Manufacturing companies reach this question from a different direction than research organisations. They rarely need broad simulation capability. They usually need the same analysis, repeatedly, on variants of the same product — and that specificity changes the economics substantially.
The pattern that makes ownership work
The manufacturers for whom this succeeds share a recognisable profile:
- One dominant analysis type — the same class of problem run hundreds of times a year on product variants.
- Stable physics — the governing equations have not changed in a decade and will not.
- High run count rather than one enormous run — which is exactly where per-seat and per-core licensing hurts most.
- Desire to automate — running the analysis inside a design workflow, not by hand.
- At least one engineer who understands the numerics.
The high-run-count pattern is the key signal. A company running one large simulation a month should licence. A company running four hundred variants a year of the same analysis has a workload that a narrow, specialised solver can serve far faster and without a licence meter — and specialisation often makes each run several times quicker than a general-purpose code.
Specialisation is the real advantage
Cost is the usual motivation and speed is frequently the bigger payoff. A general-purpose solver must handle arbitrary geometry, arbitrary physics, arbitrary meshes. A solver built for one product family can assume:
- A known geometry topology, so meshing can be automated rather than manual.
- A known physics regime, so the numerical scheme can be tuned for it.
- A known range of operating conditions, so initialisation can be smart.
- A fixed output set, so post-processing is automatic.
The manual meshing step is usually what makes analysis slow, not the solve. Removing it for a known geometry family is often worth more than the licence saving.
Where manufacturers underestimate the commitment
| Assumption | Reality |
|---|---|
| "We build it once" | 15–20% of build cost annually to maintain |
| "Our engineer can maintain it" | One person is a single point of failure |
| "We can validate it later" | Validation is 25–40% of the project |
| "We will extend it as needed" | Each new physics is development plus re-validation |
| "It will replace our licences" | Usually replaces most, not all |
Knowledge concentration is the risk manufacturers manage worst. A solver understood by one engineer is a business continuity problem, and manufacturing organisations frequently have exactly one person who could ever have owned it. Documentation and a second capable engineer are not overhead — they are what makes the asset survivable.
A staged path that limits exposure
- Measure your analysis mix. Which case dominates core-hours, and how stable has that been over three years?
- Automate within your commercial tool first. Scripting the meshing and setup for your product family often captures a large share of the benefit with no development risk at all.
- Prototype the physics in a framework. A custom OpenFOAM solver proves the approach at a fraction of from-scratch cost.
- Benchmark honestly against your tuned commercial workflow — accuracy and wall-clock on your real cases.
- Commit only with validation cases agreed in advance, and with a named second engineer for continuity.
Step 2 is worth pausing on. Many manufacturers who believe they need an in-house solver actually need automation around the one they already have — and that is a fraction of the cost and risk.
When to stay commercial
- Your analysis mix is varied rather than dominated by one repeated case.
- Your physics requirements are still evolving.
- Nobody internally understands the numerics well enough to own it.
- Licence cost is an irritation rather than a genuine constraint on what you can run.
- Customers or standards specify particular commercial tools.
What "in-house" should actually mean
Rarely a full replacement. For most manufacturers the sensible end state is an owned, narrow, automated solver for the production analysis that dominates their workload — sitting alongside a small number of commercial seats for everything unusual. That structure captures the economics without pretending you can maintain a general-purpose simulation capability.
Running the same analysis hundreds of times a year? Tell us the analysis and how often — we will say plainly if automation over your existing tool is the better move. See our CFD solver service and the TCO comparison.