Thrust and torque force analysis in the drilling of aramid fibre-reinforced composite laminates using RSM and MLPNN-GA

Anarghya, A; Harshith, D.N.; Rao, Neeraj; Nayak, Nagaraj S.; Gurumurthy, B M; Abhishek, Virat; Patil, Ishwar Gouda S.

doi:10.1016/j.heliyon.2018.e00703

Cited by 40 publications

(16 citation statements)

References 35 publications

(41 reference statements)

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“…Moreover, as the point angle of a drill bit increases, the contact area of the hole increases, resulting in an increase in the thrust force. The feed rate is directly related to the contact area; therefore, as the feed rate increases, the buildup on the edge of the tool, which enhances heat generation and the thrust force, is promoted irrespective of the nanocontent percentage, causing delamination of the workpiece [37,38]. According to many researchers, as the feed rate increases, the thrust force increases in drilling processes, which coincides with the results obtained in the present investigation, as shown in Fig.…”

Section: Effect Of Thrust Force On Drilling Parameterssupporting

confidence: 91%

Modeling and evolutionary computation on drilling of carbon fiber-reinforced polymer nanocomposite: an integrated approach using RSM based PSO

Vijayan

Rajmohan

2019

J Braz. Soc. Mech. Sci. Eng.

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Among the various classifications of fiber-reinforced polymer composites, carbon fiber-reinforced plastic (CFRP) composite materials have great potential in aerospace, automobile and marine industries. Drilling is a common machining process of CFRP composites. Surface delamination, tearing, abrasion, denting, cutting of fibers, formation of voids, fiber bending and pullout, etc. are significant problems that occur in the drilling of CFRP composites, among which surface delamination is identified as a critical issue. By optimizing the drilling parameters, the effect of delamination can be minimized, resulting in good quality holes. The drilling process involves several critical process parameters. Therefore, achieving accurate holes during the process is extremely difficult. Three significant drilling process parameters were considered in the present investigation aimed at achieving an optimum drilling response: the thrust force and entry and exit delamination factors. An integrated response surface methodology-based particle swarm algorithm was used to obtain optimal drilling parameters. The obtained optimal settings for CFRP drilling are a drilling speed of 1100 rpm, a feed rate of 5 mm/rev, 5% CNTs and a 110° point angle. The high feed rate increases the thrust force and entry and exit delamination factors in the drilling of fabricated hybrid nano-CNT/CFRP composites.

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Section: Effect Of Thrust Force On Drilling Parameterssupporting

confidence: 91%

Modeling and evolutionary computation on drilling of carbon fiber-reinforced polymer nanocomposite: an integrated approach using RSM based PSO

Vijayan

Rajmohan

2019

J Braz. Soc. Mech. Sci. Eng.

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“…The plot of prediction vs. actual and 3D plots of response surface obtained during analysis is revealed in Figure 13, which indicates that there is a higher difference amid predicted and experimental values (residuals) due to the low value of predicted R 2 (42.32%). From the surface plots, for cryogenic cooling, a direct association occurs among drill speed and torque, as drill speed increases torque increases and also with conditions of feed rate increase, a higher torque is observed in a linear manner [37]. A similar trend is observed with wet machining also.…”

Section: Figure 12 Interaction Effect and Normal Probability Plot For Torquesupporting

confidence: 56%

Temperature evaluation and performance comparison of various cooling techniques in drilling of grade 5 titanium alloy

et al. 2021

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Heat dissipation is a foremost issue in machining of materials and to overcome this different cooling techniques are adopted to improve the surface integrity and diminish microstructural damage and to effectively flush chips produced. In this research, machinability of titanium grade 5 (Ti-6Al-4V) was carried out through drilling process considering three different cooling procedures like cryogenic cooling (CO2), palm oil based minimum quantity lubrication (MQL) and wet/flood cooling with general cutting fluid (emulsifiers). Experiments were prearranged in par with Taguchi?s technique and a suitable L18 orthogonal array was formulated and the outputs obtained viz., interface temperature and cutting forces (torque/thrust force) were analyzed by adopting response surface methodology (RSM). For interface temperature, type of coolant is the most influencing factor, whereas for cutting forces, the impact of feed rate, drill speed and type of coolant are significant. Response surfaces were fitted for the outputs and subsequently a higher polynominal regression equation was developed for prediction. The optimum condition obtained for constraint multiobjective optimization using desirability approach was: drill speed of 42.49 m/min, feed rate of 0.05 mm/rev and cooling type as cryogenic cooling. The main objecive is to minimize the interface temperature and torque subjected to the constraint thrust force (?1500 N). Confirmation experiment performed with optimum condition displays a significant enhancement in output results.

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“…While common supervised artificial neural networks and their adaptations include single-layer perceptron (SLP) [ 10 , 31 ], multilayer perceptron (MLP) [ 42 , 43 ], and linear classifiers [ 44 , 45 ]. Also, popular supervised ANNs include support vector machines (SVMs) [ 46 , 47 ], k-nearest neighbours (kNNs) [48] .…”

Section: Main Textmentioning

confidence: 99%

State-of-the-art in artificial neural network applications: A survey

Abiodun

Omolara

Dada

et al. 2018

Heliyon

2,140

785

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This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and area of focus for researchers. Additionally, the study presents ANN application challenges, contributions, compare performances and critiques methods. The study covers many applications of ANN techniques in various disciplines which include computing, science, engineering, medicine, environmental, agriculture, mining, technology, climate, business, arts, and nanotechnology, etc. The study assesses ANN contributions, compare performances and critiques methods. The study found that neural-network models such as feedforward and feedback propagation artificial neural networks are performing better in its application to human problems. Therefore, we proposed feedforward and feedback propagation ANN models for research focus based on data analysis factors like accuracy, processing speed, latency, fault tolerance, volume, scalability, convergence, and performance. Moreover, we recommend that instead of applying a single method, future research can focus on combining ANN models into one network-wide application.

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Thrust and torque force analysis in the drilling of aramid fibre-reinforced composite laminates using RSM and MLPNN-GA

Cited by 40 publications

References 35 publications

Modeling and evolutionary computation on drilling of carbon fiber-reinforced polymer nanocomposite: an integrated approach using RSM based PSO

Modeling and evolutionary computation on drilling of carbon fiber-reinforced polymer nanocomposite: an integrated approach using RSM based PSO

Temperature evaluation and performance comparison of various cooling techniques in drilling of grade 5 titanium alloy

State-of-the-art in artificial neural network applications: A survey

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