Effect of ball nose flank wear on surface integrity in high-speed hard milling of AISI 4340 steel using MQL.

Tool flank wear, owing to its direct interaction with the machined surface, can have detrimental effects on the workpiece surface integrity. This study investigates the impact of tool flank wear on surface integrity characteristics, particularly white layer thickness (WLT) and chemical corrosion resistance, during high-speed milling of AISI 4340 steel. Twenty-one experiments, ranging in 7 levels of flank wear widths (0-0.6 mm), were carried out under consistent cutting conditions in the presence of a minimum quantity lubrication (MQL) system. The results illustrate that up to a flank wear width of 0.4 mm, there is a modest increase in surface roughness, microhardness, and WLT. However, beyond this threshold, a significant escalation in these parameters is observed. Notably, a wear width of 0.6 mm induces non-uniform material flow, impacting microhardness up to 120 mm beneath the surface and causing a sudden increase in WLT. According to open-circuit potential analysis, the surface's tendency to electrochemical reactions increases slightly as the wear width increases up to 0.5 mm. The electrochemical impedance spectroscopy of the machined surfaces also revealed that utilizing tools worn to 0.4 and 0.6 mm, respectively, led to a decrease in Rcorr values by 35 % and 75 % compared to the specimen machined with a new tool. These insights underscore the critical importance of managing tool wear to maintain surface integrity in high-speed milling operations.

Assessing the cooling/lubricating agencies for sustainable alternatives during machining of Nimonic 80: Economic and environmental impacts.

Developing sustainable manufacturing methods that balance environmental and economic aspects is challenging. A comprehensive analysis of the economics of machining and carbon emissions is essential to encourage adopting sustainable practices. This work presents the machinability and comparative sustainability analysis of Nimonic 80 superalloy when it is machined utilizing a novel, environmentally friendly vegetable oil-based hybrid nanofluid-minimum quantity lubrication (MQL) and liquid carbon dioxide (LCO2) technique. The main objective is to comprehend the efficacy of the proposed approach on tool life, surface roughness, power consumption, total machining costs, and carbon emissions. Compared to other machining conditions, the use of hybrid nanofluid-MQL under 100 m/min cutting speed prevented rapid flank wear and considerably increased tool life by about 17-59 %. The change in cutting speed from 100 to 150 m/min has resulted in reduced tool life about 13-42 % under the selected environments. In addition, when compared to dry, flood, and MQL machining, the use of hybrid nanofluid-MQL and LCO2 reduced surface roughness by around 16-45 % at 150 m/min. Sustainability analysis revealed that machining at 150 m/min resulted in decreased costs ranging from 6.1 % to 36.4 % for selected cutting environments. Applying hybrid nanofluid-MQL lowered carbon emissions by 16.83 %, whereas LCO2 reduced carbon emissions by 14.6 % at 100 m/min. At 150 m/min, hybrid nanofluid-MQL and LCO2 lowered carbon emission by 22.3 % and 21.5 % at 150 m/min compared to dry machining. Compared to alternative cutting environments, hybrid nanofluid-MQL and LCO2 applications have longer tool lives, lower machining costs, and carbon emissions. As a result, they are economical and environmentally friendly.

Understanding the Relationship between Surface Quality and Chip Morphology under Sustainable Cutting Environments.

Although chip morphology changes according to the machining method and related cutting parameters, chip formation affects the quality of the machined surface. In this context, it is very important to understand the relationship between chip morphology and surface quality, especially in materials that are difficult to machine. In the presented study, the changes in chip morphology, surface morphology, and surface quality criteria (Ra and Rz) that occurred during the milling of precipitation-hardened steel in different cutting environments were analyzed. Milling experiments were carried out in dry, MQL (minimum quantity lubrication), nano-MQL (graphene), nano-MQL (hBN), Cryo, and Cryo-MQL environments using TiAlN-coated inserts and three different cutting speeds and feed rates. While the highest values in terms of Ra and Rz were measured in dry machining, the minimum values were obtained in a nano-MQL (hBN) cutting environment. Due to the lubrication and low friction provided by the MQL cutting environment, chips were formed in thinner segmented forms. This formation reduced the chip curve radius and thus provided a more stable surface morphology. On the other hand, Cryo-ambient gas could not effectively leak into the cutting zone due to the intermittent cutting process, but it increased the brittleness of the chips with the cooling effect and provided a similar surface morphology. The values of minimum Ra and Rz were obtained as 0.304 mm and 1.825 mm, respectively, at a 60 m/min cutting speed and 0.04 mm/rev feed. Consequently, the use of nano-MQL cutting medium is seriously recommended in terms of surface quality in milling operations of difficult-to-machine materials.

