Applied engineering, Pittsburgh PA
We wire AI into the machines you already run
Ironwald Systems builds machine vision, predictive maintenance and robotics for mid-size manufacturers across the Ohio Valley — no rip-and-replace, no year-long rollout.
LINE 3 — DOWNTIME LOG, ROLLING 90D
−31%
Unplanned stoppages after a vibration-sensing model went live on the stamping line.
37
plant deployments since 2021
92%
of pilots reach full production
9
states served from our shop floor
8 wks
median time to first working system
What we build
Three disciplines, one install
We don't sell a platform. We diagnose the bottleneck on your floor and bring the smallest combination of these three that actually fixes it.
Predictive models
Failure prediction, demand forecasting and quality scoring trained on the sensor and ERP data your team already collects — no new hardware required to start.
See predictive work →Vision-guided robotics
Pick-and-place cells, defect inspection cameras and cobot integration tuned to your existing line speed, not the vendor's demo speed.
See robotics work →Floor-level analytics
Dashboards that sit next to the line, not in a quarterly deck — anomaly flags, OEE tracking and alerts your operators will actually check.
See analytics work →Where it's running
Built around your sector's failure modes
A vibration signature means something different on a press line than it does in a cold-storage warehouse. We tune every model to the way your sector actually breaks.
STAMPING & WELD CELLS
Metal fabrication
Vibration and thermal sensors on press and weld cells flag bearing wear and die misalignment days before a breakdown, so changeovers get scheduled instead of forced.
Talk about a fab lineFILL LINES & COLD CHAIN
Food & beverage
Fill-weight vision checks and cold-chain temperature models cut giveaway and catch refrigeration drift before product is at risk, with alerts routed to whoever's on shift.
Talk about a fill linePICK, PACK & SLOT
Warehousing
Slotting models and vision-guided picking reduce travel time and mis-picks, tuned to your actual SKU velocity rather than a generic warehouse layout.
Talk about a DCJIT & QUALITY GATES
Auto suppliers
Surface-defect cameras at quality gates and JIT demand models keep sequencing tight enough to meet OEM delivery windows without over-building buffer stock.
Talk about a supplier lineProof, not promises
Three lines, three fixes
Real numbers from real plants, measured the same way we'll measure yours: before, after, and what it took to get there.
Unplanned downtime, stamping line
Vibration sensors and a failure-prediction model on an 11-press line in Aliquippa.
"We schedule the fix now instead of firefighting it." — Dana R., plant manager
Faster defect detection, fill line
Vision inspection replacing spot-checks on a beverage co-packer's fill line.
"Rejects get caught at the camera, not by a customer." — Priya M., QA lead
Fewer mis-picks, 3PL warehouse
Slotting model and pick-path guidance across a 140,000 sq ft distribution center.
"Our new hires ramp in days, not weeks." — Tomas B., ops director
How an engagement runs
Four stages, visible metrics from week one
We size every stage to your plant, not to a standard package — but the sequence itself doesn't change.
STAGE 1
Walk the floor
Two engineers spend a day on your line, pull a week of existing sensor and ERP data, and name the three bottlenecks worth solving.
STAGE 2
Prototype the fix
We build a working model or cell against your real data before you commit to hardware, and show you where it's wrong as well as where it's right.
STAGE 3
Install & train
We install alongside your maintenance and operations teams, and hand over runbooks written for your shift, not our engineers.
STAGE 4
Tune in production
Thirty, sixty and ninety days out, we re-check the model against drift and retrain it against what your line actually does.
Who shows up
Engineers who've run a shift
Every lead on an Ironwald engagement has spent time on a factory floor, not just in a notebook.
Marcus Okonjo
Head of Applied AI
Ten years building predictive maintenance models for steel and stamping plants before co-founding Ironwald.
Renata Vosk
Head of Robotics
Leads vision system and cobot integration, with a background in automotive quality-gate engineering.
Dale Feringer
Director of Deployment
Runs every install and training handoff, keeping scope, schedule and shift training aligned with the client.
We picked Ironwald because they showed us the downtime numbers before they pitched us any hardware. The plan was specific to our line, and someone from their team was on-site through the whole cutover.
— Howell Straka, operations manager, Three Rivers Metal WorksBefore you call
Common questions from plant managers
Rarely. Most projects add sensors, cameras or a model on top of the machines you run today. We only recommend new hardware when the current equipment genuinely can't be instrumented.
The floor walk and prototype typically take two to three weeks. Most clients have a working system in production within eight weeks of kickoff.
You do. We hand over the trained model, the pipeline and documentation at project close, and your team can run it without us if you choose to.
No. We build the interface around the alerts and dashboards your shift will actually use, and train your team on those, not on the underlying model.
The floor walk is a fixed fee. From there we quote the prototype and install as a project, scoped to the specific line — never an open-ended retainer.
Ready to see what's costing you the most?
Book a floor walk and we'll tell you, in writing, which bottleneck to fix first — before you sign anything.