Abstract

The present research investigates the wear characteristics of an epoxy composite reinforced with a novel Caesalpinia decapetala (CD) shell. The CD is available abundantly worldwide, especially in Ethiopia, particularly in East and West Oromia near West Harar. The composite specimens were processed in the open mould casting technique by varying the vol.% of CD in 10, 20, and 30. EDS is used to evaluate the important elements present in the CD. The density of composites increases with the increase in the content of CD, while the void content estimations reveal good control over the composite fabrication. The wear response of composites is investigated by varying the sliding distance and load and by maintaining a fixed velocity (5 m/s). At a 5 km slide distance and 50 N load, the 30 vol.% Caesalpinia decapetala composition depicts better wear resistance and friction coefficient than other compositions. Experimental results are used to envisage the ideal wear factors and to assess the influence of parameters over the two wear objectives, wear rate and CoF. The grey relational analysis- (GRA-) coupled artificial neural network (ANN) hybrid technique was employed for the prediction and validation. It has been observed that a trivial error of 0.49% amidst GRA and ANN estimation is observed.

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