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Case Study 3 – Six Sigma DMAIC Project Portfolio Selection

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Introduction: Optimizing DMAIC Project Portfolio to Maximize Cost Savings

This is an example of DiscoverSim optimization used to select Six Sigma DMAIC projects that maximize expected cost savings.

This example model was contributed by: Dr. Harry Shah, Business Excellence Consulting

The goal is to select projects that maximize Total Expected Savings subject to a constraint of Total Resources <= 20. Management requires a minimum total project savings of $1 Million (Lower Specification Limit, LSL = 1000 $K). We will explore the optimal selection of projects that maximize the Mean Savings and also consider maximizing the Process Capability Index Ppl.

Cost Savings are specified with a Triangular Distribution.

The Probability of Success is modeled using the Bernoulli (Yes/No) Distribution.

“Resources Required” are specified for each project. DiscoverSim Input Controls (Discrete) are used to select the project (0,1).

Expected Project Savings are calculated as the sum of: Cost Savings * Probability of Success (if project is selected) or 0 (if project is not selected).

Summary of DiscoverSim Features Demonstrated in Case Study 3:

  • Create Input Distributions (Continuous Triangular)
  • DiscoverSim Copy/Paste Cell
  • Create Input Distributions (Discrete Bernoulli)
  • Create Discrete Input Controls
  • Specify Constraints
  • Run Optimization
  • Run Simulation

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