The problem with improving production without simulation
Every production manager has a list of ideas for improving the line. Add a buffer here. Speed up that machine. Move this station closer. Change the batch size. But which idea will actually help — and by how much? And which will cause an unexpected problem somewhere else?
Without simulation, the only way to find out is to implement the change on a live production line — disrupting operations, committing resources, and hoping for the best. Even experienced engineers are routinely surprised by how complex systems respond to local changes. A throughput gain at one station creates a new bottleneck three stations downstream. A buffer addition increases WIP without improving output.
Production systems are non-linear and interdependent. The only reliable way to predict how a change will behave is to simulate it — where getting it wrong costs nothing.
What production simulation can answer
A SimulateFirst discrete-event simulation model captures your entire process — machines, workers, buffers, conveyors, batching rules, failure rates, and variability — and runs it for thousands of simulated hours. This allows you to answer questions that no spreadsheet can:
- Where is the real bottleneck — and is it the same one at different demand levels?
- How much buffer is needed between stations to prevent starvation and blocking?
- What happens to throughput if the fastest machine fails for 2 hours?
- How many workers are needed to sustain target throughput across all shifts?
- Which of three layout alternatives gives the best throughput per unit of floor space?
- What is the maximum capacity of the current line — and what is the cheapest way to increase it?
Data collection & process mapping
We work with your engineers to document the process flow, cycle times, failure rates, batch sizes, worker assignments, and throughput targets. We identify which data is critical and which can be estimated with validated benchmarks.
Model build & validation
We build the Simio, AnyLogic, or Visual Components model and validate it against historical production data. A validated model reproduces past performance within a defined tolerance before any scenario analysis begins.
Scenario testing
We run the specific scenarios you want to evaluate — plus any our analysis suggests. Each scenario is replicated multiple times to produce statistically robust results with confidence intervals.
Results, recommendations & handover
A clear report: throughput by scenario, bottleneck identification, utilisation analysis, and a ranked list of recommended improvements with expected impact. Model handed over for ongoing use.
What you get at the end
Deliverables: the simulation model file, a scenario comparison report with throughput curves and utilisation data, a bottleneck analysis with visualisation, recommended improvement actions with expected impact, and documentation for ongoing use. The model is yours — no subscription required.
Technology — choosing the right tool
Unlike most simulation providers who specialise in one platform, SimulateFirst is genuinely technology-agnostic. We choose the simulation tool that best fits your problem:
- Simio — best for manufacturing processes with scheduling requirements, or where digital twin connectivity is a future goal. Native risk-based scheduling output.
- AnyLogic — best for large-scale logistics networks, processes with complex human behaviour or agent interactions, or multi-method modelling needs.
- Visual Components — best when accurate 3D CAD representation of the production layout is required, for example to validate reach, cycle time, and spatial constraints alongside throughput.
See it in practice
Warehouse logistics — end-to-end process model with AGV coordination
Simio · Logistics
Steel plant — full production process model, ERP integration
AnyLogic · Manufacturing