Performance assessment of vegetable-based additive enriched cutting fluid for eco-friendly machining environment.

The investigation focuses on determining the effects of canola oil-based cutting fluid with three different volume percentages of boric acid additives over the machining forces and surface roughness while turning hardened AISI 1018 mild steel. Experiments were carried out under Taguchi's design of the experiment concept. The minimum quantity lubrication (MQL) technique was followed to minimize the cutting fluid consumption. The homogeneity of the additives dispersed in the fluid has been validated through a zeta potential study. Machining forces and surface roughness were considered as chief machining objectives. The hybrid mathematical model, grey relational analysis (GRA)-artificial neural network (ANN), has been implemented to assess the performance of developed cutting fluid. The results explored that the canola oil cutting fluid with 5 wt% of boric acid additive exhibits lesser cutting forces and surface roughness. The optimal machining parameters identified by the hybrid modeling are 665 rpm of cutting speed, 35 mm/min of feed rate, and 0.3 mm of depth of cut, along with 5 wt% of boric acid composition in cutting fluid. The results explore the 2.677 times improvement in machining objective in comparison with a non-optimal set of parameters. The implementation of hybrid modeling is considered to be a novel attempt to minimize the machining objectives. It has been recorded a negligible error percentage of 0.66% between GRA and ANN prediction.

Datasets describing optimization of the cutting regime in the turning of AISI 316L steel for biomedical purposes based on the NSGA-II and NSGA-III multi-criteria algorithms.

There are several methods of analysis used in the metalworking industry for dry machining processes and with Minimum Quantity Lubrication (MQL). Evolutionary methods [1] have been used in the decision-making process in the machining process to select the optimal data and to analyze the behavior of variables such as cutting speed (V), feed rate (f) and cutting depth (ap). This work addresses the use of evolutionary algorithms of low dominance class II and III (NSGA-II and NSGA-III) to analyze from the multicriteria approach the initial wear of the cutting tool (VB), the energy consumption (E) and the machining time (t) in the turning process of the AISI 316L steel workpiece for biomedical purposes. As input variables to the algorithm with 54 records, there are: cutting speed (V: 200, 300, 400 m/min) and feed rate (f: 0.1, 0.15, 0.2 mm/rev). The experiment was developed for a dry (1) turning operation and with the use of MQL (-1). For the MQL lubrication regime, a TRI-COOL MD-1 lubricant was employed, a vegetable type used in ferrous and non-ferrous metal cutting operations. A BIDEMICS JX1 ceramic cutting tool was used.

Comparison of Tool Wear, Surface Roughness, Cutting Forces, Tool Tip Temperature, and Chip Shape during Sustainable Turning of Bearing Steel.

In this study, a comparison of measured cutting parameters is discussed while machining AISI 52100 low-alloy hardened steel under two different sustainable cutting environments, those in which a dry and minimum quantity lubrication (MQL) medium are used. A two-level full factorial design method has been utilized to specify the effect of different experimental inputs on the turning trials. Experiments were carried out to investigate the effects of three basic defining parameters of turning operation which are namely cutting speed, cutting depth, feed rate effects and also the effects of the cutting environment. The trials were repeated for the combination of different cutting input parameters. The scanning electron microscopy imaging method was used to characterize the tool wear phenomenon. The macro-morphology of chips was analyzed to define the influence of cutting conditions. The optimum cutting condition for high-strength AISI 52100 bearing steel was obtained using the MQL medium. The results were evaluated with graphical representations and they indicated the superiority of the pulverized oil particles on tribological performance of the cutting process with application of the MQL system.

The Effects of Lubricooling Ecosustainable Techniques on Tool Wear in Carbon Steel Milling.

