Excel Monte Carlo Simulation (Quantum XL) is an Excel add-in providing fast and easy Monte Carlo analysis and simulation functions to Excel models. |
The Monte Carlo Simulation add-in also provides adduced data visualization and analysis including optimization, custom distributions, latitude plots and percentage contribution analysis.
Key features of Monte Carlo Simulation for Excel include:
- Comparable to Crystal Ball but at a much lower cost.
- Monte Carlo simulations can be run in Rocket mode of up to 2 million simulation per second and automatically switches to Native mode depending on resource limitations.
- Model optimization finds optimal set points for both input and output variables. Optimization criteria statistics are flexible such as defects per million, mean, standard deviation, percentile, median etc.
- Supports custom discrete and continuous distributions as well as the normal, uniform, triangular, log Normal, logistic, log logistic, gamma, Weibull, exponential, uniform discrete, Poisson, binary and binomial distributions.
- Input/Output Manager window provides an overview of all inputs, outputs and custom distributions.
- Define multiple inputs and outputs simultaneously by selecting ranges of cells.
- Provides percent contribution and tolerance allocation tables to analyze the most sensitive model inputs.
- Latitude plots provide a graphical representation of the variation being consumed by inputs.
- Merge two or more legacy model design sheets to create one larger model.
- Create surface, contour and interaction plots of the model's inputs versus outputs to analyze relationships.
- Allows entering of part, process and performance information to monitor the capability and maturity of model design and creates Pareto of defects per unit to help allocate critical resources.
- Creates Latin hypercube samples and descriptive samples for validation strategies.
- Creates NOLHS designs ideal for multiple level experiments with deterministic simulators.
- Allows creation and edit of houses of quality, pairwise comparison matrices, FMEA and Pugh matrices.