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This study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.

In this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).

The optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.

The MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.

Most studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.

This study aims to determine the properties of a new non-toxic cutting fluid and compared with cutting fluid based on mineral oil.

The tool wear was measured under dry and wet cutting conditions. The non-toxic cutting fluid was compared with cutting fluid based on mineral oil. The experiments were carried out using CTX 310 ECO numerical control lathe. The wear of the cutting tools was measured by means of stereo zoom microscopy (SX80), while the elements were identified through scanning electron microscopy (JSM 7100F). The workpiece surface texture was studied using a Talysurf CCI Lite non-contact 3D profiler. The contact wetting angle was established with a KSV CAM 100 tester.

The non-toxic cutting fluid has reached comparable coefficient of friction with a coolant containing mineral oil. The use of the non-toxic cutting fluid with low foaming tendency resulted in lower wear.

Machining processes require that cutting fluids be applied to reduce the tool wear and improve the quality of the workpiece surface. Cutting fluids serve numerous purposes such as they act as coolants and lubricants, remove chips and temporarily prevent corrosion of the product.

The investigations discussed in this paper have contributed to the development of non-toxic and environmentally friendly manufacturing because of the use of cutting fluid containing zinc aspartate and its comparison with commonly used cutting fluid.

Sustainable manufacturing is one of the most important and most challenging issues in present industrial scenario. With the intention of diminish negative effects associated with cutting fluids, the machining industries are continuously developing technologies and systems for cooling/lubricating of the cutting zone while maintaining machining efficiency. In the present study, three regression based machine learning techniques, namely, polynomial regression (PR), support vector regression (SVR) and Gaussian process regression (GPR) were developed to predict machining force, cutting power and cutting pressure in the turning of AISI 1045. In the development of predictive models, machining parameters of cutting speed, depth of cut and feed rate were considered as control factors. Since cooling/lubricating techniques significantly affects the machining performance, prediction model development of quality characteristics was performed under minimum quantity lubrication (MQL) and high-pressure coolant (HPC) cutting conditions. The prediction accuracy of developed models was evaluated by statistical error analyzing methods. Results of regressions based machine learning techniques were also compared with probably one of the most frequently used machine learning method, namely artificial neural networks (ANN). Finally, a metaheuristic approach based on a neural network algorithm was utilized to perform an efficient multi-objective optimization of process parameters for both cutting environment.

The purpose of this paper is to study the influence of the cutting conditions (cutting speed, feed rate and cutting depth) on the roughness (Ra) and on the flank wear (Vb) of the steel AISI 4140.

Mixed ceramic (CC650) and polycrystalline cubic boron nitride (PCBN) have been used to carry out straight turning tests under dry conditions.

The results indicate that PCBN is more efficient than mixed ceramic (Al2O3+TiC) used in terms of wear resistance regardless of the aggressiveness of the AISI 4140 at 50 hardness rockwell (HRC). Consequently, it is the most powerful. Surface quality attained with PCBN tool considerably compares with that of grinding. Even when the tool wear VB reached 0.3 mm, the majority of the recorded Ra values did not exceed 1 m at the various speeds tested. The correlation of tool wear Vb and surface roughness Ra established allows obtaining experimental empirical data on the cutting tool wear from measured surface roughness for practical use in industry. The values of constants and the coefficient of determination R² of this mathematical model will be calculated. Mathematical models expressing the relation between the elements of the cutting regime and technological parameters (tool life and roughness) are proposed.

Many works have been already made in the similar manner, but this study of CC650 and PCBN wear is the first. Through this study, we propose a mathematical model expressing the relation between the elements of the cutting regime, tool life and roughness.

The purpose of this paper is to evaluate the cooling ability of minimum quantity lubrication (MQL) cutting fluid.

An experimental system is devised to find the heat transfer coefficient of MQL under simulated reaming conditions. Cooling rate of the specimen is measured with an infrared camera. The effect of air pressure and oil volume on cooling rate is tested. Metal cutting tests are performed to evaluate the effect of heat transfer coefficient on workpiece temperature.

Convective heat transfer coefficient for MQL increases with increasing air pressure. Oil volume has an indeterminate effect on the heat transfer coefficient; however, it is a dominant factor for controlling temperature during reaming.

The results of the study can provide guidance to optimize the temperature controlling ability of MQL for production.

There is limited information available in literature regarding the heat transfer coefficient of metal working fluids, particularly for MQL. In particular, experiments designed to investigate the effect of air pressure and oil volume on the heat transfer coefficient of the mist have not been previously documented. This information may be used to improve the overall cooling ability of MQL mist, thus increasing its effectiveness at controlling tool wear and maintaining part quality. The other major contribution of this work is to separate the role of the cooling and lubrication for controlling temperature while reaming aluminum. Prior to this study, there has been relatively little research performed for the reaming metal cutting operation, and still less for reaming with MQL. The nature of how metal working fluids control temperature is not fully understood, and this work provides insight as to whether cooling or lubrication plays the dominant role for reaming.

