Product Platform Planning through Sensitivity Analysis and Improved QFD Approach

Abstract

The identification of platform parameters plays a key role to keep equilibrium between the external diversity and internal commonality. The relationship between the performance parameter and the design parameter in the traditional Quality of House (QoH) was evaluated by a correlation degree rather than an influence degree. The influence degree measures the design parameter’s influence on the performance parameter, and be more effective to evaluate the performance-design relationship. Hence, based on virtual orthogonal experiment, a method incorporated sensitivity analysis into the improved Quality Function Deployment (QFD) is proposed. Firstly, the virtual experiment scheme is designed through the orthogonal experiment table. Secondly, a virtual experiment environment is built by the built-in software, in which the design parameters are assigned with different values and the corresponding performances are monitored in real-time. Then the sensitivity matrix for design parameter is constructed to replace the correlation matrix in the QoH. Thereafter, the improved QFD can be used to identify the platform parameters. A case study for the smartphone of Samsung Galaxy A series is implemented to verify the effectiveness of the proposed method.