Figure - available from: Science and Engineering of Composite Materials
This content is subject to copyright. Terms and conditions apply.
Source publication
Milling glass fiber reinforced plastic (GFRP) composite materials are problematic, owing to, e. g., nonhomogeneous and anisotropic properties and effects of plastic deformation. To reduce these problems, the effects of cutting speed, feed rate, and the number of flutes on surface roughness and of thrust forces occurring during the milling of GFRP c...
Similar publications
The reinforced mechanism is proposed to describe the energy dissipation of chopped fiber peeling and pull-out as the crack grows. Then, a finite element model (FEM) is established to simulate the process of the interfacial crack growth for a double cantilever beam. The energy release rate is calculated by the virtual crack closure technique (VCCT)....
![Figure 2. Concrete slab and simulated delaminations design [20].](profile/Thomas_Oommen/publication/316173366/figure/fig1/AS:562222713630720@1511055748431/Concrete-slab-and-simulated-delaminations-design-20_Q320.jpg)
Infrared and visible cameras were mounted on an unmanned aerial vehicle (UAV) to image bridge deck surfaces and map likely concrete delaminations. The infrared sensor was first tested on laboratory validation experiments, to assess how well it could detect and map delaminations under controlled conditions. Field tests on two bridge deck surfaces fu...
A cohesive model of the new interface of the CuZnAl SMA/GFRP hybrid composite is proposed and the interfacial delamination under Mode II loading conditions, between plain CuZnAl SMA sheet insert and GFRP matrix, as well as between CuZnAl SMA sheet insert having elliptical hole pattern and GFRP matrix, are studied in detail.
Direct preforming processes have potential for fiber-reinforced semi-finished products, creating 3D structures with strong delamination resistance using double-flat-steel-healds. However, the shedding method limits pattern variety, necessitating alternative options for interlacing diversity. One approach is using weft yarn instead of warp yarn for...
A co-investigation of mantle melting conditions and seismic structure revealed an evolutionary record of mantle dynamics accompanying the transition from subduction to collision along the Africa-Eurasia margin and the >1 km uplift of the Anatolian Plateau. New 40Ar/39Ar dates of volcanic rocks from the Eastern Taurides (southeast Turkey) considerab...
Citations
... For instance, Danyan et al. [47] showed that end milling operations in Ti-6Al-4V with three flute tools performed slightly be er in terms of the surface roughness than four flute tools. Similarly, Çelik et al. [48] showed that when end milling of glass fiber reinforced plastic composites with cemented carbide tools, the use of two flutes resulted in a reduction of 50% in surface roughness with respect to the same tool with four flutes. o Insert shape: The shape of the insert may be important since it is related to the vibration tendency during machining. ...
Understanding surface roughness generation in machining is critical to estimate the final quality of the part, optimize cu ing conditions, reduce costs and improve manufacturing sustainability in industry. This work presents a review of the factors that affect surface roughness generation in machining (turning/milling) processes. Up to twenty-five different factors were identified, which were classified as setup factors (cu ing tool, machine tool/fixturing and workpiece factors), operational factors (cu ing and process parameters) and processing factors, which are related to the resulting cu ing processes, such as built-up edge, cha er or tool wear. The importance of understanding these factors to improve machining sustainability is highlighted through three case studies, ranging from a simple change in the cu ing insert to a more complex case where a controlled surface roughness leads to the elimination of a grinding stage. A case study illustrating the potential benefit of MQL in the sustainability of the machining process is also reported from the mold manufacturing industry. In all of the cases, the improvement in sustainability in terms of the reduction in kg of CO2 equivalent is notable, especially when grinding operations are reduced or eliminated from the manufacturing process. This paper can be of interest to practitioners in finishing operations at milling and turning operations that want to increase machining sustainability through a deep understanding of surface roughness generation.
... This can also help prevent delamination for push-out and fiber pull-out and result in a smoother surface finish. Based on a study carried out by [27] saying that as the cutting speed was increased, more heat occurred. This caused softening of the work-piece material. ...
... The condition of brand and spur cutting tools in cutting process of FRP composite[11] Based on the value of the surface roughness (Ra) of Brad / spur drill obtained excellent performance results on the Glass Fiber Reinforced Materials (GFRP) sample,19 ...
... Many researchers have studied the effects of machining conditions on milling. 3,7,8,[12][13][14][15][16] The literature uses methods such as Taguchi, response surface, artificial neural network, adaptive neuro fuzzy inference system, etc., for optimization studies. 17 Ali, Iqbal, and Liang, 18 investigated the influence of drilling and milling machining parameters on hole making process of woven laminated glass fiber-reinforced polymer (GFRP) material. ...
