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Another methodology has been proposed by Sharma and Ragsdell to bring about similarity among the three cases smaller-the-better, nominal-the-best, and larger-the-btter by introducing a term called the “target-mean ratio” and proposing a unified formula for quality loss. The new methodology has some implications that need to be addressed. This paper attempts to study the implications and effects of the new methodology on the field of quality engineering. This paper presents an implied classification of LTB characteristics according to Taguchi on the basis of a target value at infinity and also discusses the classification of LTB characteristics based on the new methodology. A new concept of “Complementary Characteristic” is also suggested. It is suggested that whether a given LTB characteristic or its complementary characteristic is considered for one and the same case, the quality loss must be equal for both the characteristics.

Quality Function Deployment (QFD) is a process to translate the Voice of the Customer (VOC) into the technical will of the enterprise. QFD is an integral step in the flowdown of customer requirements into the product system, subsystem(s), components and manufacturing processes. The House of Quality (HOQ) is a fundamental element of the QFD process, which provides a framework to relate customer attributes to engineering characteristics at the product architecture level. This paper presents the advantages and limitations of the symbols and weighting schemes used in constructing the relationship matrix in the classical House of Quality of the Quality Function Deployment process. The selection of the weighting scheme for function flowdown during the early design phase impacts the prioritization of engineering characteristics. A simple example using an nxn matrix is provided to illustrate the impact.

The concept of product or system function is considered as described in the Taguchi System of Quality Engineering. The importance of transfer functions is also discussed and a review of conventional value analysis techniques is given. This paper proposes a combination of the principles of robust design and value methodology to enable on-target functionality and direct cost allocation early in the product development process. The discussion on integration of value analysis principles in robust design methodology is provided considering the six sigma environment.