Simulation for Packaging & Consumer Products
Five Good Machines Don’t Make a Good Line
A packaging line is a series. The filler, capper, labeler, case packer and palletizer can each hit their targets while the line still misses badly. What matters is how their stoppages interact, not how each machine performs alone. The arithmetic is harsh, and it's why so many well-run CPG lines sit far below the number their machine reports suggest.
The arithmetic nobody likes
85% OEE is the world-class benchmark, and it's a single-machine benchmark. Put five machines at 85% in series with no buffering between them and the line comes out near 44%, even though nothing has gone wrong.
Buffering, sequencing and constraint management exist to recover that gap. How much you can recover depends on which machine stops, for how long, how often, and what's sitting between it and its neighbors. Those are dynamics, not averages, so a spreadsheet can't answer it.
Is 85% OEE achievable on your line? works through the arithmetic in full.
What makes CPG lines their own problem
Making and packing keep different time
The upstream process is continuous or batch, while packaging is a series of discrete machines. They rarely want to run at the same rate, so the surge capacity between them is the main design question. Too little and the making process stops, and that's usually the expensive end. Too much and you've paid for storage that buys nothing.
SKU count multiplies changeovers
Every size, format, label and allergen sequence adds changeovers, and changeovers interact with everything else. A schedule that's efficient for one product mix can be badly wrong for another. When the mix moves, the constraint can move with it.
Micro-stops beat rare long ones
A stoppage measured in seconds looks negligible on a loss report. On a tightly coupled line it never lets buffers refill, so its cost is carried all the time rather than now and then. Eliminating it can return much more uptime than its recorded downtime suggests. It's the most common misranking on a CPG loss tree.
Rework and reblend make storage circular
Material re-introduced into the process is good economics and terrible for capacity planning, because the flow into storage is no longer just the making rate. Scheduling changes the recycle volume, the recycle volume changes the storage requirement, and the storage requirement constrains what can be scheduled.
All four lead to the same result. The loss report ranks by minutes lost, the plant funds the top of that list, and the throughput doesn't come back. What you want ranked is recoverable throughput, meaning what the line actually returns when a failure mode is removed. That's a different number and often a different order.
Who has used it
Unilever · Estée Lauder · Rich Products · ConAgra · Hormel · Pitney Bowes · Hewlett-Packard
Packaging and consumer products work on this site
$1.5M in hidden throughput
A filler, capper, labeler, case packer and palletizer line. Two failure modes had near-identical downtime, and removing the smaller one returned 62% more.
Read the case study → Consumer ProductsThe $4M retrofit that was never built
Consolidating multiple plants across 300+ products. The model sized the surge between processing and packaging and caught a configuration that would have created a quality problem.
Read the case study → Consumer ProductsToo little storage stops the expensive end
In-process storage that moved with scheduling rules and reblend volume. Re-implemented at 12+ similar factories.
Read the example → Make-Store-PackThe Shifty Bottleneck
Changing the packaging size moved the constraint, which defeats any planning system optimizing against a fixed bottleneck.
Read the example →A free line assessment, this fall
Bring one question about your line. We model it on your own data and send back a two-page readout in about five business days.
Apply for a free line assessment →Or explore the Sandbox first, with no sign-up.