A Study of Optimization of Process by Using Taguchi's Parameter Design Approach

Taguchi Methods (TMs) are statistical methods developed by Genichi Taguchi to improve the quality of manufactured goods. Recently, TMs have been used in the areas of biotechnology, marketing, advertising industries, corporations and universities (Sreenivas Rao et al., 2004). TMs are intended as cost-effective method to improve the performance of a product by reducing its variability in the customer’s usage conditions. To meet international competition (Logethetis, 1992) the quality should start from the stage of product design and carried to after sale service also. Quality achieved by process optimization is found to be very cost-effective in gaining and maintaining a competitive pos6ition in the world market. Taguchis’s method (TM) of quality engineering encompasses all stages of product or process development, but the key element for achieving high quality and low cost is the parameter design. Through parameter design, optimal levels of process parameters are selected, such that the influence of uncontrollable factors causes minimum variation of system performance. The objective of this paper is to analyze and describe Taguchi’s methodology of parameter design approach and to identify the various significant control and noise factors of a process to be optimized. The paper also presents the criteria for the use and selection of Orthogonal Arrays (OAs) and Signal-to-Noise ratio (S/N ratio) for designing experiments and minimizing Taguchi’s quality variation caused by various noise factors.