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This work employs the T6 heat treatment process to aluminium-clay (Al-Clay) composite consisting of 15 wt% clay. The samples were solutionized at 500°C, 550°C and 600°C, and were quenched in air, oil and water. Selected samples of the heat-treated composite were subjected to wear tests using Denison T62 HS pin-on-disc wear-testing machine in accordance with ASTM: G99-05 standard. The effects of two different loads (4 and 10 N) and three sliding speeds (200, 500 and 1000 rpm) under dry sliding conditions were investigated. The potential of using back-propagation neural network with 4-10-1 architecture was explored to predict the wear rate of the heat-treated composites. The results show that the performance of Levenberg-Marquardt training algorithm is superior to all other algorithms used. The well-trained ANN system satisfactorily predicted the experimental results and can be handy for an optimum design and also an alternative technique to evaluate wear rate. ARTICLE HISTORY

Steels are used widely for production of machine components due to their versatility, low cost, ease of production and modification of their properties through heat-treatment. ST60Mn Steel is one of the common high strength steel produced in Nigeria and utilized for machine building purposes. Components made from this materials failed by wear, corrosion or both mechanism. The aim of this paper is to determine the influence of austempering heat-treatment on the corrosion-wear resistance of ST60Mn steel in cassava juice. The heat-treatment was performed by varying the austenitizing temperature, austempering temperature and time. The corrosion wear resistance was investigated under an instrumented pin-on-disc wear testing machine with the steel samples dipped in the cassava juice. The results obtained showed that the austempered ST60Mn steel has a wear rate of 3.0µg/cycle. While, the un-heat-treatment sample possess 70.1µg/cycle. This is a tremendous improvement in corrosion wear rate through the austempering heat treatment.

Most aluminum profiles' production by deep-drawing and extrusion processes require certain degree of structural homogeneity because of the segregated second-phase particles in the as-cast structure. Rolled texture and directionality in properties often give rise to excessive earring, breakout, and tears. This study investigates the effect of heat treatment (artificial aging) on the anisotropic behavior of AA6063 alloy between rolling direction (0 • ) through 90• directions. The results show significant reduction in property variability in the aged samples along the rolling direction 0• , and 90• directions compared with the as-cast samples. This gave rise to improved % elongation, impact toughness, and substantial reduction (33.3%) in hardness. These results are capable of achieving huge savings in die conditioning and replacement with improved quality and sale of deep-drawn AA6063 alloy profiles for sustained profitability.

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