The present study focused to improve material characteristics and quality in terms of the NaOH concentration for treating the coconut and bamboo fiber to enhance the mechanical properties of natural fiber polymer-based hybrid composites. The NaOH-treated fibers were washed thoroughly using distilled water and allowed to dry for 24 hours. Composition of each specimen, bamboo (B) and coconut (C) fiber with epoxy composite, was prepared by hand layup process as per the American Society for Testing and Materials (ASTM) standard. The proportionality of the material was carefully fulfilled according to the previous literature reports. The weight fraction of the composite material content was set to be 30% and 70% of epoxy (E) resin and isolated fibers. Three distinct criteria were used to calculate mechanical parameters such as tensile strength, flexural strength, and material hardness. It was found that the combination of 70% E with 30% BC of hybridized composite had a maximum tensile strength of 62.42 MPa, whereas the flexural strength and hardness of the other combinations, such as 70% E with 30% C and 70% E with 30% B, were observed to be 58 MPa and 185 HRC (Hardness Rockwell C), respectively.
The goal of this observes is to take a look at the effect of machining parameters on surface roughness in end milling. An incipient technique in modelling surface roughness that makes use of synthetic perspicacity implements is defined in this paper. This paper fixates on growing empirical models utilizing fuzzy logic and regression analysis. The values of surface roughness presaged with the aid of using those fashions are then in comparison. The effects confirmed that the proposed gadget can considerably boom the precision of the product profile whilst in comparison to the traditional approaches, like regression analysis. The effects designate that the regression modelling method may be effectively applied for the presage of surface roughness in dry machining.
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