 barrels reach a serving tank after evaporation.

The schedule has to meet demand and fit the labor available. It also has to keep each beer separate and leave time to sanitize the pipes and hoses between them. Adding kegging and bottling makes that puzzle harder. The brewery needs answers to five questions:

• Can the brewing equipment keep up with both off-premise and on-premise sales?
• Is it wise to spend capital on kegging or bottling?
• How should labor be scheduled for brewing, kegging and bottling?
• What’s the best sequence for the different flavors?
• How much extra storage is needed for kegging and bottling?

How it is modeled

Beer is a fluid, so the model tracks rates of flow and tank levels rather than individual items. Pumps, tanks with setpoints and branching paths define the routes. Control logic attached to each tank chooses which tank to fill or draw from, shuts off flow for schedules, maintenance and changeovers, and holds beer for its fermenting and aging time. This rate-based approach keeps a bulk process model fast enough to run many scenarios.

A database inside the model ties each beer to its process data, and a central control panel sets up and runs the experiments. Adding another fermenting or serving tank is a matter of dropping in one more block. Cost and revenue are linked to the process changes, so each scenario shows its financial result along with its operating one.

What the model shows

The new kegging and bottling equipment, together with the expected sales growth, needs more storage than the brewery thought. The brewing steps in the mash/lauter tun and kettle are short. Fermenting and aging take so much longer that the brewery would need more fermenting and serving tanks to keep serving a variety of beers.

That’s hard to see by looking at the plant, where the lines under discussion look like the equipment that will decide throughput. The model shows that the time beer spends in tanks sets the limit.

What changes

The capital plan has to cover more fermenting and serving tanks, not only the packaging lines. Because the model ties cost and revenue to each change, management can compare the financial and operating results of several scenarios before spending. In the paper’s account, that leaves management more confident about the return on the investment. Testing a capital plan this way is what capacity planning simulation is for.

Where this work comes from

Built by Simulation Dynamics, the team behind ReliaSim®, using the rate-based method ReliaSim is built on. The bulk flow blocks come from several years of modeling in food and consumer products, adapted for this brewery. Evidence: Modeling a Microbrewing Facility Using Discrete Event Simulation (PDF), Andrew J. Siprelle, Simulation Dynamics, Inc.