Cutting performance and wear characteristics of PVD coated and uncoated carbide tools in face milling Inconel 718 aerospace alloy

Jawaid, A.; Köksal, Sakıp; Sharif, Safian

doi:10.1016/s0924-0136(01)00850-0

Cited by 127 publications

(45 citation statements)

References 10 publications

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“…Cutting inserts were coated carbide as used with Settineri and Lerga [16] and Jawaid et al [17] with the standard designation (ISO) of SNGN 120408 with radius nose of 0.8 mm, commercialized by Sandvik under GC1025. The tool holder used in this experimental study has the standard designation of CSBNR2525M12 with the following angles: χr = 45°, α = 6°, γ = -6° and λ = -6° as mentioned in Coromant [18].…”

Section: Fig 1 Set-up and Design Of Experimentsmentioning

confidence: 99%

On the Modeling of Surface Roughness and Cutting Force when Turning of Inconel 718 Using Artificial Neural Network and Response Surface Methodology: Accuracy and Benefit

Tebassi¹,

Yallese²,

Meddour³

et al. 2017

Period. Polytech. Mech. Eng.

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IntroductionThe Inconel 718 is one of the most important materials used in modern industries. In addition of the best properties in terms of high strength, corrosion resistance, heat resistance and fatigue resistance, the Inconel 718 has, also a low thermal conductivity as it is mentioned by Lynch [1]. Certainly, this type of alloy is difficult to machine for the following reasons as it is presented by Alauddin [2]: High work hardening rates at machining, strain rates leading to high cutting forces; abrasiveness; toughness, gummy and strong tendency to weld to the tool with forming the built-up edge; low thermal properties leading to high cutting temperatures. However, it has a wide variety of applications such as aircraft gas turbines stack gas reheaters, reciprocating engines and others.In order to respond to the requirements of those applications, it is very important to forecasting surface roughness and cutting force. Consequently, it is necessary to search the best modeling approach of these output parameters. To obtain this objective, several approaches can be used as well as response surface methodology (RSM) and artificial neural network (ANN). Response surface methodology (RSM) is considered as a quick and useful procedure for the investigation and optimization of complex processes as well as modeling machining output parameters. Certainly, Davoodi and Eskandari [3] found that response surface methodology represents a better approach to predict tool life and productivity when turning of N-155 iron-nickel-base superalloy. Shihab et al. [4], investigated cutting temperature during hard turning of AISI 52100 alloy steel using multilayer coated carbide insert; they concluded that the developed RSM model is able to predict cutting temperature for different combination of input parameters very close to experimental values. Arokiadass et al. [5], used response surface methodology to modeling tool flank wear when end milling of LM 25 Al/SiCp with carbide tool. They concluded that the developed relationship can be effectively used to predict flank wear of carbide tool at a confidence level of 95%. Sahoo et al. [6], confirmed this conclusion when studying the development of flank wear model in turning hardened EN 24 steel with PVD TiN coated mixed ceramic insert under dry environment.

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Section: Fig 1 Set-up and Design Of Experimentsmentioning

confidence: 99%

On the Modeling of Surface Roughness and Cutting Force when Turning of Inconel 718 Using Artificial Neural Network and Response Surface Methodology: Accuracy and Benefit

Tebassi¹,

Yallese²,

Meddour³

et al. 2017

Period. Polytech. Mech. Eng.

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“…Cutting inserts were coated carbide (Settineri et al, 2008;Jawaid et al, 2001), with the standard designation (ISO) of SNGN 1204 with radius nose of 0.8 mm, commercialized by Sandvik under GC1025 (Sandvik, 2009). The tool holder used in this experimental study has the standard designation of CSBNR2525M12 with the following angles: χr = 45°, α = 6°, γ = -6° and λ = -6°.…”

