Optimization and prediction of thrust force, vibration and delamination in drilling of functionally graded composite using Taguchi, ANOVA and ANN analysis

Köklü, Uğur; Mayda, Murat; Morkavuk, Sezer; Avcı, Ahmet; Demir, Okan

doi:10.1088/2053-1591/ab2617

Cited by 27 publications

(11 citation statements)

References 27 publications

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“…The combined effect of cutting force and cutting temperature causes the surface characteristic to change. Köklü et al 8,9 has developed the research of alloy machining to manufacturability of composite materials functionally graded composite (FGC) materials. The results show that the effect of material direction on delamination can reach 89.5%, but the influence on vibration and thrust are 8.4% and 0.1%, respectively.…”

Section: Introductionmentioning

confidence: 99%

Effects of cutter path orientations on milling force, temperature, and surface integrity when ball end milling of TC17 alloy

Shen

Zhang

Tan

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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To explore the effects of cutter path orientations on milling force, temperature, and surface integrity, end ball milling experiments of TC17 titanium alloy were accomplished derived from different cutter path orientations. The experiment results of milling force and temperature were obtained. Combining with the thermo-mechanical coupling, this paper analyzes the impact of the cutter path orientations on the surface roughness, surface topography, in-depth residual stress, microhardness distributions, and microstructure. The results indicate that the maximum milling force is 224.24 N and the temperature is 672°C under vertical downward milling path, while horizontal downward orientation provides the lowest cutting force of 81.12 N and temperature of 493°C. The surface topography of the four cutter path orientations is basin-like shape, and the minimum surface roughness of 1.128 µm is achieved under vertical upward mode. Moreover, the maximum compressive residual stress of −491.8 MPa and the maximum residual stress layer depth of 45 µm are acquired under vertical downward milling. The maximum microhardness can arrive at 390 HV0.025 under the vertical path. Additionally, the transformation of the material microstructure remains elongated, bent, and fractured. The maximum plastic deformation layer depth is 44 µm under vertical downward milling path.

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Section: Introductionmentioning

confidence: 99%

Effects of cutter path orientations on milling force, temperature, and surface integrity when ball end milling of TC17 alloy

Shen

Zhang

Tan

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…To identify the significant effects of the input parameters and their relationship on the output parameters, one of the statistical techniques [ 23 ]—the one-way Analysis of Variance (ANOVA) presented by Tank et al [ 24 ], Köklü et al [ 25 ], Kumar et al [ 26 ], as well as Palaniappan et al [ 27 ]—was used. Statistical calculations were carried out at a confidence level of α = 0.05.…”

Section: Resultsmentioning

confidence: 99%

Dimensional Analysis of Workpieces Machined Using Prototype Machine Tool Integrating 3D Scanning, Milling and Shaped Grinding

et al. 2020

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In the literature, there are a small number of publications regarding the construction and application of machine tools that integrate several machining operations. Additionally, solutions that allow for such integration for complex operations, such as the machining of shape surfaces with complex contours, are relatively rare. The authors of this article carried out dimensional analysis of workpieces machined using a prototype Computerized Numerical Control (CNC) machine tool that integrates the possibilities of 3D scanning, milling operations in three axes, and grinding operations using abrasive discs. The general description of this machine tool with developed methodology and the most interesting results obtained during the experimental studies are given. For a comparative analysis of the influence of the machining method on the geometric accuracy of the test pieces, an Analysis of Variance (ANOVA) was carried out. The obtained results show that for four considered features (deviations of flatness, vertical parallelism, opening dimensions, and opening cylindricality), no statistically significant differences were detected. For the evaluation criteria, the probability level p exceeded the assumed confidence level α = 0.05 and ranged from p = 0.737167 to p = 0.076764. However, such differences were found for two others—a dimensional deviation between flat surfaces (p = 0.010467) and horizontal parallelism deviation (p = 0.0)—as well as for the quality of the machined surface defined by four surface texture parameters: Ra (p = 0.831797), Rt (p = 0.759636), Rq (p = 0.867222), and Rz (p = 0.651896). The information obtained by the ANOVA will be useful for the elimination the weaknesses of the prototype machine tool, further analysis of technological strategies, and to find possible benefits of integrating machining operations.

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“…This is done by controlling the cutting parameters to keep the drilling process at an optimal level of quality assurance and optimal tool life exploitation. The author in [15] proposes the use ANNs and other machine learning methods to determine a relation between the cutting process parameters and conditions such as feed rate, thrust force, vibration, directions of the plys, and the appearance of delamination in the holes inner surfaces.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving the quality assessment of drilled holes in aircraft structures

Kawano

Toledo²,

Barbosa³

et al. 2023

Preprint

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This paper presents a case study carried out in an assembly cell where automated drilling of an aeronautical structure is performed. The study shows how techniques approached by the 4.0 industry have the potential to contribute to manufacturing, breaking the limits imposed by the previous state of the art systems. This paper proposes a method capable of calculating an indicator for the final quality of the drilled holes, by using a committee of neural networks, which analyses data obtained by monitoring the electric current consumed by the drilling system drive. The method has the potential to enhance the efficiency of the drilling process, avoiding measurement steps and physical inspections that increases the cell cycle time.The proposal contributes to the literature by presenting an unprecedented application and to the praxis by solving a relevant problem of the aerospace industry.

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Optimization and prediction of thrust force, vibration and delamination in drilling of functionally graded composite using Taguchi, ANOVA and ANN analysis

Cited by 27 publications

References 27 publications

Effects of cutter path orientations on milling force, temperature, and surface integrity when ball end milling of TC17 alloy

Effects of cutter path orientations on milling force, temperature, and surface integrity when ball end milling of TC17 alloy

Dimensional Analysis of Workpieces Machined Using Prototype Machine Tool Integrating 3D Scanning, Milling and Shaped Grinding

Improving the quality assessment of drilled holes in aircraft structures

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