Find the set-points that pay you back.
What-if simulation and closed-loop optimization for parameters, schedules and energy. Recommendations come with predicted KPI impact, simulated before any change goes near the machine.
For
Optimization / Line 3
Recommendation · WO-2241 · stator winding
Maximize yield · subject to cycle ≤ 28s
Set-points
| Parameter | Current | Recommend | Δ |
|---|---|---|---|
| Wire tension | 12.0 N | 12.4 N | +3.3% |
| Spindle RPM | 1850 | 1820 | −1.6% |
| Bond pulse | 65 ms | 62 ms | −4.6% |
| Oven temp | 210 °C | 210 °C | 0 |
Predicted impact
Set-points drift. Tribal knowledge retires.
Most plants run on hand-tuned parameters that nobody dares change. The result: leaving yield and energy on the table. Optimization needs simulation, audit and operator buy-in — not a black-box recommendation.
Capabilities included.
Parameter optimization, energy management and machine data collection — with what-if simulation and closed-loop control where it's safe to enable.
Parameter Optimization
Recommend parameter set-points that maximize yield or minimize energy — with what-if simulation before any change goes live.
Energy Management
Monitor energy consumption per machine. Identify waste and optimize usage to reduce costs.
Machine Data Collection
Connect to any PLC or sensor using vendor-independent standard protocols. Centralize data for analysis and reporting without vendor lock-in.
From insight to set-point.
Define goal
Yield, scrap, energy, cycle time — set objectives and constraints in plain language.
Simulate
Models project KPI impact across set-points before any change touches the line.
Recommend
Operators see ranked set-points with predicted impact and the reasoning behind each.
Apply
Apply with approval, or close the loop on safe parameters. Every change is signed and reversible.
Outcomes that pay for the platform.
+5%
First-pass yield
Recommended set-points deliver measured yield gains within weeks.
−12%
Energy per part
Combined process and HVAC tuning, validated in simulation first.
−80%
Tuning time
Engineers go from quarterly DOEs to weekly improvements.
A loop that closes — with humans in it where it counts.
Optimization isn't a one-shot recommendation. It's a loop: define the goal, simulate, recommend, apply (with approval where needed), measure the outcome — and tune the model on what actually happened.
Goal
Pick objective and constraints in plain language.
Simulate
Project KPI impact across set-points before any change goes live.
Recommend
Ranked set-points with predicted impact and reasoning.
Apply
Apply with approval, or close the loop where it's safe — every change signed and reversible.
Measure
Compare predicted vs. actual; results feed back into the model.
Powered by the RockQ platform
This solution composes these platform capabilities. Each one is also available standalone.
An expert behind every solution.
Real engineers, real factory experience. Drop them a line — they'll respond, scope and propose a working architecture, not a sales deck.
Simulate one parameter change.
Pick a process. We'll model the KPI impact of three set-point changes — before any of them go to the floor.