Engenharia Mecânica
URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/23
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Resultados da Pesquisa
- Surface integrity analysis in machining of hardened AISI 4140 steel(2017-01-23) STIPKOVIC, M. A.; Ed Claudio Bordinassi; Farias, Adalto; Sergio DelijaicovThis study aimed to analyze the residual stresses and roughness in finishing milling of AISI 4140 steel, quenched and tempered up to hardness of 58 HRC. Machining operations were performed with the use of CBN inserts and by varying three basic cutting parameters (cutting speed, feed per tooth and cutting depth). Hardened materials are typically machined by abrasive processes, which in turn are more expensive and complex to be studied due to the undefined cutting geometry of the grinding wheel. A series of machining tests with milling process and CBN tools was implemented in order to study the resultant condition of the specimeńs surface. An experimental design was used and the results were statistically treated, enabling the generation of a model that aims to obtain roughness values due to the optimization of three adopted cutting parameters. The roughness values found in the range of Ra 0,16 to 0,4 μm indicate that it is possible to use the milling process with CBN tools for finishing, reducing machining time and the cost of the machined part. The generated residual stresses were compressive and the feed per tooth parameter showed greater influence in this result. The research was limited to test only one type of CBN insert, which was constantly replaced, preventing the influence of tool wear on responses. The geometry of the tool as well as the use of cutting fluid were not considered. Milling process with CBN inserts is confirmed as a possibility for replacing grinding process for finishing machining leading to significant gains in machining time. An optimized model was derived to predict the value of the roughness and three optimizations were made to specify the best cutting parameters to desirable answers such as better roughness, higher compressive residual stresses and low cutting forces, for example.
- Effect of hybrid manufacturing (am-machining) on the residual stress and pitting corrosion resistance of 316L stainless steel(2022-10-05) Ed Claudio Bordinassi; MHURCHADHA, S. U.; SERIACOPI, V.; Sergio Delijaicov; LEBRÃO, S. M. G.; THOMAS, K.; BATALHA, K.; RAGHAVENDRA, R.© 2022, The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering.The use of additive manufacturing (AM) has grown exponentially in recent years and has many advantages, including feasibility, over other conventional processes in many current applications. The use of a second process, for example, machining, improves the surface finish and in this case, the use of two processes is known as hybrid manufacturing. Heat treatments are often performed on parts generated by the AM process, mainly to relieve the residual stresses generated, but for some materials, this can decrease the pitting corrosion resistance of the parts. The objective of this study is to analyze the effect of hybrid manufacturing (AM + machining) on residual stresses and pitting resistance corrosion, which can bring advantages to piece properties without the use of heat treatment. 316L stainless steel parts are generated by direct laser metal sintering (DLMS), with subsequent milling using a complete factorial planning for the design of the experiments. The cutting speed, feed rate, cutting depth, use of the cutting fluid and laser power in the DLMS process are all varied. Residual stresses are measured by X-ray diffraction and the blind hole method, with polarization curves raised by a potentiostat. The results show that it is possible to reduce the residual surface stresses in the parts, even for compressive stresses, and to improve the pitting corrosion resistance, when compared to the part without milling, depending on the cutting parameters used.
- Superficial residual stress, microstructure, and efficiency in similar joints of AA2024-T3 and AA7475-T761 aluminum alloys formed by friction stir welding(2021-09-05) PERANDINI, J. P. B.; Ed Claudio Bordinassi; BATALHA, M. H. F.; CARUNCHIO, A. F.; Sergio Delijaicov© 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.Friction stir welding (FSW) represents a conceptually simple technique that consists of joining either similar or dissimilar solid-state materials through higher plastic deformation rates. FSW is an important technique in the aeronautical and aerospace industries, and its development is vital because of the significant difficulty in joining higher resistance AA 2000 and AA 7000 aluminum alloys with conventional techniques, like fusion welding, due to porosity and mechanical property losses. Thin sheets with a 1.6-mm nominal thickness of AA2024, heat treated to condition T3, and thin sheets with a 1.6-mm nominal thickness of AA7475, heat treated to condition T761, were used to investigate the influence of welding parameters under superficial residual stress and the efficiency of joints by FSW of AA2024-T3 and AA7475-T761 aluminum alloys. A central composite design (CCD) was used as a statistical model in this study (23 factorial points, six stellar points, two central points, and two replicas). Micrographic analysis showed that in the nugget zone of the AA7475-T761 alloy, there was hardness recovery. The fractography images showed that failures occurred mainly due to the joint line remnant defect, evidenced by the presence of cracks. The superficial residual stresses show a maximum value of 81 MPa at the advancing side in run 27 (hot welding) of AA2024-T3, whereas in AA7475-T761, a value of 57 MPa was found in the same run. Finally, tensile strength represents an efficiency of ~92% of the AA2024-T3 base metal value, while for AA7475-T761, this value was ~85%. From a component design perspective, the parameter window of this study is identified as interesting for its evaluation in the possible application in component manufacturing, due to the low values of superficial residual stresses found compared to those in previous work.
- Correction to: Superficial residual stress, microstructure, and efficiency in similar joints of AA2024-T3 and AA7475-T761 aluminum alloys formed by friction stir welding (The International Journal of Advanced Manufacturing Technology, (2021), 116, 1-2, (117-136), 10.1007/s00170-021-07238-5)(2021-09-05) PERANDINI, J. P. B.; Ed Claudio Bordinassi; BATALHA, M. H. F.; CARUNCHIO, A. F.; Sergio Delijaicov© 2021, Springer-Verlag London Ltd., part of Springer Nature.The original article contained a mistake. The Figs. 14 and 15 are the same. The Fig. 14 needs to be changed to: (Figure presented.). The Figs. 16 and 17 are the same. The Fig. 16 needs to be changed to: (Figure presented.). The original article has been corrected.
