Optimization of hole quality produced by novel drill geometries using the Taguchi S/N approach

Meral, Güven; Sarıkaya, Murat; Mia, Mozammel; Dilipak, Hakan; Şeker, Ulvi

doi:10.1007/s00170-018-2956-z

Cited by 9 publications

(2 citation statements)

References 29 publications

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“…The thrust force used in drilling processes is one of the main components of force generation affected by the drilling parameters, workpiece mechanical properties, number of drill holes, tool wear, drilling operation and machine tool structure [27]. Previously, the thrust force generated during the one-shot single drilling process has been widely studied [3,[28][29][30][31][32][33][34][35][36]. Therefore, this study represents the thrust force generated during multi-hole simultaneous drilling operations.…”

Section: Analysis Of Thrust Forcementioning

confidence: 99%

Performance Analysis of Multi-Spindle Drilling of Al2024 with TiN and TiCN Coated Drills Using Experimental and Artificial Neural Networks Technique

et al. 2020

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Multi-spindle drilling simultaneously produces multiple holes to save time and increase productivity. The assessment of hole quality is important in any drilling process and is influenced by characteristics of the cutting tool, drilling parameters and machine capacity. This study investigates the drilling performance of uncoated carbide, and coated carbide (TiN and TiCN) drills when machining Al2024 aluminium alloy. Thrust force and characteristics of hole quality, such as the presence of burrs and surface roughness, were evaluated. The results show that the uncoated carbide drills performed better than the TiN and TiCN coated tools at low spindle speeds, while TiCN coated drills produced better hole quality at higher spindle speeds. The TiN coated drills gave the highest thrust force and poorest hole quality when compared with the uncoated carbide and TiCN coated carbide drills. Additionally, a multi-layer perceptron neural network model was developed, which could be useful for industries and manufacturing engineers for predicting the surface roughness in multi-hole simultaneous drilling processes.

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Section: Analysis Of Thrust Forcementioning

confidence: 99%

Performance Analysis of Multi-Spindle Drilling of Al2024 with TiN and TiCN Coated Drills Using Experimental and Artificial Neural Networks Technique

et al. 2020

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“…The gash should provide the smooth connection from the main cutting edge to the chisel edge of the drill [19]. In addition, there are designs of drills with a flat gash of the rake surface [4,6,20,21]. Disadvantages in modern twist drill designs include: small rake angle values along the cutting edge, even negative when approaching the center; rake angles at the periphery are too large.…”

Section: Introductionmentioning

confidence: 99%

Influence of the radius of the generatrix of flank surface on the geometric parameters of the cutting wedge of the twist drill

Pivkin,

Grechishnikov,

Ershov

et al. 2023

E3S Web of Conf.

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Drills with various flank surface shapes are widely used to machine holes. Drill teeth have flank surfaces of various shapes, flat, conical and helical. In this work, we have investigated the influence of radius of the generatriх in the form of a circular arc on the geometric parameters of the cutting wedge. It has been found that the range of changes in the clearance and rake angles along the cutting edge decreases with the decreasing radius of generatrix forming rake. It was found that a tool with a minimum permissible radius of curvature has the best distribution of rake and clearance angles of the blade along the cutting edge . The improvement reaches up to 40% compared conical flank surface. It was also found that in the case, when the generatrix radius decreases, the cutting edge increases by 18% compared to conical flank surface, which reduces the stress along the entire cutting wedge.

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ANN-FPA Based Modelling and Optimization of Drilling Burrs Using RSM and GA

Mondal¹,

Mandal²,

Mandal³

et al. 2022

Lecture Notes in Networks and Systems

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Optimization of hole quality produced by novel drill geometries using the Taguchi S/N approach

Cited by 9 publications

References 29 publications

Performance Analysis of Multi-Spindle Drilling of Al2024 with TiN and TiCN Coated Drills Using Experimental and Artificial Neural Networks Technique

Performance Analysis of Multi-Spindle Drilling of Al2024 with TiN and TiCN Coated Drills Using Experimental and Artificial Neural Networks Technique

Influence of the radius of the generatrix of flank surface on the geometric parameters of the cutting wedge of the twist drill

ANN-FPA Based Modelling and Optimization of Drilling Burrs Using RSM and GA

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