M.P. Peres

Bio: M.P. Peres is an academic researcher from Sao Paulo State University. The author has contributed to research in topics: Titanium & Electroplating. The author has an hindex of 1, co-authored 1 publications receiving 168 citations.

Review: Optimization of cutting parameters on delamination based on Taguchi method during drilling of GFRP composite

Abstract: Drilling of glass fibre reinforced plastic (GFRP) composite is substantially different from metallic materials due to its mechanical properties. The drilling of this material may generate delamination of drilled holes on workpiece. The purpose of this paper is to investigate the influence of the cutting parameters, such as cutting speed and feed rate, and point angle on delamination produced when drilling a GFRP composite. The damage generated associated with drilling GFRP composites were observed, both at the entrance and the exit during the drilling. Hence it is essential to obtain optimum cutting parameters minimizing delamination at drilling of GFRP composites. Moreover, this paper presents the application of Taguchi method and analysis of variance (ANOVA) for minimization of delamination influenced by drilling parameters and drill point angle. The optimum drilling parameter combination was obtained by using the analysis of signal-to-noise ratio. The conclusion revealed that feed rate and cutting speed were the most influential factor on the delamination, respectively. The best results of the delamination were obtained at lower cutting speeds and feed rates.

Modeling and optimization of burr height in drilling of Al-7075 using Taguchi method and response surface methodology

Abstract: This investigation presents the use of Taguchi and response surface methodologies for minimizing the burr height and the surface roughness in drilling Al-7075. The Taguchi method, a powerful tool to design optimization for quality, is used to find optimal cutting parameters. Response surface methodology is useful for modeling and analyzing engineering problems. The purpose of this paper was to investigate the influence of cutting parameters, such as cutting speed and feed rate, and point angle on burr height and surface roughness produced when drilling Al-7075. A plan of experiments, based on L27 Taguchi design method, was performed drilling with cutting parameters in Al-7075. All tests were run without coolant at cutting speeds of 4, 12, and 20 m/min and feed rates of 0.1, 0.2, and 0.3 mm/rev and point angle of 90°, 118°, and 135°. The orthogonal array, signal-to-noise ratio, and analysis of variance (ANOVA) were employed to investigate the optimal drilling parameters of Al-7075. From the analysis of means and ANOVA, the optimal combination levels and the significant drilling parameters on burr height and surface roughness were obtained. The optimization results showed that the combination of low cutting speed, low feed rate, and high point angle is necessary to minimize burr height. The best results of the surface roughness were obtained at lower cutting speed and feed rates while at higher point angle. The predicted values and measured values are quite close to each other; therefore, this result indicates that the developed models can be effectively used to predict the burr height and the surface roughness on drilling of Al-7075.

A simulation-based optimisation approach for identifying key determinants for sustainable transportation planning

Abstract: Sustainable transportation planning is vital to manage resources effectively and minimise air pollution, noise and congestion in cities. In this paper, we present a simulation-based optimisation approach for identifying key determinants for sustainable transportation planning. The proposed approach comprises of five steps. In the first step, a system dynamics (SD) based conceptual model is proposed for understanding sustainable transportation system and its components. Step 2 involves running the SD model to generate data on sustainable transportation key factors. Step 3 involves conducting design of experiments and analysis of variance on the simulated data to develop regression-based metamodel for identifying the key determinants for sustainable transportation planning. In step 4, optimisation of the key factors for achieving sustainability is performed. Finally, in step 5, sensitivity analysis is conducted to determine the sensitivity of model outputs (dependent variables) to changes in input p...