This paper discuses the robust design method for reducing cost and improving quality. Robust design id Dr. Taguchi’s approach for determining the optimum configuration of design parameters for performance, quality and cost. The method will be briefly explained and its applications will be demonstrated by the use of an example. The results will suggest that the robust design method is an efficient, disciplined approach that can aid product delivery team in designing for cost.
 
 

Delivering reliable, high quality products and processes at low cost has become the key to survival in today’s global economy. Driven the need to compete on cost and performance, many quality organizations are increasingly focusing on the optimization of product design. This reflects the realization that quality can be not been achieved economically through inspection. Designing in quality is cheaper than trying to inspect and re-engineer it in after a product hits the production floor. Thus new philosophy, technology and advanced statistical tools must be employed to design high quality products at low cost.

Since late 1950s Dr. Tagushi has introduced several new statistical tools and concepts of quality improvement that depend on the statistical theory for Design of Experiments. These methods of design optimization developed by Dr. Tagushi are also refereed to as Robust Design. The robust design method provides a systematic and efficient approach for finding the near optimum combination of design parameters so that the product is functional, exhibits a high level of performance, and is robust to noise factors. Noise factors are those parameters that are uncontrollable or are too expensive to control.