See every batch ripple before release slips.
RippleFlo simulates pharma process manufacturing — API synthesis, hold times, blending, fill-finish, and release windows — with DES-powered ripple tracing and audit-grade replay. Also built for aerospace, process, discrete, and critical manufacturing.
- 10×
- faster batch what-if cycles
- 30%
- less schedule rework
- 100%
- release traceability
Starting with pharma — extending to every critical manufacturing vertical
Today's planning stack lies to you — in every industry.
Spreadsheets hide queue effects
One delay compounds across shared stations — whether it's a CNC queue, reactor campaign, or fill line.
ERP assumes a perfect world
No breakdowns, no alternate routes, no shift calendar reality — across discrete and process lines alike.
Firefighting is expensive
Overtime, expedites, and lost credibility with customers, regulators, and program offices.
Critical mfg needs evidence
In regulated environments, you can't just reschedule — you need traceability, replay, and defensible decisions.
Pharma process manufacturing needs foresight — not another ERP schedule.
ERP records what happened on the batch record. RippleFlo simulates what will happen across API synthesis, hold times, blending, fill-finish, and release windows — before QA finds a deviation.
Exploring another industry? Use the selector above — Aerospace, Process, Discrete, Medical, and Critical Manufacturing each have dedicated pages.
Plans batches. Can't model the process.
ERP handles orders, BOMs, inventory, and batch records. It assumes average cycle times and dedicated equipment — but pharma is campaigns, holds, shared reactors, and release windows.
- Schedules batches on average lead times — not reactor queues or hold-time chains
- Cannot model campaign overlap when two products share validated equipment
- Batch record deviations discovered at QA sign-off, not days earlier
- Changing a release date means re-planning across planning, QA, and ops manually
Simulates the batch journey.
A discrete-event digital twin of your pharma line. Batches flow event by event through reactors, holds, QC gates, and fill-finish — with release risk scored before the window closes.
- Simulates API synthesis → hold → blending → fill-finish as discrete events
- Scores every batch on track, at risk, or critical before release window slips
- Traces reactor delays through hold, QC IPC, and fill-finish in one ripple map
- Pre-commit blast preview shows which lots shift before QA publishes a change
Pharma process manufacturing — ERP vs RippleFlo
| Dimension | ERP / MES | RippleFlo |
|---|---|---|
| Batch scheduling | Fixed lead times per SKU | Campaign windows with queue & hold modeling |
| Equipment sharing | Assumes dedicated lines | Validated train contention & overlap detection |
| Hold times | Static offset in plan | Dynamic hold chains that ripple downstream |
| Release risk | Discovered at sign-off | Amber/red scoring days before deviation |
| Lot splitting | Manual spreadsheet math | Min/max batch sizes simulated in DES |
| Equipment failure | Logged after production stops | MTBF/MTTR injected — measure batch slip |
| Audit trail | Reconstruct from batch records | Deterministic replay + commitment diff |
| What-if cost | Change the real campaign | Re-run the model — zero shop-floor risk |
Watch a pharma campaign ripple through the line.
Reactor R2 builds queue. Hold times extend. Fill-finish slips. Release windows turn amber — all visible before a batch record changes.
How RippleFlo solves what ERP cannot in pharma.
Process manufacturing in regulated environments needs simulation-backed decisions — not spreadsheet hope.
Campaign overlap detection
See when Batch BX-77 and BX-78 compete for Reactor R2 before either misses a release window.
Hold-time ripple chains
A 6-hour hold extension traces the slip through fill-finish and QC release — not just one operation.
QA-ready risk scoring
Flag batches at risk before deviation paperwork. Planning and QA see the same amber alert.
Validated alternate routes
When Reactor R2 is down, DES routes through the next qualified train.
Release window defense
Pegging tree from customer PO → batch → operation → root cause for review or regulator.
Audit-grade replay
Re-run any historical campaign scenario with identical inputs.
Reactor R2 down 18 hours. Five batches. Five different release stories.
