How do you optimize your ESD simulation workflow and reduce the computational cost and time?

2 Simplify the geometry and mesh

The second step in ESD simulation and modeling is to simplify the geometry and mesh of your device or system. The geometry and mesh determine the size and complexity of the simulation problem, which affect the computational cost and time. You should try to eliminate unnecessary details, features, and elements that do not significantly affect the ESD behavior or response of your device or system. You should also use adaptive mesh refinement, where possible, to increase the resolution and accuracy only in the regions of interest, such as the ESD sources, paths, and sensitive components.

3 Use parallel computing and cloud resources

The third step in ESD simulation and modeling is to use parallel computing and cloud resources to speed up the simulation process. Parallel computing allows you to distribute the simulation workload among multiple processors or cores, which can reduce the simulation time significantly. Cloud resources enable you to access high-performance computing platforms and services on demand, without the need to invest in expensive hardware or software. You should leverage the parallel computing and cloud resources that are compatible with your simulation tool and model.

4 Validate and calibrate the ESD model

The fourth step in ESD simulation and modeling is to validate and calibrate the ESD model against experimental data or measurements. Validation and calibration are important to ensure that the ESD model accurately represents the real ESD behavior or response of your device or system. You should compare the simulation results with the experimental data or measurements at different test points, conditions, and scenarios, and adjust the model parameters or assumptions accordingly. You should also perform sensitivity analysis to identify the most influential factors and uncertainties in your ESD model.

5 Optimize the ESD design and performance

The fifth step in ESD simulation and modeling is to optimize the ESD design and performance of your device or system. Optimization is the process of finding the optimal values or settings of the design variables or parameters that maximize or minimize a certain objective function or criterion, such as the ESD robustness, protection, or immunity. You should use optimization techniques, such as gradient-based, evolutionary, or stochastic methods, to explore the design space and find the optimal solution. You should also consider the trade-offs and constraints among different design objectives and criteria.