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Aluminium is extensively used in many manufacturing processes because of its intrinsic properties like soft, ductile, high electrical conductivity and highly corrosion resistant. Unfortunately, pure aluminium cannot give a required tensile strength, whereas by adding some other materials like particles of silicon carbide can give a proper strength and converted into a composite with adequate properties which is most suitable in the manufacturing of some specific biomedical instruments. It is well known that size and spatial distributions of particles are both influential in determining the mechanical properties of composite materials and, therefore, statistical characterization of these distributions is of prime importance if we wish to control the quality of the manufacturing processes for these materials. Many researchers have considered quantitative analysis of these features separately, but here we investigate the relationship between size and spatial distribution of the particles over an aluminium matrix. We have considered the actual sizes simply as ‘large’ or ‘small’ and, consequently, the characterization of the particle distribution patterns in the aluminium matrix can be carried out using statistical methods based on the theory of bivariate spatial point processes. We have applied this statistical approach to a sample of an aluminium alloy reinforced with silicon carbide particles. It is shown that the methods provide a complete characterization on the spatial interaction between small and large silicon carbide particles and it can be successfully used in a quality control step for the production of particulate composite materials used in the manufacturing of biomedical instruments.
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