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The aging phenomenon in age hardenable aluminum alloys is complex and well under research. The supersaturated solid solution of these alloys, during aging, undergoes complex precipitation causing increase in strength with time. These alloys have wide range of applications in the aviation and automotive industry. The properties such as electrical conductivity and hardness of these alloys are well related to its precipitation behavior. Cryogenic treatment (CT) has been tried on tool and alloy steels where it has been found that this treatment positively affects the wear resistance and also causes uniformity in structure. The CT has become an important step in the manufacturing of tool steels.This work comprises applying CT at À185 C to AA 6061 aluminum alloy for various time periods. The treatment was sequenced in the conventional solutionizing and artificial aging. This sequence of treatment has not been reported in the literature. The characterization was done using scanning electron microscopy. The behavior of this alloy to the treatment was identified by measuring electrical conductivity and hardness. The surface roughness of this alloy was also found to be highly influenced by this treatment.

Obtaining good surface finish in tool steels by conventional machining is a difficult task. Nontraditional material removal processes, for example, wire electro discharge machining (WEDM), are very useful for precision manufacturing. In WEDM, it is very difficult to choose the correct combination of machining parameters and materials. Traditionally, heat treatment process is used for improving the hardness of tool steels, whereas cryogenic treatment is used as a secondary treatment to enhance the hardness as well as the wear properties. In this work, the effect of WEDM parameters on surface finish of cryo-treated AISI D2 tool steel is investigated. Taguchi DOE methodology is used for designing and conducting the experiments. The surface roughness was considered a response for improving surface quality.ANOVA is used to optimize the machining process for better surface quality. A mathematical model is developed for predicting the response quality using regression analysis. Further experiments were conducted with optimized parameters to authenticate the usefulness of the proposed model. The confirmation experimental result shows that the model suggested by the Taguchi's method is suitable for improving the surface quality by reducing the surface roughness.

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