ERP reschedules on averages. RippleFlo measures slip per batch against its own release window — BX-77 slips 6 hours while BX-75 only slips 2 because its hold cleared before the queue peaked.
- Per-batch slip with attribution (% Reactor R2 vs downstream hold)
- Stage-to-stage trace: if hold extends, when does fill-finish move?
- Pre-commit preview — see which release windows shift before QA signs off
Explore other industries.
Pharma is our default focus — switch anytime using the industry selector above. Each vertical has its own ERP comparison, process animation, and use cases.
Pharma & biotech
Batch release risk scoring, campaign scheduling, validated equipment trains, and hold-time modeling — so QA sees amber alerts before deviations.
- Batch & lot splitting
- Release window scoring
- Regulator-ready audit trail
Critical manufacturing
Audit-grade traceability, pre-commit blast preview, deterministic replay, and commitment pegging for environments where every schedule change must be defensible.
- Simulation history archive
- Commitment diff on publish
- War Room crisis coordination
Aerospace & defense
Contractual delivery promises, alternate qualified routes, shared bottleneck stations, and program-level ripple traces across complex routings.
- Order-level ATP/CTP
- Alternate machine routing
- Program milestone tracking
Process manufacturing
Campaign windows, min/max batch sizes, shared reactors, and material readiness gates — DES models the queue effects process planners actually fight.
- Campaign scheduling
- Resource pool contention
- Process route alternates
Discrete manufacturing
CNC job shops, custom lots, shared stations, and order-level promises — with per-commitment slip attribution when one machine goes down.
- Factory line designer
- Chaos mode stress tests
- Actuals → auto replan
Medical devices & life sciences
Traceable schedules from PO to operation, CAPA-style pre-commit preview, and deterministic scenario replay for quality and regulatory review.
- Pegging tree export
- Role-aware change preview
- Shop-floor calibration loop
Your ERP tells you what happened. RippleFlo tells you what will happen on the shop floor.
Discrete-event simulation for critical manufacturing — model machines, queues, operators, shifts, failures, and WIP, then run virtual production days before changing a single setting on 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.
Stop guessing. Start simulating.
Bring decisions — not opinions — to the next ops review. Model your line, run the scenarios, and trace every ripple before it hits production.
One operating system for production planning.
Design → Plan → Simulate → Schedule → Actuals → Replan. Critical manufacturing, process campaigns, and discrete lines in one closed loop.
Model the real factory
Lines, routings, calendars, alternates — your shop floor, digitally twinned.
Simulate forward with DES
Event-driven engine captures queues, blocking, and variability.
Inject discrete events
Breakdowns, material delays, demand surges — measure commitment impact.
Close the loop with actuals
Shop-floor timings calibrate your model and trigger automatic replan.
600 minutes on CNC1. Three lots, three different stories.
Naive schedulers say “later = worse.” RippleFlo measures slip per order against its own plan — so Lot 2/6 finishes 4 hours late while Lot 3/6 only slips 40 minutes because its downstream path took an alternate route.
- Per-commitment slip with attribution (% CNC1 vs downstream queue).
- Stage-to-stage trace: if CNC1 slips, when does Final QC move?
- Pre-commit blast preview — before you publish, see who gets hit.
Engineered for critical manufacturing — where every slip has stakes.
Pharma, aerospace, medical devices, defense, process, and regulated discrete. Environments where every minute is traceable, every change is reviewed, and every customer commitment is contractual. RippleFlo brings the rigor.
Audit-grade traceability
Every schedule decision, simulation run, and replan is archived. Export the pegging tree from commitment back to root cause for internal review or regulator.
Validate before you commit
Pre-commit blast preview shows exactly which lots, batches, and customer promises shift — before a single change touches the floor.
Release & commitment risk scoring
Risk analytics flag equipment conflicts, calendar collisions, and CAPA-style actions before they become deviations — for batches, orders, and programs.
Deterministic replay
Re-run any historical scenario with identical inputs. Reproduce, review, and defend every scheduling decision you ever made.
Earlier-than-human warning
Amber and red alerts fire days before a slip becomes a missed commitment — giving QA, planning, and customer success room to act.
