The Question
Case study · Food manufacturing · Packaging lines
Client's brief · reconstructed excerpt · values held in confidence
(withheld), a leading spice manufacturer, packs on 700 to 800 lines across a global network and wants fewer sites doing the packing. One facility could take volume from others, if its lines can absorb it. A consolidation costs money before it pays: severance, equipment relocation, and decommissioning are booked up front, and the savings arrive only if the receiving line keeps up. The lines differ in fill sizes, container formats, and run rates, floor space at the receiving site is tight, and the fourth quarter, when holiday baking pulls demand forward, is when a shortfall would show. The company needs the answer before it moves a line, and a way to ask the same question about the next site.
Bars cover values SimWell holds and is not releasing. The released figures stand as printed.
§ 1
Rated capacity assumes the line runs the whole shift on one product. A consolidated line runs more SKUs, and every switch between fill sizes, containers, and labels is time it packs nothing. Stoppages, off-shift hours, and waits for material take more. On high-mix food packaging lines, changeovers are often the largest loss the plant controls, and they grow with every SKU a line takes on. A spreadsheet spreads those losses evenly across the year. The shortfall shows up in the weeks they stack.
§ 2
By tracking every line through five states: running, changeover, downtime, off shift, and idle. SimWell built the model in AnyLogic with line data, schedules, and run strategies loaded from CSV, so the same model stands in for any of the 700 to 800 lines without a rebuild. Each consolidation scenario reports what the planners had to weigh: throughput rate, cost per unit, and inventory levels.
Representative model. Lines, volumes, and schedules are illustrative, not client data.
§ 3
Which line takes the volume, how it runs, and what it carries. Parameter variations put the consolidation options side by side, so the team could see how much extra volume a given line absorbs before output slips, where cost per unit and inventory move, and which run strategy keeps downtime lowest on each line. The model showed what each option would do, and the company's team made the call.
Cleared for release
The company consolidated volume onto a specific packaging line, and the consolidation delivered a 35% increase in return on investment.
The model stays with the company, configured for its own network, so the next consolidation question starts from a working model of any line it runs.
SimWell helps operators make better decisions under uncertainty. We build simulation and optimization models that reflect operational reality, test scenarios before committing resources, and transfer capability so teams can run decisions independently.
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