- Simple machine learning allied with data-driven methods for monitoring tool wear in machining processes(2020-08-01) FARIAS, ADALTO DE; ALMEIDA, SÉRGIO LUIZ RABELO DE; Sergio Delijaicov; SERIACOPI, VANESSA; Ed Claudio BordinassiThe aim of this work was to identify the occurrence of machine tool wear in carbide inserts applied in a machine turning center with two steel materials. Through the data collected with an open-source communication protocol during machining, eighty trials of twenty runs each were performed using central composite design experiments, resulting in a data set of eighty lines for each tested material. The data set consisted of forty lines with the tool wear condition and forty lines without. Machining parameters were set to be in the range of the usual industrial values. The cutting parameters in the machining process were cutting speed, feed rate, cutting depth, and cutting fluid applied in the abundance condition and without cutting fluid (dry machining). The collected data were the spindle motor load, X-axis motor load, and Z-axis motor load in terms of the percentage used. AISI P20 and AISI 1045 steels workpieces were tested with both new and worn inserts, and a flank tool wear of 0.3 mm was artificially induced by machining with the same material before the data collecting experiment. Two approaches were used in order to analyze the data and create the machine learning process (MLP), in a prior analysis. The collected data set was tested without any previous treatment, with an optimal linear associative memory (OLAM) neural network, and the results showed 65% correct answers in predicting tool wear, considering 3/4 of the data set for training and 1/4 for validating. For the second approach, statistical data mining methods (DMM) and data-driven methods (DDM), known as a self-organizing deep learning method, were employed in order to increase the success ratio of the model. Both DMM and DDM applied along with the MLP OLAM neural network showed an increase in hitting the right answers to 93.8%. This model can be useful in machine monitoring using Industry 4.0 concepts, where one of the key challenges in machining components is finding the appropriate moment for a tool change.
- MQL Strategies Applied in Ti-6Al-4V Alloy Milling-Comparative Analysis between Experimental Design and Artificial Neural Networks(2020-08-30) PASCHOALINOTO, NELSON WILSON; BATALHA, GILMAR FERREIRA; Ed Claudio Bordinassi; FERRER, JORGE ANTONIO GILES; LIMA FILHO, ADERVAL FERREIRA DE; RIBEIRO, GLEICY DE L. X.; CARDOSO, CRISTIANOThis paper presents a study of the Ti-6Al-4V alloy milling under different lubrication conditions, using the minimum quantity lubrication approach. The chosen material is widely used in the industry due to its properties, although they present difficulties in terms of their machinability. A minimum quantity lubrication (MQL) prototype valve was built for this purpose, and machining followed a previously defined experimental design with three lubrication strategies. Speed, feed rate, and the depth of cut were considered as independent variables. As design-dependent variables, cutting forces, torque, and roughness were considered. The desirability optimization function was used in order to obtain the best input data indications, in order to minimize cutting and roughness efforts. Supervised artificial neural networks of the multilayer perceptron type were created and tested, and their responses were compared statistically to the results of the factorial design. It was noted that the variables that most influenced the machining-dependent variables were the feed rate and the depth of cut. A lower roughness value was achieved with MQL only with the use of cutting fluid with graphite. Statistical analysis demonstrated that artificial neural network and the experimental design predict similar results.
- The effect of process parameters and cutting tool shape on residual stress of SAE 52100 hard turned steel by high speed machining(2020-04-26) PASCHOALINOTO, N. W.; Ed Claudio Bordinassi; Roberto Bortolussi; Fabrizio Leonardi; Sergio DelijaicovThis study focused on determining the residual stress of SAE 52100 hard-turned steel. The objective was to evaluate and compare the effects of the cutting-edge geometry and cutting parameters (cutting speed, feed rate, and cutting depth) on the residual stresses of three different conventional inserts: S-WNGA08 0408S01020A 7025, T-WNGA08 0408T01020A 7025, and S-WNGA432S0330A 7025. Tests were performed on 60 samples of SAE 52100 hardened steel with an average hardness of 58.5 HRC. The circumferential residual stresses of the samples were measured by X-ray diffraction. A full factorial design of experiments with three factors and two levels each with two central points and a replicate was used for a statistical analysis. The most significant results were as follows: For all inserts, the measured residual stresses were compressive, which extended the tool lifespan. The residual stresses of the Type-S inserts were significantly influenced by the cutting speed and depth, and those of the Type-T insert were significantly influenced by the feed rate and cutting depth. In addition, the residual stresses of the insert 3 were more compressive than those of the other two types of inserts. In other words, residual stresses are more compressive for inserts with larger chamfer angles even as the principal residual stress profiles were all compressive. This work has also shown that it is possible to determine a significant statistical relationship between cutting forces and residual stresses, allowing force measurements to predict the residual stress without any information on process parameters.
Artigo Comparação entre ferramentas para furação de polímeros reforçados por fibra de vidro(2006-04-05) BATALHA, G. F.; STIPKOVIC FILHO, M.; Sergio Delijaicov; Ed Claudio BordinassiPara obter furos de boa qualidade em matrizes termofixas reforçadas com fibra de vidro, deve-se reduzir a força axial e o torque durante a furação. O estudo experimental relatado neste artigo avalia o desempenho e aponta a influência de quatro tipos de ferramentas (brocas helicoidais de aço rápido, serra de copo comum, serra de copo diamantada e trepanadora com insertos de metal duro) sobre estes parâmetros. Com base em um planejamento estatístico dos experimentos e na análise de variância, é possível avaliar esses fatores individualmente, seus efeitos de interação e os respectivos níveis de significância.