AXIOMATIC DESIGN FOR SIX SIGMA

Six Sigma is one of the most innovative and successful methodologies to have been introduced in recent years at an industrial level. The goal of this approach is to increase the efficiency of the company system and to generally reduce the costs involved in the production process. The instruments used are mainly statistical: a representative CTQ characteristic is studied for each Six Sigma Project, and the causes of any non-conformities found, as well as their effects on the system, are analysed. This makes it possible to evaluate the best choice for optimising the system and to identify the risk associated with each choice; Six Sigma is, therefore, generally used for optimising processes. After an initial Define phase, Six Sigma can be subdivided into the following phases: Measure, Analyze, Improve & Control. Product optimisation can be developed in greater detail by using Design For Six Sigma (DFSS) techniques during the Improve phase. These techniques adopt a statistical approach in order to assess which design solutions are best and the system response associated with the solution chosen. The aims of this paper are as follows. Firstly, to demonstrate that the DFSS techniques used for calculating a given process capability can interface with the Axiomatic Design (AD) schematisation of the product. In particular the meaning and use of the first and second axiom is focused on as a demonstration of how AD can be used within the framework of Six Sigma product optimisation. Secondly to demonstrate how the AD approach can be advantageous not only in the Improve phase, but also in the other phases of th