Alternate-route resilience
When a qualified machine goes down, DES finds the next compliant route automatically — respecting validated equipment trains.
Defensible schedules. Reviewable decisions. Repeatable outcomes.
Simulation History preserves every run with station metrics, event traces, and CSV exports. Commitment Diff captures what changed and why. Recipe calibration links shop-floor reality back to your planning model — closing the loop your quality team already expects.
- Pegging tree from customer order → lot → batch → operation
- Full simulation archive with replay and export
- Commitment Diff for every schedule publication
- Role-aware change preview before publishing
Watch your line breathe — every unit, every station, every slip.
Design dual-flow lines, route through alternate equipment, and see the discrete event simulation stream units between stations in real time. Bottlenecks light up the moment they form.
Six modules. One closed loop.
Factory & Line Design
Top-down layouts, drag-and-drop stations, primary/secondary/bypass routes. Per-station cycle times, distributions, MTBF/MTTR, resource pools.
Production Planning
Order and batch entry with ATP/CTP feasibility, calendar-aware ideal/ASAP/Start-now options, lot splitting, campaign windows, and material readiness gates.
DES Scheduling Engine
ManPy-inspired event engine: Source → Machines → Queues → Exit. Captures waiting, blocking, starvation that Gantt tools miss.
Discrete Event Chaos Testing
Inject breakdowns, material delays, worker absence, rework, demand surges. Test it in software before the shop floor finds out.
Ripple Observability
Trace a delay from source through every downstream stage. Per-commitment severity. Stage-to-stage what-if queries.
Actuals → Calibration → Replan
Capture shop-floor timings, recalibrate recipes, and auto-replan remaining steps from actual finish time.
Platform advantages that apply everywhere.
The same DES core powers critical manufacturing rigor, pharma batch planning, aerospace programs, and CNC job shops.
DES engine, not static Gantt
Event-driven simulation captures queues, blocking, and starvation that spreadsheets and ERP schedulers miss — across discrete, process, and hybrid lines.
Ripple observability
Trace any delay from source station through every downstream stage. Per-commitment severity with station-level attribution.
Critical mfg traceability
Simulation history, commitment diff, and deterministic replay — the evidence layer regulated and high-stakes environments require.
Chaos testing before the floor
Inject breakdowns, material delays, demand surges, and rework. Measure impact in software before the shop floor or QA finds out.
Closed-loop calibration
Shop-floor actuals recalibrate recipes and trigger automatic replan — keeping your digital twin aligned with reality.
Alternate-route resilience
When primary equipment is down, DES finds the next compliant path — qualified alternates for aerospace, pharma, and discrete alike.
Calendar-aware planning
Shifts, holidays, maintenance windows, and equipment calendars baked into every feasibility check and simulation run.
Earlier-than-human alerts
Amber and red warnings fire days before a slip becomes a missed commitment — orders, batches, programs, and release windows.
Spreadsheets pretend. DES proves.
RippleFlo simulates your factory as a sequence of events — jobs arriving, machines starting, breakdowns happening, repairs finishing. It captures the queueing, blocking, and starvation that static Gantt tools can’t see.
| Spreadsheet / static Gantt | RippleFlo DES |
|---|---|
| Assumes fixed durations | Models queues & contention |
| One delay = manual fix | Ripples propagate automatically |
| Ignores shifts and holidays | Factory calendar aware |
| Hard to compare scenarios | Baseline vs scenario side-by-side |
| No audit trail | Simulation history archive |
Don’t discover the ripple on the floor. Inject it in software first.
From source station to customer commitment in one trace.
See exactly how a delay propagates. Severity scoring (on track / at risk / late / critical) per commitment. Attribution per station. Open the War Room for crisis-level coordination with pre-commit blast preview.
Plan once. Calibrate continuously.
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.
See your factory simulated in 30 minutes.
Load a sample scenario — CNC Dual-Flow, 100 orders, pharma batch line, or aerospace routing — and walk through a real ripple trace with our team.