Optimization of correlated multiple quality characteristics robust design using principal component analysis

The use of the Taguchi method for improving the design and quality of products and processes has become widespread among different industries. The traditional Taguchi method focused on one characteristic to optimize a combination of parameter conditions. In practice, most products have more than one quality characteristic. The methods of multiple quality characteristics design have become very important for industries. Several studies have presented approaches addressing multiple quality characteristics. Few published articles have focused primarily on optimizing correlated multiple quality characteristics. This research presents an approach to optimizing correlated multiple quality characteristics by using proportion of quality loss reduction and principal component analysis. The results reveal the advantages of this approach in that the optimal parameter design using proportion of quality loss reduction is the same as that using the Taguchi traditional method for one quality characteristic; the chosen optimal design is robust for optimizing correlated multiple quality characteristics.