Composite materials are often preferred in many engineering applications because of their lightness and high-strength properties. However, in addition to the advantages of composite materials, processing problems exist. The processing of fiber-reinforced composite materials is more complex than other metal materials. The forces that arise during milling cause undesir�able results, such as tool wear and energy loss. In this study, the cutting parameter optimi�zation was made by measuring the force during carbon fiber and glass fiber-reinforced epoxy
matrix composites milling. Cutting velocity (90, 120, and 150 m/min) and feed per tooth (0.1, 0.15, and 0.2 mm/tooth) were selected as cutting parameters. Experiments were planned according to the Taguchi method with two parameters and three levels. Optimization of the parameters was evaluated using the signal/noise ratio approach. The effectiveness of parameters on results was determined by analysis of variance (ANOVA). Optimum levels were
found as 120 m/min for cutting velocity and 0.1 mm/tooth for feed per tooth both glass fiber�reinforced polymer (GFRP) and carbon fiber-reinforced polymer (CFRP) composites. According to the ANOVA results, the contribution rates of the force parameters were 81.05 % for cutting velocity and 15.03 % for feed per tooth in GFRP composites. The contribution rates of the force parameters were 43.69 % for cutting velocity and 46.18 % for feed per tooth in CFRP composites.
The surfaces of the milled samples were examined with an optical microscope to investigate the damage. It was observed that the surfaces of CFRP samples had a better surface quality than GFRP samples.
... Rodríguez et al. [24] predicted the roughness for face milling 11SMnPb37 steel in terms of tool wear and type, using the decision tree method. A fuzzy logic model was employed by Ç elik et al. [25] to estimate the surface roughness and thrust force based on different cutting parameters during end milling of GFRPC materials; they found low feed rate, high cutting speed, and a large number of flutes resulted in low surface roughness. Lin et al. [26] studied the relationship between feed force and tool wear when machining A359 Al/SiC composites and found that using the ANN method to define this relationship was more accurate compared with regression analysis. ...
... From the aforementioned Refs. [18][19][20][21][22][23][24][25][26][27][28][29], it could be seen that artificial intelligence methods were valid and reliable means of investigating the quantitative relationship between surface quality and cutting parameters (or other parameters). However, research regarding roughness prediction and control for machining Al/SiC composites is too limited; this is the primary motivation for our work. ...
In recent years, there has been a significant increase in the utilization of Al/SiC particulate composite materials in engineering fields, and the demand for accurate machining of such composite materials has grown accordingly. In this paper, a feed-forward multi-layered artificial neural network (ANN) roughness prediction model, using the Levenberg-Marquardt backpropagation training algorithm, is proposed to investigate the mathematical relationship between cutting parameters and average surface roughness during milling Al/SiC particulate composite materials. Milling experiments were conducted on a computer numerical control (CNC) milling machine with polycrystalline diamond (PCD) tools to acquire data for training the ANN roughness prediction model. Four cutting parameters were considered in these experiments: cutting speed, depth of cut, feed rate, and volume fraction of SiC. These parameters were also used as inputs for the ANN roughness prediction model. The output of the model was the average surface roughness of the machined workpiece. A successfully trained ANN roughness prediction model could predict the corresponding average surface roughness based on given cutting parameters, with a 2.08% mean relative error. Moreover, a roughness control model that could accurately determine the corresponding cutting parameters for a specific desired roughness with a 2.91% mean relative error was developed based on the ANN roughness prediction model. Finally, a more reliable and readable analysis of the influence of each parameter on roughness or the interaction between different parameters was conducted with the help of the ANN prediction model.
... The most frequently used technique in manufacturing is milling that is the machining process of materials. 1 Micro-milling is a significant operation of mechanical micro-machining, with realistic application in mold and die, automotive, aerospace, military, biomedical, and micro-electronics packaging industries. Commercially available micro-milling tools have the tool diameter ranging ½ 25 1000 mm. 2 In addition, regenerative chatter is a main topic of immense engineering significance due to its incidence in macro/micro-machining results in poor surface finish and limits the efficiency and productivity. ...
Determination of optimal parameters of cutting tool is one of the most significant factors in any operation planning of metal elements, especially in micro-milling process. This article presents an optimization procedure, based on genetic algorithms, to optimize some parameters related to micro-milling tool including number of teeth, shank diameter, fluted section diameter, shank length, taper length, and length of fluted section. The aim of this optimization is maximizing the minimum value of cutting depth on the border of stability lobe diagrams, which is called allowable cutting depth, for chatter-free machining. Cutting tool is modeled as a three-dimensional spinning cantilever Timoshenko beam based on strain gradient elasticity theory. Structural nonlinearity, gyroscopic moment, rotary inertia, and velocity-dependent process damping are also considered in the cutting tool model. The values of natural frequency, damping ratio, and material length scale of the micro-milling tool are calculated using a system identification based on genetic algorithm to match the analytical response with recorded experimental vibration signal. Using beam model, the allowable cutting depth is increased in the optimization process for a specific range of spindle speed to avoid the chatter phenomenon. Analytical study of micro-milling process stability is carried out to determine the cost function of the genetic algorithm. A plot of the greatest fitness in each generation is sketched. In addition, stability lobe diagrams before and after optimization process are presented to show the efficiency of the optimized micro-milling tool. In the presented examples, the results of genetic algorithm may lead to design or find a micro-milling tool that its acceptable cutting depth increases up to 1.9313 times.
