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Achieving Robust Designs with Six Sigma: Dependable, Reliable, and Affordable

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Developing "best-in-class" robust designs is crucial for creating competitive advantages. Customers want their products to be dependable—"plug-and-play." They also expect them to be reliable—"last a long time." Furthermore, customers are cost-sensible; they anticipate that products will be affordable. Becoming robust means seeking win–win solutions for productivity and quality improvement. This chapter will help you to achieve all of this.
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Developing "best-in-class" robust designs is crucial for creating competitive advantages. Customers want their products to be dependable—"plug-and-play." They also expect them to be reliable—"last a long time." Furthermore, customers are cost-sensible; they anticipate that products will be affordable. Becoming robust means seeking win–win solutions for productivity and quality improvement. So far, robust design has been a "road less traveled." Very few engineering managers and professionals are aware of robust design methods; even fewer of them have hands-on experience in developing robust designs. As a breakthrough philosophy, process, and methodology, Six Sigma offers a refreshing approach to systematically implement robust designs. This chapter outlines a process for engineering robust designs with Six Sigma and provides a road map.

1.1 Six Sigma and Robust Design

Six Sigma is a rigorous and disciplined methodology that uses data and statistical analysis to measure and improve a company's operational performance. It identifies and eliminates "defects" in product development, manufacturing, and service-related processes. The goal of Six Sigma is to increase profits by eliminating variability, defects, and waste that undermine customer loyalty.

A best-in-class robust design starts with three categories of static response metrics: the smaller-the-better, the nominal-the-best, and the larger-the-better. Each of these characteristics should be measurable on a continuous scale.

  • A smaller-the-better response is a measured characteristic with an ideal value of zero. As the value for this type of response decreases, quality improves.
  • A nominal-the-best response is a measured characteristic with a specific target (nominal) value that is considered ideal.
  • A larger-the-better response is a measured characteristic with an ideal value of infinity. As the value for this type of response increases, quality improves.

Besides static responses, dynamic responses are also encountered when developing engineering products. A dynamic response is a characteristic that, ideally, increases along a continuous scale in proportion to input from the system. Dynamic responses should be related to the transfer of energy through the system. To develop robust products, dynamic formulations are recommended for the maximum benefit of the application of a Parameter Design methodology (see Chapter 7). Using a dynamic response provides the greatest long-term benefits, but it requires the most engineering know-how.

The Six Sigma approach for engineering robust designs depends heavily on formulating the Voice-of-Customers (VOCs) and Critical-to-Quality (CTQ) characteristics through experiments. The following steps provide a thorough, organized framework for planning, managing, conducting, and analyzing robust design experiments.

  1. Identify project and organize team
  2. Develop VOC models
  3. Formulate the CTQs based on VOCs
  4. Control the energy transformation for each CTQ
  5. Determine control and noise factors for each CTQ
  6. Establish the control factor matrix

These steps, although specified sequentially, should not be used as a "cookbook approach" to experimentation; instead, they should be used in an iterative way. During each stage of development, consider the decisions that were made in earlier steps. Your team may need to revisit previous steps in light of insights gained farther along in the process.

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