Six sigma design through process optimization using robust design method

Six Sigma or high level of process output is very common interest of world class industry. Six Sigma methodology not only ensures the quality of products but also ensures the quality of each element associated with that product, from conception to the end of the product life cycle. Because of such ensuring, Six Sigma qualities made an evolution in industry in 1990's. Now Six Sigma is almost a proven methodology for industry to produce high level quality of products. To achieve Six Sigma quality, industries need to optimize the process; there are many mathematical, engineering and statistical methods that are being used for optimizing the process. However, these methods do not always deal with a combined consideration of the effects of mean and variability of quality characteristics of the product. One of the major steps to achieve a high level of quality is to optimize the process. It is well known that processes have many inputs, and inputs are key element to the quality of process output. Therefore, optimization of the process contributes a vital impact for Six Sigma. The proposed Taguchi robust method optimization will take both effects such as mean and variation of product quality characteristics into consideration. In view of Dr. Taguchi's very popular phrase "loss to society", in this research we applied Taguchi method to optimize the process for Six Sigma design. We showed that a positive gradient relationship exists between S/N ratio and process sigma. The robust design method ensures minimum variation of quality characteristics of the product or to produce almost "defects free" products. Due to such minimal variation in product, it will ensure minimum use of resources for manufacturing of product. Therefore unit cost of production will become lower and as well as it satisfies customer's implied and stated need. These are the main objectives of Six Sigma design and this research contributes to formulate a generalized and easier method to optimize the process for Six Sigma design in an industry