Elsevier

Measurement

Volume 188, January 2022, 110594
Measurement

Cutting forces and temperature measurements in cryogenic assisted turning of AA2024-T351 alloy: An experimentally validated simulation approach

https://doi.org/10.1016/j.measurement.2021.110594Get rights and content

Highlights

  • FEM simulation of cutting forces and cutting temperature were performed.

  • Advantedge software was used for FEM simulation.

  • Experiments were performed to validate the results.

Abstract

Aluminium alloys are widely used in modern engineering applications such as automobile, aerospace etc because of its characteristics. The machining of aluminium alloys are also considered as difficult because of its sticky and soft nature, low thermal conductivity, strain hardening effect etc. The cooling conditions employed at cutting zone improved the machining performance but the resources, material consumption, skilled labor etc. are also required for performing the machining experiments. Therefore, the simulation of process parameters with the help of Finite Element Modelling (FEM) during machining is highly researched topic these days. In this work, a new practice from measurement science i.e., FEM simulation was performed with AdvantEdge software and the prediction models were developed for evaluating the cutting forces and cutting temperature while machining AA2024-T351 alloy under dry, liquid nitrogen (LN2) and carbon dioxide (CO2) conditions. Initially, the 3D turning model was developed and the results were compared with experimental findings. The results obtained from simulation model are very close with experimental results with minimum standard value of 0.67 (5.7%) for cutting forces and 4.58 (6.16%) for cutting temperature. Thus, it is worthy to mention that the 3D FE model is efficient and effective to predict and measurement results with minimum error.

Introduction

Aluminum is one of the most used materials in engineering after steel and cast iron [1]. In particular, Al-Cu alloys are increasingly used in aircraft and automotive industries due to its low density (2.7 gm/cm3), higher strength (18–26 kg/mm2) compared to other Al alloys, and heat treatment applicability [2], [3]. In general, metal materials are not used as much as they are obtained from nature. They have low mechanical properties (hardness, rupture, wear, etc.) as in pure aluminum material. Various methods are applied to improve the mechanical properties of materials. Alloying and heat treatment are some of the applied methods [4]. AA2024-T351 is the addition of alloying elements to pure aluminum material, and then tempering with the process of T351 that means solution heat-treated, stress-relieved with a controlled amount of stretching [5].

In addition to the positive aspects of the changing mechanical properties of the materials, there are also negative aspects. In particular, mechanical properties are directly effective in shaping the material (machining, cutting, bending, etc.) [6]. The shaping of materials by removing chips (turning, milling, drilling, etc.) has an important share in the manufacturing industry [7]. The machinability of the materials is of great importance in terms of cutting tools, cutting forces and surface roughness [8]. In the recent studies, materials were divided into two categories such as easy to machine and difficult to cut materials [9]. The easy and difficult machinability of the material is directly dependent on the mechanical properties of the material (flow, rupture, hardness, etc.) and the cutting parameters. Materials with high mechanical properties (for example, hardness) are difficult to process, while materials with low mechanical properties may be easier to machine. In the processing of materials with high mechanical properties, higher cutting forces and consequently higher temperatures may occur [10]. Although the machining of materials with low mechanical properties seems to be problem-free in terms of cutting forces and cutters, in some materials, it can also bring about negativities such as chip adhesion on the cutting insert, deterioration of the surface quality. Especially in the machining of aluminum alloys under dry cutting conditions, negative effects such as deterioration of the machined surface due to Built-up-Edge (BUE) formations and increase in cutting forces are observed a lot [11]. Apart from the mechanical properties of the materials, improperly selected cutting parameters (cutting speed, feed, depth of cut, etc.) can also cause negative effects such as increased cutting forces, low tool life, poor surface roughness [12], [13]. For that reason, cryogenic cooling processes are needed to avoid mentioned negativities in machining of aluminum alloys [14], [15]. In the cryogenic cooling process, the materials are cooled to very low temperatures (around −196 °C) to achieve the desired metallurgical and microstructural properties [16], [17].

