No abstract

Tribological behavior of AA-6063 casted by microwave casting process was investigated. In this work, sliding wear analysis has been done on in-situ cast developed through the novel technique. The in-situ cast of AA-6063 was developed using microwave irradiation. Sliding wear process parameters such as normal load, sliding velocity and sliding distance are optimized through Taguchi technique. L9 orthogonal array and signal-to-noise (S/N) analysis is used to obtain the optimumprocess parametersfor wear rate (WR) as the selected response.After optimization, a confirmatory test was performed using the analysis of variance (ANOVA).Scanning electron microscopy (SEM) images, energy dispersive X-ray spectroscopy (EDS) images and frictional characterisationwere usedto study the mechanism of wear.Using the experimental data an adaptive neuro fuzzy inference system (ANFIS) model has been developed and which was further tested using average wear rate.

No abstract

In-situ microwave casting is one of the recently developed advanced metal casting techniques in which the bulk metal and mould assembly are exposed to microwave radiations at 2.45 GHz. In in-situ microwave casting, the exposure and self-pouring is done inside the microwave. The cast quality that has been casted through the microwave casting process is directly dependent on the process parameters that are selected during the process. This paper explores the effect of process parameters on hardness of AA-6063 by using microwave hybrid heating technique. Apply Taguchi L9 orthogonal array to conduct the experimentations. Here consider three process parameters: solidification environment, susceptor material and microwave power.

Tribological behaviour of AA-6063 casted by microwave casting process was investigated. In this present work, sliding wear analysis has done on in-situ cast developed through the novel technique. The in-situ cast of AA-6063 was developed using microwave irradiation. Sliding wear variables like normal load, sliding velocity and sliding distance are optimized through Taguchi technique. L9 orthogonal array and signal-to-noise analysis is used to obtain the optimum process parameter for wear rate (WR) as the selected response. After development, validation tests were performed using variance analysis (ANOVA). The addition of this electron scanning (SEM) microscope, scattering X-ray spectroscopy (EDX) images and the friction characteristics was done to study the wear rate. The adaptive neuro-fuzzy inference device (ANFIS) model changed into evolved the use of test information and re-evaluated the use of an aging level for wear rate.