This case is suitable for graduate-level quantitative analysis, business and government, environment and sustainability, and global economics courses. Students must consider the tradeoffs between continuing to run an old coal-burning plant and purchasing emissions allowances (EAs) versus upgrading to emissions-reducing wet or dry scrubbers. Reducing emissions creates the possibility of selling the plant's surplus EAs (which are likely to increase in price). Choosing a wet or dry scrubber requires considering installation cost and construction time, variable cost, and SO2 removal efficiency. Ideally, the investment should pay back over time, but management believes some net investment could also be justified. For that, however, complete analyses from both economic and environmental perspectives are required. A supplemental spreadsheet is available to accompany the case (UVA-QA-0726X).

The main purpose of the study was to analyze the relationship between cutting forces and tool wear during turning of steel 30CrNiMo8.

It is very important to find the optimal machining conditions to increase the tool life and to improve product quality. Width of tool wear was measured by universal microscope.

During experimental procedure, one chip shape was obtained for the given machining parameters. Results showed negligible tool wear for the given experimental conditions. In other words, the tool wear is negligible for one chip shape.

To increase tool wear, there are different chip shapes.

ATTEMPTS have been made in the past to use liquid carbon dioxide as a cutting coolant, notably in the U.S.A. However, results were not in general very satisfactory, and this may have been because the material was applied by people who were more familiar with machine tools than with carbon dioxide. Recently considerable progress has been made, however, by The Carbon Dioxide Company—a Division of the Distillers Company Ltd. The earlier attempts had taken the form of spraying a relatively large jet of the liquefied gas on to the work and tool generally. This proved to be wasteful of the gas, and in any case cooled the chip as much as the tool, which to a large extent cancels out the benefits gained from keeping the tool cool. The most important property of carbon dioxide as a coolant is that, when expanded to the atmosphere, a portion of the liquid becomes gas, while the consequent cooling, due to the absorption of the latent heat of vaporization, converts a further portion of the liquid to solid CO2 in the form of ‘snow’. This solid exists, under atmospheric pressure, at—78 deg. C., and under these conditions will sublime directly into gas, with a latent heat absorption from the surroundings of 250 B.T.U. per lb. of solid gasified. It can be seen that, if full use is made of these properties, very high rates of heat removal can be achieved.

Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in machining operations due to growing awareness of ecological and health issues, government strict environmental regulations and economic pressures. Therefore, the purpose of this study is to raise awareness of the minimum quantity lubrication (MQL) technique as a potential substitute for environmental restricted wet (flooded) machining situations.

The methodology adopted for conducting a review in this study includes four sections: establishment of MQL technique and review of MQL machining performance comparison with dry and wet (flooded) environments; analysis of the past literature to examine MQL turning performance under mono nanofluids (M-NF); MQL turning performance evaluation under hybrid nanofluids (H-NF); and MQL milling, drilling and grinding performance assessment under M-NF and H-NF.

From the extensive review, it has been found that MQL results in lower cutting zone temperature, reduction in cutting forces, enhanced tool life and better machined surface quality compared to dry and wet cutting conditions. Also, MQL under H-NF discloses notably improved tribo-performance due to the synergistic effect caused by the physical encapsulation of spherical nanoparticles between the nanosheets of lamellar structured nanoparticles when compared with M-NF. The findings of this study recommend that MQL with nanofluids can replace dry and flood lubrication conditions for superior machining performance.

Machining under the MQL regime provides a dry, clean, healthy and pollution-free working area, thereby resulting the machining of materials green and environmentally friendly.

This paper describes the suitability of MQL for different machining operations using M-NF and H-NF.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/

The purpose of this paper is to investigate the influence of turning parameters such as cutting speed, feed rate and depth of cut on tool flank wear and machined surface quality of AISI 304 stainless steel during environment friendly turning under nanofluid minimum quantity lubrication (NMQL) conditions using PVD-coated carbide cutting inserts.

Turning experiments are conducted as per the central composite rotatable design under the response surface methodology. ANOVA and regression analysis are employed to examine significant cutting parameters and develop mathematical models for VB (tool flank wear) and R_a (surface roughness). Multi-response desirability optimization approach is used to investigate optimum turning parameters for simultaneously minimizing VB and R_a.

Optimal input turning parameters are observed as follows: cutting speed: 168.06 m/min., feed rate: 0.06 mm/rev. and depth of cut: 0.25 mm with predicted optimal output response factors: VB: 106.864 µm and R_a: 0.571 µm at the 0.753 desirability level. ANOVA test reveals depth of cut and cutting speed-feed rate interaction as statistically significant factors influencing tool flank wear, whereas cutting speed is a dominating factor affecting surface roughness. Confirmation tests show 5.70 and 3.71 percent error between predicted and experimental examined values of VB and R_a, respectively.

AISI 304 is a highly consumed grade of stainless steel in aerospace components, chemical equipment, nuclear industry, pressure vessels, food processing equipment, paper industry, etc. However, AISI 304 stainless steel is considered as a difficult-to-cut material because of its high strength, rapid work hardening and low heat conductivity. This leads to lesser tool life and poor surface finish. Consequently, the optimization of machining parameters is necessary to minimize tool wear and surface roughness. The results obtained in this research can be used as turning database for the above-mentioned industries for attaining a better machined surface quality and tool performance under environment friendly machining conditions.

Turning of AISI 304 stainless steel under NMQL conditions results in environment friendly machining process by maintaining a dry, healthy, clean and pollution free working area.

Machining of AISI 304 stainless steel under vegetable oil-based NMQL conditions has not been investigated previously.