Multi objective optimization of rotorcraft compact spinning system using fuzzy-genetic model

In this paper, the mechanical and physical properties of rotorcraft compact spinning yarns were evaluated. For this aim, the filament pre-tension, yarn count and type of sheath fibers were selected as the controllable factors, and the effect of them on the elongation and hairiness was investigated statistically and the obtained results indicated that controllable factors have significant effect on the measured properties. In the next step, the relation between factors and measured properties was modeled by fuzzy interface system and genetic algorithm was used to optimize the number of membership function and its kind. It was observed that the accuracy of obtained models for both elongation and hairiness is acceptable (correlation coefficient for both models was: 0.99). Finally, to find a set of controllable factors to produce a yarn with high elongation and low hairiness, multi objective optimization was applied by means of non-dominated sorting genetic algorithm and a set of trade off solutions obtained so that each solution can be accepted as a response.