Right-sizing CAE simulation teams for mid-program crunches

Why simulation workloads fluctuate

CAE demand is derived demand: it rises whenever design decisions need evidence. Workload increases significantly during:

• Design iterations, where multiple concepts require comparative evaluation
• Validation phases, where analysis supports formal gate decisions
• Design changes, which invalidate prior results and require re-analysis
• Program milestones with fixed dates and fixed evidence requirements
• Customer reviews requiring substantiation at short notice
• Testing cycles, where correlation work follows physical results

These events overlap. A design change late in a validation phase can multiply workload without any change to program scope.

The challenge of maintaining the right team size

Simulation leaders are balancing four pressures that rarely align:

• Permanent engineering teams, which provide method ownership and continuity
• Temporary project demand, which is often several times baseline capacity
• Specialised expertise, needed occasionally but difficult to develop or retain at low utilisation
• Cost efficiency, which penalises capacity held for peaks that occur a few times a year

Where additional CAE capacity is needed

Additional capacity is most commonly required across:

• Structural FEA — linear and non-linear strength, stiffness and durability studies
• CFD — internal and external flow, cooling and aerodynamic evaluation
• Thermal analysis, including coupled thermal-structural behaviour
• NVH — modal behaviour, response analysis and noise path studies
• Crash simulation and occupant or structural safety load cases
• Optimization — parametric, topology and design-of-experiments studies
• Pre-processing and post-processing, often the largest share of elapsed effort

Pre- and post-processing is frequently the most scalable element, and the one where added capacity produces the fastest schedule relief.

A flexible engineering capacity model

A workable model keeps a stable internal core and adds capacity in defined layers. Project-based engineers absorb volume work during peaks, while specialised external teams take bounded scopes that the internal team does not perform often enough to sustain.

1. 1Internal core — methods, correlation, result acceptance and program interfaces
2. 2Project-based capacity — model preparation, load case execution and reporting during peaks
3. 3Specialised external teams — occasional disciplines, engaged against a defined deliverable

Capacity planning works best when it is tied to the program's milestone calendar rather than to headcount budgeting cycles.

How to maintain quality while scaling

Added capacity only helps if results remain comparable and defensible. The controls that matter most:

• Standard processes for model setup, meshing conventions and boundary conditions
• Engineering guidelines and documented modelling assumptions
• Review mechanisms with clearly assigned technical accountability
• Knowledge transfer at both entry and exit of temporary capacity
• Quality checks including benchmark cases and correlation against known results

Organizations that maintain these controls can scale simulation capacity repeatedly. Those that do not tend to spend the time saved on re-analysis and rework.

Conclusion

Flexible capacity models help engineering organizations manage temporary simulation peaks without permanently expanding every capability. The requirement is structural: a clear internal core, documented methods and disciplined review, so capacity can be added and released without compromising the credibility of the results.