Application of TOPSIS in the Taguchi Method for Optimal Machining Parameter Selection

Taguchi method is frequently used in product/process design optimization. This method explores the concept of SN ratio to optimize the given process control parameters with respect to an objective function (called response) via reduction in variances. In practice, a product or process is generally consists of a number of conflicting responses while Taguchi method fails to overcome such a multi-response optimization problem. It is therefore, essential, that an equivalent aggregated index has to be determined (by logical accumulation of multiple responses) which can be finally optimized by Taguchi method. Multi-Criteria Decision Making (MCDM) is a methodology to compare, select and rank multiple alternatives that involve disproportionate criteria attributes. Among various MCDM approaches, TOPSIS (technique for order preference by similarity to ideal solution) can be efficiently used to identify the best alternative solution from a finite set of points. In the present paper, TOPSIS based MCDM approach has been adopted in combination with Taguchi's robust design philosophy to optimize multiple surface roughness parameters of machined GFRP polyester composites. TOPSIS has been used to convert multiple responses to a single preference number which has been treated as Multi-Performance Characteristic Index (MPCI). MPCI has been optimized finally by the Taguchi method. The proposed methodology and the result obtained thereof has been illustrated in detail.