Abstract
Micromachining of advanced ceramics has been growing tremendously especially in the MEMs industry. All the time, researchers and industrial engineers have strived to achieve the lowest production cost at possible highest quality in micromachining operations. In this paper, the micromachining operation by means of chemical etching of ceramics is discussed. Machinable glass-ceramic (MGC) is used as the substrate and the influence of various input factors of the etching process is analyzed. These factors include etching temperature, etching period and, etching solution. The etching rate is then analyzed by calculating the weight loss per minutes. In order to establish the relationship between these factors, central composite design (CCD) and artificial neural network are used. Additionally, a prediction model that can be used with a high level of confidence in the industry is created at the end of the analysis.
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