Section: Materials and Measurementmentioning

confidence: 99%

“…When faced milling of Inconel 718 aerospace alloy, Jawaid et al (2001) obtained that the PVD TiN coated tools award a better performance than the uncoated tool at cutting speed of 50 m/min and feed rate of 0.08 mm per tooth. Results of machinability investigation of Incone1 718 (Rahman et al, 1997), indicated that the allowable speed and feed ranges for machining Inconel 718 were at notably low levels and tool life of the inserts decreased when the speed or the feed was increased; this is due to the commonly experienced high cutting forces, low thermal conductivity, abrasiveness and work hardening tendencies of work material, resulting in high heat generated at the cutting edge.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of surface roughness, cutting forces, productivity and Power consumption when turning of Inconel 718

Tebassi¹,

Yallese²,

Khettabi³

et al. 2016

10.5267/j.ijiec

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Nickel based super alloys are excellent for several applications and mainly in structural components submitted to high temperatures owing to their high strength to weight ratio, good corrosion resistance and metallurgical stability such as in cases of jet engine and gas turbine components. The current work presents the experimental investigations of the cutting parameters effects (cutting speed, depth of cut and feed rate) on the surface roughness, cutting force components, productivity and power consumption during dry conditions in straight turning using coated carbide tool. The mathematical models for output parameters have been developed using Box-Behnken design with 15 runs and Box-Cox transformation was used for improving normality. The results of the analysis have shown that the surface finish was statistically sensitive to the feed rate and cutting speed with the contribution of 43.58% and 23.85% respectively, while depth of cut had the greatest effect on the evolution of cutting force components with the contribution of 79.87% for feed force, 66.92% for radial force and 66.26% for tangential force. Multi-objective optimization procedure allowed minimizing roughness Ra, cutting forces and power consumption and maximizing material removal rate using desirability approach.

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“…Jawaid et al (2001), conducted experiments regarding the face milling if inconel 718 where the effect of cutting speed and feed on the tool wear were investigated by using a PVD TiN coated and uncoated tungsten carbide inserts. It was concluded that the uncoated inserts performed better at lower speeds while the coated inserts gave a better performance at higher speeds [6]. Sharman et al (2001), worked in the area of tool life using TiAlN and CrN coated tungsten carbide ball end milling cutters.…”

Section: Introduction and Literature Surveymentioning

confidence: 99%

Parametric Optimization Using The Particle Swarm Optimization (PSO) Technique for Minimizing Tool Wear While Milling Inconel 718 Alloy Assisted by Minimum Quantity Lubrication (MQL)

Sharma¹,

Singh²,

Sørby³

2016

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation

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Abstract-In today's industrial scenario, the high cost involved in manufacturing is the major concern apart from the environmental factors. With the manufacturing cost reaching sky high levels, the use of a suitable optimization technique has become one major requirement while designing any manufacturing process. The current study involves a series of milling experiments on Inconel 718 alloy. Minimum quantity lubrication has been used as the cooling technique alongside the flood and the dry conditions. The combined objective functions were generated using ANOVA. Particle swarm optimization (PSO) technique was used to optimize the input parameters i.e. the cutting speed (Vc), cutting feed (F) and the depth of cut (ae) in order to minimize the tool wear (Vbmax). A series of validation experiments were performed and the PSO technique proved to be a highly effective method in predicting the tool wear (Vbmax), also allowing a simultaneous comparison amongst the cooling methods, thus, suggesting MQL to be a better cooling technique when compared to the dry and the flood cooling.

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Cutting performance and wear characteristics of PVD coated and uncoated carbide tools in face milling Inconel 718 aerospace alloy

Cited by 127 publications

References 10 publications

On the Modeling of Surface Roughness and Cutting Force when Turning of Inconel 718 Using Artificial Neural Network and Response Surface Methodology: Accuracy and Benefit

On the Modeling of Surface Roughness and Cutting Force when Turning of Inconel 718 Using Artificial Neural Network and Response Surface Methodology: Accuracy and Benefit

Multi-objective optimization of surface roughness, cutting forces, productivity and Power consumption when turning of Inconel 718

Parametric Optimization Using The Particle Swarm Optimization (PSO) Technique for Minimizing Tool Wear While Milling Inconel 718 Alloy Assisted by Minimum Quantity Lubrication (MQL)

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