Updating the TSP Quality Plan Using Monte Carlo Simulation

Abstract

The 309th Software Maintenance Group at Hill AFB has started implementing an updated version of the TSP quality plan utilizing Monte Carlo simulation. This article presents an overview of why an updated quality plan with variability is needed, what data the model requires to be useful, and how the new model works. Actual data from Hill AFB projects that have implemented this method are presented for review. The TSP quality plan is composed during meeting 5 of the launch by determining the defect injection rates and yields for each phase of the product development process. Using the team's historical averages for these rates and estimated hours per phase, the team can predict how many defects will likely be injected and removed as products move through this process. Unfortunately, these averages do not take into account normal variability in the process. However, by applying a Monte Carlo simulation to the standard TSP quality planning process, a team can determine the historical distribution of process variability and produce a plan with ranges for expected defects injected and removed, as well as a measure of goodness for the product and process.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2010
Accession Number
ADA523653

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  • David R. Webb

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