A new way to think about throughput

Test it on the model
before you try it
on the plant.

Built for executives: fast, game-style production line simulation that shows what each decision is worth, from one machine to the whole supply chain.

Validated within 1% of measured OEE
New game Beat the Bottleneck. Every machine on this line runs at the same speed, yet it delivers 54% of what it could. Can you do better? Play →
Why averages mislead

Two failures, 120 minutes of downtime a week each.
Your Loss Tree ranks them the same.

Fix either one and the line responds very differently.

Scenario 1: Timing Belt
One long stop per week
Frequency1× / week
Repair time~2 hours
120 min downtime / week
Scenario 2: Bottle Jams
One hundred twenty short stops per week
Frequency~120× / week
Repair time~1 minute
120 min downtime / week
Stops ripple. A stop starves and blocks the machines around it, and those losses are logged under other names. Averages can’t show which fix pays. ReliaSim® models the stops themselves.
See what the model found → or why short stops behave differently
Why the engine works this way

Pieces and parts, or rates and flow

Most simulation was built for assembly, where every item is tracked on its own. Point that at a filler running hundreds of units a minute and the model runs slower than the line. ReliaSim models rates and flow instead, so it keeps up.

We build playing fields that get the math right. The film shows what that means before capital is committed.

Apply for a free assessment →
A look inside

This is the software.

A full year of the Buffer-Options bottling line runs in 0.3 seconds, and 1,000 of those years take 32 seconds on a laptop.

A time-to-failure distribution (solid blue) and a time-to-repair distribution (dashed red) for one interrupt TTF, uptime TTR, repair Time (min) → PDF
Step 1

Fit your stop history

ReliaStats® groups each machine’s stops by cause and fits a time-to-failure and time-to-repair curve to every one.

Try ReliaStats in the Sandbox →
The ReliaSim desktop application after a one-year run of the bottling line, from filler through capper, labeler, case packer and palletizer, with each machine's availability and a 54.5% line efficiency.
Step 2

Model the line

ReliaSim builds your line from machines, converters and the buffers between them, and every run comes with eight analyses.

Open the Sandbox →
ReliaSim Throughput Scatter for 1,000 one-year runs of the Buffer-Options bottling line, most runs between 284,000 and 290,000 pallets.
Step 3

Test the change

Run each option a thousand times from a fixed seed, so anyone can repeat the answer and see the spread one run hides.

See the method →
Try it

From one machine to the whole supply chain

The free Sandbox runs in your browser. Every number on screen comes from the ReliaSim engine.

Beat the Bottleneck: the bottling line game A game · Beat the Bottleneck Can you get more out of this line? Every machine on this bottling line runs at the same speed, yet it delivers only 54% of what it could. Fix one problem or add buffers, and ReliaSim runs your line ten times. Then see what Lean, TPM and TOC would have done. Play Beat the Bottleneck →
The eight bottling-line models

Eight curated models from the same real bottling line, across two tracks (Constraint-Level rollups vs LEDS-Level drill-downs) and four complexity steps. The engine ran each model once and saved the results. Read the model documentation → to see what each contains, and why all eight predict the same throughput but disagree about the cause.

Open the Sandbox → Plus an AI agent in every tier that answers from the model’s own engine runs.
How the guided workflow runs

Ask your model questions in plain English

ReliaSim exposes your production model through a Model Context Protocol (MCP) server. Claude and other MCP-compatible assistants can load, inspect, run, and question the model in plain language. You drive the conversation and the model does the math.

Inspect topology & constraints

Node types, buffer positions, interrupt configs and constraint availability, in plain language.

Run simulations on demand

Per-constraint availability, OEE, and multi-run stats instantly.

Buffer analysis through time

Utilization, inflow/outflow, empty/full percentages, and throughput distributions.

Diagrams & reports

Topology visuals and detailed exports, all from one conversation.

Works with Claude, any MCP-compatible AI, and Claude Code.
Bottling Line 90-day run
Online ReliaSim AI · Bottling Line Validated ✓
You
The model matches our 54.3% OEE. Which fix should we make first?
ReliaSim
ReliaSim
Not the one the Loss Tree ranks first. Labeler Misalignment costs 6.79% and Filler Micro Stop costs 6.72%, nearly a tie. Removing each one in the model, the Labeler fix gives back +5.0 points and the Filler fix gives back +8.1, 62% more, because the Filler’s short stops ripple into every machine after it. Start with the Filler.
You
Could a buffer after the Filler do the same job without touching the machine?
ReliaSim
ReliaSim
It can soak up some of those short stops. Run the buffer trade-off on this line against the Filler fix and the model shows which one gives back more output for the money. Both answers come from the same validated playing field.
Ask about throughput, buffers, interrupts, or what-if scenarios…

Every response comes from your own validated production graph.

Connect your own assistant

/mcp is a live JSON-RPC endpoint. Point Claude, Claude Code, or any MCP-compatible client at it. Setup is in the documentation.

A ReliaSim project

From your stop data to a decision you can defend

Most sim tools hand you a blank canvas. ReliaSim hands you the method our own modeling team runs. Every project follows the same four steps. See how a project runs →

Step 1: Ingest & Validate

Your data, hygiene-checked before the first model run.

Drop in your line event CSV. The system checks for gaps, time resolution, and fault-code hygiene before you build anything, so bad data gets caught before it becomes a bad model.

Step 2: Build the playing field

Guided parameterization against your actual OEE.

You don't need to know which distribution fits which interrupt type, because the method does. A typical build takes 15 minutes.

Step 3: Run the Decisions That Matter

The five scenarios every production system faces.

Fix priority, line speed, buffer sizing, redundancy and resupply, set up as structured scenarios instead of blank-slate guesswork. See the five →

Step 4: Ship a Defensible Recommendation

Your team leaves with a written recommendation.

Every scenario run comes with the topology, the assumptions, and the sensitivity check a capital review needs.

ReliaSim is made by ChiAha in Maryville, Tennessee. Andrew Siprelle created discrete rate simulation in 1990, and the same team has been modeling production lines ever since. Meet the team →

Get Started

Ready to find your next throughput gain?

The quickest way to see it is one question on your own line. You can also explore on your own or walk through a real model with us.

"It runs on my desktop. No integration, no IT project, no waiting. I just install it and start modeling."
— Technology Director, Essity
"I've never seen anything like this."
— VP of Food Production
Free this fall

ReliaSim Line Assessment

We model one question about your line on your data and send a two-page readout in about five business days.

Apply for an assessment
Free · Start Now

Download ReliaSim Demo

Open and run pre-built models like the bottling line and explore the process hands-on. There's no purchase and no license key. Sign in with your work Microsoft account and the download is free.

Sign in & download the demo
Guided

Live Demo

We walk you through a real production model, then sketch your line and look at your data together, so you can see what a validated model of your system would look like.

Schedule a call
Industries we've modeled

Food & Beverage Pharma & Life Sciences Aerospace & Defense Energy & Chemical Packaging & CPG Paper & Pulp Semiconductor Academic Research

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