... It was observed that wear resistance of composites increased with GF content. As the mechanical and tribological behaviors of GFRP composites are improved, their usage areas are increasing day by day and they are subjected to different processing methods [6][7][8][9]. ...
Glass fiber-reinforced plastic (GFRP) composites take place in engineering materials owing to their low-weight and high-mechanical properties. In some cases, they need to be shaped by machining before using in industrial applications. However, when these composites are machined, many problems such as bad surface quality, rapid tool wear are encountered. Therefore, optimization of cutting parameters is essential to eliminate or minimize these problems. In this study, GFRP composites were produced by combining polyester matrix material with glass fibers (GF) having 6 mm, 6–12 mm, 12 mm fiber length, and 20%, 25%, 30% fiber ratio by weight. The tensile strengths of these composites were investigated. Turning tests were also performed with cutting speeds of 40, 80, and 120 m/min, feed rates of 0.1, 0.2 and 0.3 mm/rev, and depth of cut of 1, 2, and 3 mm, according to Taguchi L27 standard orthogonal array method. The effect of fiber length and ratio, and cutting parameters on cutting forces and surface roughness were analyzed. As a result of the experiments, it was observed that the reinforced polymer matrix with GF provide to increase the tensile strength. The highest tensile strength was obtained as 55.95 MPa from the composite having a fiber length of 12 mm and a fiber ratio of 25%. Besides, the feed rate was determined as the most effective parameter among the all parameters on both cutting force and surface roughness. Therefore, the feed rate should be chosen low for lower cutting force and surface roughness values.
... Corresponding to this, Fuzzy Logic Modeling (FLM) has been used to predict the surface roughness, to control the cutting force in various machining processes and estimation, and to prediction in switched reluctance motor 277 drives by Celik et.al. [3], Cheok and N. Ertugrul [4], respectively. On the other hand, Vijayaraghavan and Jayalakshmi [5] showed that FLM are used in chemical process systems without any mathematical ambiguity in process industries. ...
Bu çalışmada, bulanık
mantık modeli kullanılarak ağırlıkça % 60 Ni ve %80 Ni içeren borlanmış Fe-Ni
ikili alaşımların radyasyon koruma özellikleri borlama parametreleri olan
sıcaklık ve zamanın fonksiyonu olarak incelenmiştir. Bunun için, borlanmış
numunelerin doğrusal zayıflama katsayıları hesaplanmış ve bu değerlere bulanık
mantık modeli uygulanmıştır. Elde edilen sonuçlar, bulanık mantık modelinin
test edilmemiş şartlar içinde bile borlanmış Fe-Ni alaşımlarının radyasyon
koruma özelliklerini tahmin etmek için kullanılabileceğini göstermektedir.
... Corresponding to this, Fuzzy Logic Modeling (FLM) has been used to predict the surface roughness, to control the cutting force in various machining processes and estimation, and to prediction in switched reluctance motor 277 drives by Celik et.al. [3], Cheok and N. Ertugrul [4], respectively. On the other hand, Vijayaraghavan and Jayalakshmi [5] showed that FLM are used in chemical process systems without any mathematical ambiguity in process industries. ...
... Carbon fiber reinforced plastic (CFRP) is the most known composite material [4]. CFRP requires machining for assembly integration [5]. The drilling is the most used machining method for CFRP. ...
The application areas of carbon fiber reinforced plastics (CFRP) have been increasing day
by day. The machining of CFRP with incorrect machining parameters leads in huge loss cost and time.
Therefore, it is very important that the composite materials are machined with correct machining
parameters. The aim of this paper is to examine the influence of drilling parameters on tensile load
after drilling of CFRP. The drilling operations were carried out on Computer Numerical Control
(CNC) by Tungsten Carbide (WC), High Speed Steel (HSS) and Brad Spur type drill bits with spindle
speeds of 1000, 3000 and 5000 rpm and feed rates of 0.05, 0.10 and 0.15 mm/rev. The results indicate
that the surface roughness, delamination and thrust force, were affected by drilling parameters
therefore tensile load was also affected by the same parameters. It was observed that increase in
surface roughness, delamination and thrust force all lead to the decrease of tensile load of CFRP.
If the correct drilling parameters are selected; the decrease in tensile load of CFRP can be saved up to
25%. Furthermore, an artificial neural network (ANN) model has been used to predi
