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Your ERP tells you what happened. RippleFlo tells you what will happen.
Discrete-event simulation for critical manufacturing — model machines, queues, operators, shifts, failures, and WIP before changing the real line.
System of record
ERP plans, schedules, and accounts for what actually happens. It's transactional — orders, BOMs, inventory, work-orders, costs.
- Answers: what did we produce, ship, and consume?
- Static plans built on average lead times
- Cannot model machine failures, queues, or variability
- Changing a parameter means changing the real plant
System of foresight
A discrete-event digital twin of your line. Time advances event by event: an entity arrives, a machine seizes a resource, a failure occurs, a shift ends. You watch the factory run — virtually.
- Answers: what will happen if we change X?
- Stochastic — handles variability, breakdowns, and repair times
- Models WIP, buffers, operators, shifts, and scheduling rules
- Runs thousands of replications in minutes — zero shop-floor risk
Same factory. Two very different questions.
| Dimension | ERP / MES | RippleFlo |
|---|---|---|
| Time model | Calendar / batch | Event-by-event (discrete) |
| Purpose | Execute & record | Predict & decide |
| Variability | Averages only | Distributions & randomness |
| Failures & repairs | Logged after the fact | Modelled as first-class events |
| Scenario cost | Real production change | A re-run of the model |
| Queue & contention | Hidden in averages | Queues, blocking, starvation visible |
| Output | Reports & invoices | Throughput, utilisation, WIP, bottlenecks, ripple traces |
| Schedule changes | Publish and hope | Pre-commit blast preview before you publish |
Problems that only simulation can solve.
ERP keeps the lights on. RippleFlo tells you where to point them next — with numbers, not gut feel.
Bottlenecks stay invisible
ERP averages utilisation across a week. It won't show that Mill is at 96% while Cut starves 14% of the time.
Failures are history, not forecasts
A breakdown is logged after production stops. ERP can't inject MTBF/MTTR and ask: how many orders slip if CNC1 is down 600 minutes?
Buffers are guesses
Right-sizing WIP between stations requires simulation — ERP has no queue model to run the buffer-allocation problem.
What-if costs the floor
Testing a new shift pattern, staffing level, or capex decision in ERP means changing live settings. RippleFlo runs it virtually first.
From model to insight in five steps.
Decisions you can defend with numbers.
Find the real bottleneck
Utilisation per station, queue lengths, and starvation ratios expose the constraint your ERP averages away.
Right-size buffers & WIP
Sweep buffer configurations across thousands of replications and pick the throughput-per-inventory winner.
Stress-test failures & repair
Inject realistic MTBF/MTTR. Decide repair capacity before signing a contract — not after a crisis.
Validate shifts & staffing
Compare 2-shift vs 3-shift, end-of-shift rules, and operator allocation with measurable off-shift impact.
Compare scheduling rules
Rank dispatching policies by tardiness, flow time, and WIP in a job-shop — before the floor adopts one.
De-risk capex
Prove throughput and ROI in the model before buying a new line. The cheapest experiment is the one you don't run on the plant.
How DES saves time and money.
Before and after, across the moments planners actually feel pain.
Typical results observed with early RippleFlo customers. Your mileage will vary.
Ready to see how simulation fits your industry? Explore vertical-specific examples or book a demo.