article · Scientific African
This study examines the wear behaviour of hybrid aluminium matrix composites reinforced with silicon carbide and varying proportions of palm kernel shell ash. Samples were manufactured using a double-stir casting technique and evaluated under varying abrasion loads and operational speeds using a Taber testing machine. Statistical analysis via Taguchi and grey relational methods identified the optimal operational conditions to minimise wear index and material volume loss. Testing revealed that rotational speed and applied load exerted a stronger influence on wear performance than the overall proportion of reinforcement materials. The optimal combination for wear resistance required the lowest load and speed settings alongside specific reinforcement levels. Confirmation tests verified that experimental wear metrics closely aligned with statistical predictions, demonstrating the effectiveness of the analytical models in establishing operating parameters for these composite materials.
Understanding how materials degrade under friction helps engineers design more durable mechanical components. By evaluating agricultural waste ash alongside silicon carbide as reinforcement, this work outlines how processing conditions affect wear resistance. Demonstrating that operational factors like speed and load dictate wear more than reinforcement levels provides guidance for managing friction in lightweight metal components.
This research represents early-stage laboratory work on composite formulation and wear characterisation. It could inform materials engineers and component manufacturers seeking wear-resistant, lightweight aluminium parts that incorporate agricultural by-products such as palm kernel shell ash. However, moving toward practical application would require evaluating these formulations under industrial operating environments, scaling the double-stir casting process, and testing complex mechanical properties beyond basic laboratory abrasion.
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The tribological properties of synthesized hybrid reinforced aluminium matrix composites (AMCs) have been optimized in this study using Taguchi and grey relational analysis (GRA), methods where a L16 orthogonal array was used for the experimental design. Hybrid palm kernel shell ash (0–6 wt.%) and SiC (2 wt.%) formed the reinforcements of interest, which were combined in ratios ranging between 2 and 8 wt.%. Different loads (250, 500, 750, and 1000 g) and speeds (250, 500, 750, and 1000 rpm) were used as control factors. The wear samples were produced using the double-stir casting method, while a Taber type abrasion machine was used for the wear experiments. The evaluated wear index and volume loss showed that the speed and load were better influential factors on the performance characteristics of the composites than wt.% of reinforcements. The Taguchi-Grey's relational analysis gave the optimal combination of the process parameters for both the wear index and the volume loss as A3B1C1 (Reinforcement = 6 wt.%; Load = 250 g; Speed = 250 rpm) and A1B1C1 (Reinforcement = 2 wt.%; Load = 250 g; Speed = 250 rpm), respectively. The predicted and experimental values at the optimum conditions were confirmed to be within the range based on the performance of the confirmation test. The utilization of Taguchi and GRA methods have significantly confirmed that the influence of speed as a factor of performance was higher than load, which in turn was a better influencing factor than wt.% of reinforcements.
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DOI: 10.1016/j.sciaf.2021.e00839
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