Overview

Taguchi's quality loss function provides a measure of the overall loss to society when a product fails to meet its target functionality and reliability. His signal-to-noise ratio measures the positive quality contribution from controllable or design factors versus the negative quality contribution from uncontrollable or noise factors. Taguchi Methods involve seven steps, beginning with a clear statement of the design problem and ending with a confirming statistical experiment showing how parameter choices will enhance robustness. An example from electrical circuit design is presented, because it is much more similar to software design than mechanical design, where Taguchi Methods have found their largest application. A more-detailed example from software design or product improvement is given, building on the previous example. Taguchi further developed and applied an earlier technique involving Latin squares or orthogonal matrices to allow the evaluation on multiple parameters simultaneously. His use of orthogonal matrices permits a multifactorial analysis that is far more efficient than a conventional "bottleneck" analysis. It also allows the study of factor interactions.

Chapter Outline

• Taguchi Methods for Robust Software Design

• An Example from Engineering Design

• An Example from Software Design and Development

• Orthogonal Matrices for Taguchi Parameter Design Experiments

• Applications to the Design of Trustworthy Software

• Key Points

• Additional Resources

• Internet Exercises

• Review Questions

• Discussion Questions

• Problems

• Endnotes