Case studies
How We Work
Five projects, described the way an engineer would want to read them: what was actually wrong, what we measured, what we designed, and what we put in writing. Four are delivered or in commissioning; the fifth is in build, and is labeled that way. Clients anonymized — see the note at the bottom.
Innovate · Specialty producer industrializing a process nobody had automated
1. De-Risking a $2M Production System With Structured R&D
The problem
This product had only ever been made in small batches, slowly, by people. Nobody had industrialized the process — there was no equipment on the market for it, and the obvious approach produced output that failed inspection. The insight that unlocked it: the critical variable wasn't the setpoint everyone had been chasing. It was precise control over the rate of change on the way there.
Our approach
Two structured R&D phases — prove feasibility on a bench rig first, then scale to a production-size rig. Off-the-shelf process controllers could not hold the ramp rate the process actually needed, so we built a custom PLC-based control system that could, and instrumented it so every run produced data rather than an opinion.
The result
27 documented test runs. Cycle time came down from 8+ hours to a measured 4.75-hour minimum, 5.2 typical — the single number that decided whether the economics worked. Full electrical load characterized at 203 A / 480V three-phase. Output met spec consistently across every run once the custom controls were in. The R&D program then informed a $2M production system design carrying a written performance guarantee — which is the entire point of doing R&D first.
Related: Why process comes before equipment
Project at a Glance
- Pillar
- Innovate → Production
- Location
- Texas
- Scope
- Two phased R&D programs
- Test runs
- 27 documented
- Cycle time
- 8+ hr → 4.75 hr measured
- Outcome
- Production system design with written performance guarantee
- Status
- In commissioning

Innovate → Build · Plant-based food startup with a recipe and no production path
2. From Squirt Bottles to 10,000 Strips an Hour
The problem
The product existed as a recipe and a hand process — batter squeezed from squirt bottles onto a plate. No machine on the market made it, and the batter was non-Newtonian, so it behaved nothing like the fluids standard depositing equipment is built for. The company was launching a business and needed a path from that plate to sellable volume, without betting the company on equipment sized for a future it hadn't reached yet.
Our approach
We developed a novel depositing technique for the batter, proved it, and built a pilot machine sized to the volume they actually had rather than the one they hoped for. Then we iterated — three generations of machine, roughly 16 weeks each, scaling up as the recipe firmed up. Because the recipe kept moving, the machine had to move with it: later generations added automated cleaning and were re-engineered around how the co-manufacturer actually ran it, not how we assumed they would.
The result
A production machine running 10,000 strips per hour, installed and operating in the co-manufacturer's plant. Each generation was designed from what the last one measured, so the company scaled its equipment at the pace it scaled its sales — which is the whole argument for starting smaller than you think you need to.
Related: Why process comes before equipment
Project at a Glance
- Pillar
- Innovate → Build
- Location
- California, then Illinois
- Scope
- Three machine generations
- Duration
- ~16 weeks per iteration
- Hard part
- Depositing a non-Newtonian batter
- Output
- 10,000 strips per hour
- Operated by
- The client's co-manufacturer

Scale · Mid-market refrigerated foods manufacturer, two facilities
3. Finding the Real Bottleneck Before Buying Equipment
The problem
The client needed to hit 280,000 lb/day for their next season and was ready to buy another filler to get there. Their internal capacity model assumed 95% OEE.
Our approach
A station-by-station Theory of Constraints analysis across the entire line. The bottleneck wasn't the filler — it was the chill loop. Batch-mode chillers ran at 96 cups per minute while the six-lane filler rated at 120 cpm sat idle waiting on them. We decomposed true OEE: roughly 75% availability × 82% performance × 95% quality — about 58% actual, against the 95% assumed.
The result
A path that moves the bottleneck to 200 cpm and roughly 270,000 lb/day, with the sensitivity levers quantified: one added hour per day is worth 13,500 lb, each OEE point worth 3,600 lb. And the filler they were about to buy turned out to be sitting in their own facility already — not a buy decision, an integration decision. We also found a gas-rate reclassification worth $3,500–$10,700 a year with no capital at all.
Related: How our capacity assessment works
Project at a Glance
- Pillar
- Scale
- Location
- Colorado
- Engagement
- $28,000 fixed price
- Duration
- 2–3 weeks
- Method
- Theory of Constraints, station by station
- Found
- True OEE ~58% vs. 95% assumed
- Avoided
- Buying a filler they already owned

Build · Equipment OEM — high-precision dosing systems for the cannabis industry
4. Twenty Machines, One Repeatable Build
The problem
A proven design for a high-precision dosing system — the kind where dose accuracy is a regulatory matter, not a preference — had to become twenty identical delivered units, with consistent quality and predictable per-unit cost. That is a fundamentally different engineering problem than building the first one.
Our approach
Production engineering, procurement, build scheduling, and QA across the full run in our own shop. Fixturing and work instructions built for repeatability rather than one-off craftsmanship.
The result
20 machines delivered on a $300,000 contract, with per-unit repeatability holding at 22.7 labor hours and $8,956 in materials per unit. Across four production runs for this client, 52 machines delivered in total.
Related: How we build production multiples
Project at a Glance
- Pillar
- Production
- Location
- Colorado
- Machine
- High-precision dosing system
- Contract
- $300,000
- This run
- 20 identical machines
- Per unit
- 22.7 labor hours
- Materials
- $8,956 per unit
- Program total
- 52 machines across 4 runs

Build · Condiment manufacturer — fourth engagement with this client
5. Sized to Your Data, Not Our Catalog
The problem
Caps were losing about five degrees of torque traveling through the dryer before the induction sealer, putting seal integrity at risk across 3,000 cases per twelve-hour shift. An operator was retorquing every jar by hand.
Our approach
We proved the clamp design on 100 of the client's own sample jars, on our shop test conveyor, before the 50% design review — because a cap retorquer that works on paper and slips on real glass is worthless. Then we sized the machine to their measured shift average rather than their nameplate ambition.
The result
This one is still in build, so here is what is committed rather than what is proven. A 35 jar-per-minute design basis against a 25 jpm shift average, with roughly 47 jpm machine capability — 34% headroom. Acceptance criteria written into the contract before work started: 30 minutes continuous at rate with the count logged from the PLC, and removal torque within ±10% across a 30-jar sample. It is done when it passes that, and not before — which is the only version of “done” we will put our name on. We had quoted this client two machines previously and told them both were wrong — one too slow, one too big.
Project at a Glance
- Pillar
- Build
- Location
- Florida
- Status
- In build — not yet installed
- Design basis
- 35 jars/min sustained
- Capability
- ~47 jpm — 34% headroom
- Torque window
- ±10% across a 30-jar sample
- Acceptance
- Written before design began
- Relationship
- 4th engagement

A note on what you don't see here
Most of our work is under NDA — proprietary processes, first-of-kind equipment, and products that aren't public yet. So we show our own engineering and our own shop rather than our clients' floors. If your process is worth protecting, that's part of why clients hire us.
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