DiscoverSim is an Excel add-in designed for Monte Carlo simulation and optimization, allowing users to analyze and optimize statistical processes, predict outcomes, and assess risks within Excel. It is bundled with SigmaXL for enhanced statistical and graphical analysis.

Key Features

Monte Carlo Simulation Simulates thousands of scenarios to predict outcomes and assess risks.

• Allows modeling of continuous and discrete input distributions.
• Generates histograms, descriptive statistics, and process capability indices.

Optimization Optimizes processes to minimize defects or maximize process capability.

• Supports linear and nonlinear constraints.
• Can minimize defects per million (dpm) or maximize process capability index (Ppk).

Distribution Fitting Fits probability distributions to data for accurate modeling.

• Supports both continuous and discrete distributions.
• Uses Anderson Darling goodness-of-fit statistic for continuous distributions.

Sensitivity Analysis Identifies which inputs most affect outputs.

• Provides correlation and regression coefficients.
• Offers sensitivity charts for visual analysis.

Multiple Response Optimization Optimizes multiple outputs simultaneously.

• Supports weighted sum and other optimization metrics.
• Allows setting of target, minimum, and maximum values for each output.

Graphical and Statistical Reporting Generates comprehensive reports for analysis.

• Includes histograms, normal probability plots, and capability indices.
• Displays descriptive statistics and percentile reports.

Benefits

Process Improvement Provides tools to optimize processes and reduce defects.

• Helps identify optimal process settings.
• Reduces variability and increases process capability.

Risk Assessment Enables users to quantify and mitigate risks.

• Predicts probability of outcomes.
• Identifies potential issues before they occur.

Data-Driven Decision Making Supports decision making with statistical evidence.

• Provides clear, actionable reports.
• Facilitates communication of results.