A study on cutting and tribology performances of TiN and TiAlN coated tools

Li, Huaying; He, Hui-Bo; Han, Wei; Yang, Jun; Gu, Tingyue; Li, Yuanming; Lyu, Sung-Ki

doi:10.1007/s12541-015-0103-4

Cited by 38 publications

(12 citation statements)

References 13 publications

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“…Ebrahimi and Moshksar [ 51 , 52 ] investigated the effect of cutting speed, feed rate and cutting force on flank wear during boring, and the influence of cutting speed, feed rate and hardness on tool life in the turning operation. Li et al [ 53 ] performed a study based on different coating conditions, and found that TiN-coated tools demonstrated abrasive and adhesive wear, while TiAlN-coated tools showed adhesive, diffusive and oxidation wear. Zhang et al [ 54 ] examined an experimental study for sintered tools to obtain wear mechanisms and optimum cutting conditions during turning.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Kuntoğlu

Aslan

Sağlam

et al. 2020

Sensors

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Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L9 orthogonal design principle, the basic machining parameters cutting speed (vc), feed rate (f) and depth of cut (ap) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, VB, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at vc = 150 m/min, f = 0.09 mm/rev, ap = 1 mm) to obtain the best results for VB, Ra and the sensorial data, with a high success rate (82.5%).

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Section: Introductionmentioning

confidence: 99%

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Kuntoğlu

Aslan

Sağlam

et al. 2020

Sensors

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“…Li ve ark. [4] kaplamalı takımlarda AISI 5140 işlerken meydana gelen aşınma mekanizmalarını incelemiştir. Buna göre TiN kaplamalı takımlarda abreziv ve adeziv, TiAlN kaplamalı takımlarda adeziv, difüzyon ve oksidasyon aşınmaları oluştuğu görülmüştür.…”

Section: Gi̇ri̇ş (Introduction)unclassified

Investigation of the Effects of Approaching Angle and Cutting Parameters on Machinability of AISI 5140 Steel during Turning

2022

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Doğası gereği karmaşık bir yapıya sahip olan tornalama ile şekillendirilecek bir malzemenin en iyi işleme şartlarının belirlenmesi maliyet, zaman ve verimlilik açısından önem kazanmaktadır. Bu çalışmada orta karbonlu alaşım çeliği AISI 5140 malzemenin kuru kesme şartlarında tornalanması esnasında kesme parametrelerinin ve yaklaşma açısının çeşitli işlenebilirlik kıstasları üzerine etkisi deneysel olarak incelenmiştir. Dinamometre, akselerometre ve yüzey pürüzlülük cihazı kullanılarak esas kesme kuvveti (Fc), titreşim (Vb) ve deney malzemesi yüzey pürüzlülüğü (Ra) ölçümleri yapılmıştır. Taguchi tasarımına göre 27 adet deney yapılmış, deneylerde Fc ve Vb anlık olarak ölçülürken, işleme durdurulduğunda Ra ölçümü gerçekleştirilmiştir. Yaklaşma açısı ve kesme parametrelerinin etkisi grafiksel olarak incelenmiş, deney malzemesinin en iyi işlenme şartları farklı işlenebilirlik kıstasları göz önüne alınarak değerlendirilmiştir. Bu çalışmada, başta otomotiv sektörü olmak üzere çeşitli alanlarda yaygın kullanıma sahip olan ancak geçmişte sınırlı sayıda çalışmanın konusu olan AISI 5140 çeliğinin işlenebilirliği kapsamlı olarak incelenmiştir. Elde edilen bulgulara göre, Fc, Vb ve Ra üzerinde ilerleme oranının etkili parametre olduğu görülmüştür. Yaklaşma açısının Fc başta olmak üzere tüm kalite karakteristikleri üzerinde etkili olduğu görülmüştür.

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“…Grzesik [ 4 ] explored the wear mechanisms of ceramic inserts during hard turning of AISI 5140 steel. Other authors investigated the tool wear and chip morphology during turning of AISI 5140 [ 5 ], tool wear during boring [ 6 ], surface roughness and cutting forces [ 7 ] and surface roughness and tool wear [ 8 ]. To ascertain the machining performance of AISI 5140, Huang et al [ 9 ] studied the influence of lubrication on surface quality in grinding.…”

Section: Introductionmentioning

confidence: 99%

“…Abbas et al [ 44 ] employed RSM optimization in turning of AISI 1045 steel for investigation of surface roughness. On the investigation of surface roughness of AISI 5140 steel, the effect of cutting parameters namely feed rate and depth of cut [ 8 , 10 , 11 ] and cutting speed [ 7 , 8 , 11 ] were incorporated into the experimental plan. However, the influence of cutting edge angle was not reported in the past studies which motivate the need to study its impact on surface roughness linearly and interactively in the current study.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Cutting Parameters and Tool Geometry for Multi-Criteria Optimization of Surface Roughness and Vibration via Response Surface Methodology in Turning of AISI 5140 Steel

et al. 2020

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AISI 5140 is a steel alloy used for manufacturing parts of medium speed and medium load such as gears and shafts mainly used in automotive applications. Parts made from AISI 5140 steel require machining processes such as turning and milling to achieve the final part shape. Limited research has been reported on the machining vibration and surface roughness during turning of AISI 5140 in the open literature. Therefore, the main aim of this paper is to conduct a systematic study to determine the optimum cutting conditions, analysis of vibration and surface roughness under different cutting speeds, feed rates and cutting edge angles using response surface methodology (RSM). Prediction models were developed and optimum turning parameters were obtained for averaged surface roughness (Ra) and three components of vibration (axial, radial and tangential) using RSM. The results demonstrated that the feed rate was the most affecting parameter in increasing the surface roughness (69.4%) and axial vibration (65.8%) while cutting edge angle and cutting speed were dominant on radial vibration (75.5%) and tangential vibration (64.7%), respectively. In order to obtain minimum vibration for all components and surface roughness, the optimum parameters were determined as Vc = 190 m/min, f = 0.06 mm/rev, κ = 60° with high reliability (composite desirability = 90.5%). A good agreement between predicted and measured values was obtained with the developed model to predict surface roughness and vibration during turning of AISI 5140 within a 10% error range.

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A study on cutting and tribology performances of TiN and TiAlN coated tools

Cited by 38 publications

References 13 publications

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Investigation of the Effects of Approaching Angle and Cutting Parameters on Machinability of AISI 5140 Steel during Turning

Modeling of Cutting Parameters and Tool Geometry for Multi-Criteria Optimization of Surface Roughness and Vibration via Response Surface Methodology in Turning of AISI 5140 Steel

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