Purpose:
- Monte Carlo Simulation: Uses repeated random sampling to evaluate uncertainty and predict the distribution of possible outcomes.
- Parameter Optimization: Searches for optimal settings of controllable inputs to improve output performance.
- Sensitivity Analysis: Evaluates how changes in input variability affect the selected output metric.
Installation:
Download the file and drag-and-drop onto Origin. A new corresponding icon will appear in the Apps Gallery window. A toolbar will appear when launching the APP.
Features:
-
Monte Carlo Simulation:
-
Multiple Inputs and Outputs: Supports mathematical models with multiple input (X) and output (Y) variables.
-
Probability Distributions: Allows users to select probability distributions and specify parameters for each input variables.
-
Automatic Distribution Fitting: Fits distributions to data in worksheets and recommends a best-fitting distribution.
-
Import Models from reports: Imports models from General Linear Regression, DOE, Nonlinear Regression analysis reports.
-
Setup Inputs from Sheet: Reads input variable names from worksheet.
-
Model Grouping: Organizes inputs, outputs, and equations into groups for complex simulations.
-
Model Preview: Visually displays the simulation model, including input distributions, output variables, and their relationships.
-
Save and Load Settings: Save models and their settings into JSON files and load them in the future.
-
Simulation Results and Visualization: Displays output histograms, summary statistics, percentiles, and other simulation results.
-
Process Capability Analysis: Calculates capability metrics such as Cpk/Ppk and out-of-specification percentages based on specification limits.
-
Export Results: Generates simulated data and saves it into worksheet.
-
Parameter Optimization:
-
Multiple Parameter Optimization: Optimizes multiple controllable input variables simultaneously.
-
Optimization Objective: Supports optimizing one or mutliple outputs. Allows users to select metric and optimization goal for each variable.
-
Parameter Bounds: Supports specifying lower and upper search limits for each controllable input.
-
Noise Variables: Allows inputs to be designated as noise variables, excluding them from direct optimization while accounting for their variability.
-
Optimization Results Visualization: Displays simulation results with graphs, process capability metrics, summary statistics, and percentiles.
-
Sensitivity Analysis
-
Multiple Input Sensitivity Analysis: Evaluates how variations in multiple input variables affect a selected output.
-
Multiple Output Support: Allows users to select which output variable to analyze when a model has multiple outputs.
-
Input Standard Deviation Analysis: Evaluates the effects of changing the standard deviation of each input variable.
-
Output Variability Analysis: Examines how variations in input variables affect the output metric.
-
Sensitivity Plot: Displays graphical sensitivity curves for input variables, showing their influence on output performance.
-
Tornado Plot: Ranks input variables by their impact on the selected output metric, based on a ±20% change from their baseline values.
-
Iterative Sensitivity Analysis: Allows users to modify input variation and repeat the analysis to evaluate alternative scenarios.