Reduction of these temperature is possible by feeding the system with controlled liquid nitrogen (N2) or CO2 and using the most suitable insulation materials [18], [19]. Some important studies based on cryogenic cooling in machining of various alloys are summarized below. Chetan et al. [20] analyzed the tribological performance of Ti6Al4V alloy in machining with wet and cryogenic cooling conditions. The authors stated that cryogenic cooling is better than wet conditions in machining based on tool wear, carbon emission, machining cost. Ding and Hong [21] studied on cryogenic machining of AISI1008 steel considering, tool wear, temperature and surface quality and found that cryogenic is superior process for better surface quality, less tool temperature and wear. Sivaiah and Chakradhar [22] examined the machinability performance of 17–4 PH stainless steel with coated carbide cutting tools under cryogenic condition. The researchers indicated that cryogenic cooling successfully decrease the cutting region temperature and so can be suggested in machining of difficult to cut materials. Jebaraj et al. [23] compared the coolants of LN2 and CO2 in cryogenic machining of AISI L6 steel via TiAlN coated carbide cutting tools. They suggested that CO2 coolants are better than LN2 in terms of surface quality while LN2 conditions are better than CO2 based on cutting forces. Khanna et al. [24] associated the dry, flood, MQL and cryogenic cooling conditions in machining of stainless steel via carbide inserts. The authors revealed that cryogenic condition is more superior to MQL cooling condition in terms of surface quality, energy consumption and tool wear. Outerio et al. [25] researched on surface integrity in turning of AZ31B-O magnesium alloy under dry and cryogenic cooling conditions and finally showed that cryogenic cooling is better than dry condition based on cutting forces. Kaynak [26] evaluated the machinability performance of Inconel718 alloy under dry, MQL and cryogenic cooling conditions. The scientist conclusively found that cryogenic is the best machining condition based on tool wear and cutting zone temperature, while MQL is the best condition on surface quality. Eapen et al. [27] studied on dry and cryogenic machining of AA6063 aluminum alloy and dedicated that cryogenic condition is more suitable than dry condition for higher surface quality.

As mentioned above, these studies are commonly costly, material wasting and thus not eco-friendly. Therefore, some numerical methods are suggested in the research field. The most used in machining processes are the finite element method. Finite element (FE) method, providing the resolution of a complicated problem, is a popular and effective method used in several engineering applications [28]. Complex engineering problems involve complex solutions. This confusion also distracts the solution phase from sensitivity. The finite element method can be used to solve complex problems in the shortest way with the closest solution to the right result. The main finite element software’s used in the machining industry are DEFORM 3D, LS-Dyna, ABAQUS and Thirdwave Advantedge. Several critical studies based on FE in machining of aluminum alloys are summarized below. Li et al. [29] verified the finite element model of experimental high speed machining process with AA6061-T6 aluminum alloy. The authors also confirmed the Johnson-Cook model parameters of this alloy that are previously determined experimentally under high strain rates. Mali et al. [30] validated the simulational cutting forces with the experimental results by performing dry turning process to AA7075 aluminum alloys. The researchers also compared and confirmed the tool wear, chip behaviour and stresses on the cutting inserts from FE model. Lima et al. [31] studied on comparison of cutting temperatures between FE and experimental results in milling of AISI D2 steel by thermocouple methods and the finally verified the FE model by experimental conditions. Baraheni et al. [32] developed a FE model for ultrasonic drilling of 7075 aluminum alloy. The researchers verified the FE model through experimental drilling tests by higher than 80% accuracy. Khajehzadeh et al. [33] compared the experimental and FE results of ultrasonic turning for AISI 4140 steel. The scientists verified the FE thrust forces and residual stress via experimental drilling tests by 91% and 87%, respectively. Huang et al. [34] created a FE model for high speed milling of aluminum 7075 alloy and then confirmed the model with experimental milling processes under same conditions by high accuracy.

It is seen that studies of FE machining based on cryogenic cooling conditions for AA2024-T351 alloy is very limited in the literature. Although this alloy is highly used in aerospace applications, but still the work on simulation under different cooling condition is quiet limited. Therefore, the purpose of this research is to develop a FE model based on dry and LN2/CO2 cryogenic turning, and evaluate the performance of machinability in terms of cutting forces and cutting temperature for AA2024-T351 alloy. Moreover, the main aim is to contribute to the solution of the important problems mentioned in the related research on manufacturing. It is observed that there are differences in the cooling techniques used in scientific research and manufacturing. In this regard, it is intended that the results of this study are directly engaged in manufacturing and scientific research. Initially, the 3D cryogenic model was developed with FEM practice and the responses were predicted. Then, the comparison has been made with experimental results. The complete analysis of this work is shown in next sections.

Section snippets

Introduction of FE model

One of the most widely used solutions in recent years is finite element analysis, which divides complicated systems into particles, transforms them into idealized structures, and solves them mathematically [35]. For derivatives of finite elements, which are subcomponents of approximation functions, the finite element approach follows specific procedures [36]. The numerical solution procedure for parameters at specific points is defined as the nodes of each element and is applied to the

Results and discussions

In this simulation study, the 3D turning was analyzed and a new finite element model was developed with Thirdwave Advantage software using the process parameters and boundary conditions detailed above. The detail of simulation results are given below:

Conclusions

The study aims on the AA2204-T351 turning process under LN2/CO2 cooling and uses FEM to model this process. The purpose of this study is to analyze the extent to which the widely adopted LN2/CO2 cooling technology performs its intended function to meet the requirements for sustainable processing. In addition, in light of the FEM data of this study, it aims to validate the FEM simulation study through an experimental turning process and to validate the evaluation of the results obtainable from

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The research leading to these results has received funding from the Norway Grants 2014-2021 operated by National Science Centre under Project Contract No 2020/37/K/ST8/02795. The authors also acknowledge the Polish National Agency for Academic Exchange (NAWA) No. PPN/ULM/2020/1/00121 for financial support.

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