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DiscoverSim™ Case Studies

Case Study 1 – Basic Profit Simulation: Introduction

  1. This is an example of DiscoverSim Monte Carlo simulation to determine probability of daily profit using a basic profit model for a small retail business. We will apply distribution fitting to historical data and specify input correlations to define the model in a way that closely matches our real world business.

    The profit (Pr) requirement is Pr > 0 dollars (i.e., the lower specification limit LSL = 0)

    The profit equation, or “Y = f(X) transfer function”, is calculated as follows:

    Total Revenue, TR = Quantity Sold * Price

    Total Cost, TC = Quantity Sold * Variable Cost + Fixed Cost

    Profit, Pr = TR – TC

  2. In this study we will use DiscoverSim to help us answer the following questions:

    1. What is the predicted probability of daily profit?
    2. What are the key X variables that influence profit Y? Can we reduce the variation in profit by reducing the variation of the important input variables?

  3. Summary of DiscoverSim Features Demonstrated in Case Study 1:

    • Distribution Fitting – Discrete Batch Fit
    • Distribution Fitting – Continuous Batch Fit
    • Distribution Fitting – Specified Distribution Fit
    • Create Input Distributions with Stored Distribution Fit
    • Specify Input Correlations
    • Run Simulation and display
      • Histograms, Descriptive Statistics, Process Capability Report
      • Percentile Report
      • Scatter Plot/Correlation Matrix
      • Sensitivity Chart of Correlation Coefficients
      • Sensitivity Chart of Regression Coefficients
    • Distribution Fitting – Nonnormal Process Capability

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