Monte Carlo Simulation Overview
Monte Carlo simulation is a powerful statistical method used in engineering to predict real-world performance when multiple design variables contain uncertainty (tolerances). Rather than relying on worst-case or nominal calculations, this approach runs thousands to millions of virtual “builds” by randomly sampling each tolerance within its realistic production range.
For Battery IV, the analysis included over 100,000 iterations.
Each iteration calculated key performance metrics, including preload, closing force, breakaway force, opening travel, and leak potential. The result is a probability distribution that shows not only averages or extremes, but how frequently specific outcomes are expected to occur in real production.
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