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Pressure die-casting is generally useful in casting of zinc, Aluminium, magnesium, lead and tin-based alloys. Better surface finish, tolerances and dimensional accuracy can be achieved by optimization of significant process parameters of Pressure die casting (PDC) such as solidifying-time, melting-temperature, fill-up-time, inoculation-pressure and plunger-velocity etc. In addition, with the proper selection of optimum process parameters the PDC defects such as flash, cold-shut, porosity, misrun, etc. also minimized. In the present work, minimization of the PDC defects using artificial intelligent technique comprises of Genetic-algorithm (GA) and fuzzy-logic-methodology (FLM). A380: A silicon based aluminium alloy carburetor-housing is considered for the same. L18 orthogonal array based Taguchi design approach is considered for number of % defects per batch in a lot of 500 components as FLM knowledge base. To estimate the extent of accuracy of predictions made by FLM, regression analysis isperformed. FLM is also validated with R-square approach. Besides this, ANOVA has also been applied to estimate the significance level in terms of percent contribution among the input parameters and defects during PDC. Solidifying-time & fill-up-time has been found most sensitive parameter. Melting-temperature, plunger-velocity and inoculation-pressure are also identified as influencing parameters with comparatively low percent contribution. To optimize process parameters GA is applied and the fitness value is calculated using FLM. From this combination of artificial intelligent approach an optimum combination of process parameter has been obtained. Further, the results are compared with the Taguchi methodology and the approach provides appreciable amount of decrease in PDC-defects by fine tuning the input parameter.

In the current research, rotary ultrasonic machining was used to drill holes in quartz material. The effect of different RUM parameters namely tool feed rate, tool rotational speed and ultrasonic power on material removal rate and surface roughness has been studied experimentally. The response surface methodology with central composite design has been used to design the experiments. From the desirability approach, the optimum setting of the rotary ultrasonic machining parameters was found to be the tool rotational speed of 4968 rpm, feed rate of 0.55 mm/min, and ultrasonic power of 80% for achieving the maximum MRR of 0.2135 mm3/s and minimum SR of 0.3685 μm. Microstructure analysis of the machined surface was performed by using scanning electron microscopy in order to study the mechanisms of material removal under the different settings of RUM parameters. It was observed that at very low feed (0.08 mm/min) and high rpm (5681) the material is predominantly removed by plastic deformation whereas at high feed (0.92 mm/min) and low rpm (2318) the material is removed by brittle fracture.

Rotary ultrasonic machining has the capability to process the materials which are very hard, brittle and electrically non-conductive, with efficiency and cost-effectiveness. The current investigation is focused on the use of Taguchi-Grey relational analysis to improve the machining performance of Rotary ultrasonically machined quartz glass. Ideal machining parameters were calculated by grey relational grade calculated in grey relational analysis which was designed for simultaneous optimization of material removal rate and surface roughness. The rotary ultrasonic machining parameters setting with tool rotational speed of 5000 rpm, tool feedrate of 0.75 mm/min, and ultrasonic power of 55% were found to have the highest grey relation grade resulting in the high material removal rate and low surface roughness of the processed material. The tool feed rate was found to be the most critical parameter followed by ultrasonic power and tool rotational speed on the rotary ultrasonic machining characteristics. Confirmatory experiments were also executed to authenticate the forecasted results obtained from the Taguchi-Grey relational analysis. Furthermore, the microstructural investigation was carried out to comprehend the mechanism of material removal in the rotary ultrasonic machining of quartz glass at optimum parameter setting. It was found that the material was removed in the brittle mode and abrasion during the machining at optimum parameter setting. The sharp cutting edges of the diamond grits have caused the abrasive wear and brittle fracture of the quartz material. The interlinking of the cracks results in the pullout of the grains and consequently deeper grooves are formed on the machined surface.