Robust design means designing a product having minimal quality losses. There are several methodologies associated with robust design. The major ones are traditional design of experiments (DOE) and the Taguchi approach. Traditional design of experiments is an experimental tool used to establish both parametric relationships and a product/process model in the early (applied research) stages of the design process. However, traditional design of experiments can be very costly, particularly, when it is desired to examine many parameters and their integrative effects. Traditional DOE examines various causes of performance for their contribution to variation, with a focus on arriving at the most influential causes of variation. Traditional design of experiments may be a useful tool in the preliminary design stage for modeling, parameter determination, research, and establishing a general understanding of product phenomena.
A major approach to robust design is the Taguchi approach. The Taguchi approach focuses on quality optimization. "Quality optimization" is based on Dr. Taguchi's definition of quality. Taguchi (2004), in his book Introduction to Quality Engineering, states that any failure to satisfy the customer is a loss. Loss is determined by variation of performance from optimum target values. Loss, therefore, in the form of variability from best target values, is the enemy of quality. The goal is to minimize variation by designing a system (product, process, or part) having the best combination of factors, i.e., centering on the optimum target values with minimal variability. By focusing on the bull's-eye, the product, process, or part is insensitive to those normally uncontrollable "noise" factors that contribute to poor product performance and business failures. The Taguchi approach is not simply "just another form of design of experiments." It is a major part of the successful total quality management (TQM) philosophy.
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