جستجوی مقالات مرتبط با کلیدواژه « machining process » در نشریات گروه « برق »

This paper presents a new method for regression model prediction in an uncertain environment. In practical engineering problems, in order to develop regression or ANN model for making predictions, the average of set of repeated observed values are introduced to the model as an input variable. Therefore, the estimated response of the process is also the average of a set of output values where the variation around the mean is not determinate. However, to provide unbiased and precise estimations, the predictions are required to be correct on average and the spread of date be specified. To address this issue, we proposed a method based on the fuzzy inference system, and genetic and linear programming algorithms. We consider the crisp inputs and the symmetrical triangular fuzzy output. The proposed algorithm is applied to fit the fuzzy regression model. In addition, we apply a simulation example and a practical example in the field of machining process to assess the performance of the proposed method in dealing with practical problems in which the output variables have the nature of uncertainty and impression. Finally, we compare the performance of the suggested method with other methods. Based on the examples, the proposed method is verified for prediction. The results show that the proposed method reduces the error values to a minimum level and is more accurate than the Linear Programming (LP) and fuzzy weights with linear programming (FWLP) methods.

We present a micro/nano-machining process to introduce nanostructured poly-silicon layer on the gate region of the pH-sensitive field effect transistors. Decoration of the gate of the field effect transistors by nanostructures plays an important role to improve the sensitivity of the pH-sensitive FETs. Electron beam lithography was exploited to realize the poly-Si nanopillars on the gate surface. Comparison between different micro and nanostructures demonstrates the potential of nanopillars to be utilized on the gate of this device rather than micro-conical structures (different size and shapes) and vertically carbon nanotubes. A high sensitivity of 500 mV/pH has been achieved, through the incorporation of silicon based nanopillars.