Poisson distribution: How tensile properties of particulate polymer composites are enhanced in a Poisson-motivated Taguchi method

Ajibade, O.A. ; Agunsoye, J.O. ; Oke, S.A. (2019)

Article

This paper examines how the Poisson distribution is being used to model the tensile properties of selected particulate reinforced polymer composites. While past studies have shown that the Taguchi method provides robust optimized composites for cost and maximum wastes reinforcement utilization, the link between optimisation and particulates with an indefinitely large number of trials to optimize has not been overtly revealed. This paper proposes a Poisson distribution to obtain the probability of each tensile property occurring independently at a fixed rate within the Taguchi scheme to address this issue. These were used as factor-levels in a Poisson-motivated Taguchi optimisation process and tested on five different composite blends of a dual reinforcement and epoxy resin matrix. The composites were treated under various curing regimes (80, 100, 120 oC). Based on the tensile properties of extension, load, strain and stress, the Taguchi method yielded an optimal parametric setting of A4B1C4D4 for the orange peel/coconut, palm kernel/coconut and periwinkle egg shell composites, while optimal parametric settings of A4B1C4D1 and A4B1C4D2 were obtained for the orange peel/periwinkle and palm kernel/egg shell composites, respectively. The Poisson motivated-Taguchi optimisation yielded optimal parametric settings of A1-2,B1-2,C1D4, A1-2,B1-2,C1,D1,4, A1-2,B1-2,C1,D1,4, A1-2,B1-2,C1,D1,4 and A1-2,B1-2,C1,D1,4, respectively, for orange peel/coconut, palm kernel/coconut, periwinkle/egg, orange peel/periwinkle and palm kernel/egg shell blends. Hence, there is a possibility of obtaining more than one factor level as an optimum condition. Overall, by analyzing the role of the Poisson distribution to enhance the tensile properties of selected polymer composites, our model departs from existing views of Taguchi optimisation methods and sheds novel light on optimisation enhancement.