Abstract

Borosilicate glass finds applications in micro-fluidic devices, micro-electro mechanical devices (MEMS) due to its bio-compatibility, optical transparency and anodic bonding capability with silicon wafer. Abrasive jet machining (AJM) is a potential process to machine low machinability brittle materials like borosilicate glass and ceramics with low specific power consumption and high material rates. This paper presents the details of developed micro-abrasive jet machine prototype and the experimental investigations on the influence of mixing chamber design on material removal rate in machining of borosilicate glass. Pressure, stand-off-distance, nozzle diameter, abrasive type (Al2O3 and SiC) and abrasive size were used as control factors. Experiments were conducted based on L16 orthogonal array and optimized with Taguchi’s method. ANOVA was performed to find the significant control factors and their percentage contribution. A multilayer perceptron artificial neural network (ANN) model was used with back-propagation algorithm to predict and validate experimental results. Experimental values of material removal rate with both the fixed and oscillating mixing chamber were compared with the predicted values. It was found that the oscillating mixing chamber has resulted good material removal rate and less spread for the given control factor combination due to uniform mixing of abrasive particles with compressed air

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