Experimental Analysis of Non-Ferrous Metals
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The material surfaces are engineered to impart specific properties, which could be different from those of the core material. These surface modifications are generally carried out to impart wear and corrosion resistance to the substrates and yet times these surface modifications enhance esthetic appearance of the substrates. Friction surfacing is an advanced manufacturing process, which has been successfully developed and commercialized over the past decade. The process is used for corrosion and wear resistant coatings and for reclamation of worn engineering components. At present the selectio...
The material surfaces are engineered to impart specific properties, which could be different from those of the core material. These surface modifications are generally carried out to impart wear and corrosion resistance to the substrates and yet times these surface modifications enhance esthetic appearance of the substrates. Friction surfacing is an advanced manufacturing process, which has been successfully developed and commercialized over the past decade. The process is used for corrosion and wear resistant coatings and for reclamation of worn engineering components. At present the selection of process parameters for new coating substrate geometries is by experiment requiring lengthy development work. The major requirement is for flexibility to enable rapid changes of process parameters in order to develop new applications, with variations of materials in a cost effective manner. Further improvement requires development of appropriate mathematical models of the process of optimization techniques for efficient experimental work. This paper considers the use of combined artificial intelligence and modeling techniques.
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