A BiF3 powder sample was prepared from the purchased Bi2O3 powder via the precipitation route. The photocatalytic performance of the prepared BiF3 powder was compared with the Bi2O3 powder and recognized as superior. The prepared BiF3 powder sample was added in a plaster of Paris (POP) matrix in the proportion of 0%, 1%, 5%, and 10% by wt% to form POP–BiF3(0%), POP–BiF3(1%), POP–BiF3(5%), and POP–BiF3(10%) composite pellets, respectively, and activated the photocatalytic property under the UV–light irradiation,in the POP. In this work, Resazurin (Rz) ink was utilized as an indicator to examine the photocatalytic activity and self-cleaning performance of POP–BiF3(0%), POP–BiF3(1%), POP–BiF3(5%), and POP–BiF3(10%) composite pellets. In addition to the digital photographic method, the UV–visible absorption technique was adopted to quantify the rate of the de-colorization of the Rz ink, which is a direct measure of comparative photocatalytic performance of samples.
EN23 is one of the most commonly used materials to fabricate forging die in Indian industries. The dies are manufactured through machining process and the parameters of the machining process have considerable impact on the roughness value of the material’s surface. While forging, it was found that die life varies with the change in the machining parametric value and this took my interest to investigate the area. Speed in rpm, feed in mm/rev, and depth of cut in mm were chosen as the process parameters for the investigation of the machining. Design of experiment was used to know the number of specimens required for proper investigation. Specimens were prepared using a L9 orthogonal array and a full factorial design. The optimal machining parameters were obtained using the Taguchi method. The optimal surface roughness value acquired using the L9 orthogonal array is fairly similar to the value obtained using the full factorial technique, according to a comparison of the results. Additionally, a mathematical tool called ANFIS was used to simulate the optimization process and anticipate the surface roughness values.
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