Intelligent self-adaptive decision model for product innovation in FE

Abstract

Companies need New Product Development (NPD) more than ever to satisfy rapidly changing customer needs, to secure and increase their share in the global market. Continuous innovation stream is required to succeed there with best promising ideas to be selected at the fuzzy Front End (FFE). The fuzziness of FE is remedied here by creating an intelligent, self-adaptive and flexible decision model The proposed model is non-bureaucratic, manages fuzziness, and it is capable to provide insight for future trends Furthermore, it contributes to knowledge accumulation by maintaining all data of ideas, both accepted or rejected, enabling knowledge based design. The intelligent is provided by the growth of idea, their computation and assessment. I.e. the model itself weighs ideas independently and adaptively by respecting the size and population of the associated idea group. This is achieved by using K-means clustering algorithm by which meaningful changes in accumulated ideas are detected to calculate trend. The synthesized model supports managers and researchers to organize the FFE.