Production optimization that increases throughput without new capex
Use intelligent digital twins to understand how your production system really behaves—identify true bottlenecks, test changes safely, and increase output with confidence.
Why increasing output is harder than it looks
Most production systems are complex, tightly coupled, and constantly changing. When decisions are based on averages or gut feel, improvements are fragile.
What's blocking throughput
- Bottlenecks that shift by product, shift, or day
- Variability that hides the true constraint
- Local improvements that hurt downstream flow
- Changeovers and schedules that look good on paper but fail in reality
- Pressure to "run faster" without understanding system limits
The system-wide approach
- Understand the whole system, not just individual machines
- Identify the true constraint under different conditions
- Test changes virtually before implementing on the floor
- Optimize flow across the entire line or plant
- Make data-driven decisions with confidence
From local fixes to system-level improvement
This solution applies the intelligent digital twin model to a specific operational challenge. For a full explanation of the model itself, see: What is an Intelligent Digital Twin →
With intelligent digital twins, production optimization is not about speeding up individual machines—it's about optimizing flow across the entire line or plant.
Using an intelligent digital twin, teams can:
- Models how machines, buffers, and constraints interact
- Reflects real operating conditions, not ideal assumptions
- Shows how variability propagates through the system
- Reveals the true bottleneck under different scenarios
This allows teams to test ideas virtually and choose changes that actually improve throughput, stability, and OEE.
A practical, repeatable approach
1. Model the production system
Create a digital representation of lines, assets, buffers, and routing.
2. Establish baseline performance
Understand current throughput, utilization, downtime, and variability.
3. Simulate improvement scenarios
Test line balancing, staffing changes, schedules, and changeover strategies safely.
4. Identify the true constraint
See which bottleneck limits output under different conditions.
5. Implement with confidence
Apply changes knowing their expected impact—and monitor results in real time.
Where production optimization delivers the most value
Bottleneck identification
Find the constraint that actually limits throughput.
- Identify shifting bottlenecks across products and shifts
- Separate chronic constraints from temporary noise
Line balancing
Improve flow without new equipment.
- Reallocate work across stations
- Reduce idle time and starvation
Changeover optimization
Reduce lost production during transitions.
- Test sequencing and batching strategies
- Balance flexibility with efficiency
Schedule & mix optimization
Protect output under real conditions.
- Evaluate schedules against variability
- Understand trade-offs between throughput, WIP, and service
Used by operations, not just analysts
Plant managers
- See which constraints threaten today's plan
- Evaluate trade-offs before changing priorities
- Improve schedule stability
Continuous improvement teams
- Test improvement ideas virtually
- Focus effort where impact is highest
- Validate gains with real data
Schedulers & planners
- Build schedules that reflect reality
- Reduce last-minute changes and expediting
- Balance throughput, WIP, and service levels
What teams typically achieve
Results vary by system and maturity, but teams often target:
- More predictable schedules and output
- Fewer unintended consequences from changes
The biggest gains come from fixing the right problem—not working harder everywhere.
Start with one line. Prove value. Scale plant-wide.
1. Start
Choose a critical line, bottleneck, or product family.
2. Prove
Validate insights and improvements using real operating data.
3. Scale
Extend optimization to additional lines, plants, or scenarios.
Common questions about production optimization
Increase output without increasing risk
Start with one production challenge—and optimize with confidence.