Optimization of cutting conditions in slotting of multidirectional CFRP laminate

Gara, Souhir; Tsoumarev, Oleg

doi:10.1007/s00170-017-1451-2

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…Particle swarm optimization (PSO) is one of the most popular population-based stochastic optimization [28]. PSO technique has received wide attention in recent years since it can converge to the optimization value quickly and has excellent robustness [29,30].…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Modified Particle Swarm Optimization-Artificial Neural Network and Gene Expression Programing for Predicting High Temperature Oxidation Behavior of Ni–Cr–W-Mo Alloys

Hasibi

Mahmoudian

Khayati

2020

IJE

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This paper is an attempt to model the oxidation behavior of Ni-base alloys by considering the alloying elements, i.e., Cr, W, Mo, as variables. Modified particle swarm optimization-artificial neural network (MPSO-ANN) and gene expression programming (GEP) techniques were employed for modeling. Data set for construction of (MPSO-ANN) and GEP models selected from 66 cyclic oxidation performed in the temperature range of 400-1150 ᵒC for 27 different Ni-based alloy samples at various amounts of Cr, W, and Mo. The weight percent of alloying elements selected as input variables and the changes of weight during the oxidation cycle considered as output. To analyze the performance of proposed models, various statistical indices, viz. root mean squared error (RMSE) and the correlation coefficient between two data sets (R 2) were utilized. The collected data of GEP randomly divided into 21 training sets and 6 testing sets. The results confirmed that the possibility of oxidation behavior modeling using GEP by R 2 = 0.981, RMSE =0.0822. By consideration of oxidation resistance as criteria, Cr, Mo, and W enhanced the oxidation resistance of Ni-based alloys. The results showed that in the presence of Cr as alloying element, especially at Cr contents higher than 22 wt.%, the effect of W and Mo were negligible. However, the same trend was reversed at the sample with Cr content lower than 20 wt.%. In these cases, the effect of W and Mo on oxidation resistance were significantly enhanced.

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Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Modified Particle Swarm Optimization-Artificial Neural Network and Gene Expression Programing for Predicting High Temperature Oxidation Behavior of Ni–Cr–W-Mo Alloys

Hasibi

Mahmoudian

Khayati

2020

IJE

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“…The optimization value of the entry and exit delamination, the thrust force, and the torque of CFRP composite drilling parameters was achieved by FIS (fuzzy interference system) combined with the Taguchi method [20], and BPNN (back propagation neural network) and PSO (particle swarm optimization) were used to attain the best parameter level according to the response graphs [21]. PSO was combined with graphical method to determine the optimal feed rate and cutting speed in the slotting milling of CFRP [22]. Special geometry drilling tools were used to analyze the cutting process.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of carbon fiber–reinforced polymer drilling process based on grey fuzzy reasoning grade analysis

Tran

Huang

2021

Int J Adv Manuf Technol

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With outstanding mechanical advantages such as high strength, light weight, high rigidity, low thermal expansion, good resistance corrosion, and high vibration resistance, carbon fiber-reinforced polymer (CFRP) is becoming increasingly popular in the automotive, aerospace, and medical spheres. For the CFRP machining, the biggest drawback is the effect of moisture on the mechanical properties caused by the cooling liquid and tool geometry. The appreciable body of study on the influence of wetness on the mechanical quality of carbon fiber-reinforced plastic has shown that there is no suitable use for lubrication fluids in the composite industry. However, there is a significant impact on the CFRP machining capabilities caused by the geometry of the cutting tool and cryogenic liquid cooling. This paper investigated the optimal choice of the parametric combinations in the CFRP drilling process. The optimization method was proposed using the Fuzzy interference system based on grey relation analysis. The experiment data was designed according to the Taguchi method. The twist angle of the drill, the coolant gas, and the feed rate were considered as the parameter inputs while observing several multi-responses such as thrust force and temperature generated during drilling process. The optimal result, as well as the case with highest grey fuzzy reasoning grade (GFRG), indicated that the low feed rate combined with the high twist angle drill in the hybrid cryogenic CO 2 -N 2 gas condition tended to minimize the value of the response output. The verification experiment results showed a good correlation with the optimal analytical result. The analysis of variance results also showed that the reliability of the data was satisfactory.

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“…Feed per tooth, F z was found to be the highest statistical and physical influence on the surface roughness for knurled or burr tool. Fine toothing of burr tool exhibited the most suitable tool for the slotting of CFRP material due to the minimum damages generated from the machined specimens in comparison to the smooth and coarse toothing [19,20].…”

Section: Introductionmentioning

confidence: 99%

Effect of Machining Parameters on Surface Roughness in Edge Trimming of Carbon Fiber Reinforced Plastics (CFRP)

2020

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The main aim of this research was to investigate the effect of machining parameters towards surface quality during edge trimming process on a specific CFRP material. There were two variation of machining parameters focused in this work namely spindle speed (N) and feed rate (V f). The CFRP panel is measured 3.25 mm in thickness and the type of fabric was unidirectional (UD). It has 28 number of plies in total and were arranged multi-directional. Router or burr tool geometry made of uncoated tungsten carbide with a diameter of 6.35 mm was used to perform the edge trimming process. Surface roughness measurement was taken using Mitutoyo Surftest SJ-410. Furthermore, optical microscope Nikon MM-800 is utilized to further observe the trimmed surfaces. The result reveals that the smallest value of the surface roughness (1.31 µm) is obtained by Run 8 (R8) which the spindle speed, N applied was 2506 rpm and feed rate, V f at 376 mm/min. Meanwhile, the highest surface roughness value (12.62 µm) exhibited by the R9 which had the highest setting of spindle speed, N 7518 rpm and the highest feed rate, V f 1128 mm/min. The result is supported by the observation of trimmed surface through optical microscopy which clearly exhibits uncut fibers and matrix degradation condition. Details results elaborated and discussed further in this paper.

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Optimization of cutting conditions in slotting of multidirectional CFRP laminate

Cited by 9 publications

References 21 publications

Modified Particle Swarm Optimization-Artificial Neural Network and Gene Expression Programing for Predicting High Temperature Oxidation Behavior of Ni–Cr–W-Mo Alloys

Modified Particle Swarm Optimization-Artificial Neural Network and Gene Expression Programing for Predicting High Temperature Oxidation Behavior of Ni–Cr–W-Mo Alloys

Multi-objective optimization of carbon fiber–reinforced polymer drilling process based on grey fuzzy reasoning grade analysis

Effect of Machining Parameters on Surface Roughness in Edge Trimming of Carbon Fiber Reinforced Plastics (CFRP)

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