This research analyses the viability of using cryogenic cooling combined with MQL (minimum quantity lubrication) lubrication, under CryoMQL technology, as a cutting fluid in the industrial environment to justify the increase in the environmental footprint generated by its use compared to MQL in stand-alone mode. For this analysis, a set of milling tests were carried out on carbon steel AISI 1045, which is one of the most commonly used materials in the business day-to-day. In this set of tests, the evolution of cutting edge wear and energy consumption of both technologies were recorded to check their tool life through technological and environmental analysis. Thus, we sought to discern whether the energy savings derived from the machining process make up for the greater environmental footprint initially generated by the use of CryoMQL technology itself. The results obtained show how the use of CryoMQL not only increased tool life, but also allowed an increase in productivity by increasing cutting speeds by 18%; in other words, thanks to this technology, a more technologically advanced and environmentally friendly process is obtained. By increasing tool life by 30%, a reduction in energy consumption is achieved together with cost savings, which implies that ECO2 machining has economic and ecological benefits.

Performance investigations for sustainability assessment of Hastelloy C-276 under different machining environments.

Hastelloy is categorized as difficult to cut superalloy widely used in aerospace, nuclear reactor components and chemical industry because of its magnificent strength and higher heat efficiency. Since, the machining of this material is quite difficult and hence suitable cooling systems are required to achieve sustainable manufacturing goals. The present investigation has been focused on the machining performance and sustainability assessment of turning Hastelloy C-276 in dry, flood and minimum quantity lubrication (MQL) environments. Taguchi L-9 array has been utilized to conduct and record the experimental output along with TOPSIS approach to evaluate the sustainability. The output responses viz. cutting forces, surface roughness, cutting temperature, energy consumption and carbon emission have been recorded at various levels of input variables. The experimental results revealed that MQL has minimized the cutting forces, surface roughness and temperature by margin of 20-38%. Likewise, energy expenditure and carbon emission was declined by 9-27% respectively compared to other conditions. Sustainability analysis explored best performance index during equal weightage criteria at 125 m/min, 0.246 and 0.8 mm doc under MQL. However, implementing assigned weightage system evaluated best condition for dry machining as 88 m/min and 0.246 mm/rev having same doc. SEM analysis of insert reported mainly abrasion and adhesion type of tool wear at all parametric range and machining conditions.

Experimental Investigation on Part Quality and Dust Emission during Minimum Quantity Lubricated (MQL) Edge Finishing of Granite.

Edge-finishing of granites by grinding is a process frequently used in the granite processing industry to generate the final desired shape and edge quality of products. However, this process releases significant amounts of fine and ultrafine particles (FPs and UFPs) containing crystalline silica. When inhaled, this dust can cause silicosis disease and threaten the health and safety of workers. The purpose of this study is to optimize the process by decreasing the concentrations of dust generated while also maintaining the required surface finish. Experimental tests were planned and performed on granite samples using a full factorial design. Two cutting tool edge shapes were studied (chamfer and concave) using G150 and G600 grit size tools, at various spindle speeds (1500, 2500, 3500 rpm), feed rates (500, 1000, 1500 mm/min) and lubrication flow rates (20, 40, 60 mL/min). The findings show that the particle emissions as well as the surface finish depend on the tool shape, its grit size, and the machining and lubrication parameters used. Higher MQL flow rates led to better finished surface quality and lower concentrations of fine dust. Polishing with flood lubrication reduces the maximum number concentration of FPs corresponding to particles smaller than 1 µm diameter by about 85% as compared to dry polishing and produced the best surface finish. Polishing with lubrication in MQL mode at 60 mL/min led to the production of part with Ra-value comparable with that obtained in flood lubrication condition.

Analysis of a Vegetable Oil Performance in a Milling Process by MQL Lubrication.

In this work, we carried out a comparison between the dry machining of an aluminum block with conventional cutting oil and a block with vegetable oil. The two oils had different flow rates. Using the Taguchi method, it was possible to determine the matrices for optimizing the best parameters for each group of tests. Then, we studied the utility of using vegetable oil as a cutting lubricant. We found that the vegetable oil studied in this work had good properties in terms of reducing cutting temperatures but was less effective than conventional cutting oil in reducing the surface roughness of the machined part. Tribological tests were carried out to understand the influence of the selected lubricants in reducing friction and wear. After the sliding experiments, which were performed without lubrication in the presence of the same lubricants that were used in the machining tests and in the presence of distilled water, we concluded that vegetable oil has satisfactory lubricating properties that are similar to those of the conventional cutting fluid, indicating a potential for consideration as an effective alternative to the conventional cutting fluid, with economic, environmental, and health advantages.

Parametric Study and Optimization of End-Milling Operation of AISI 1522H Steel Using Definitive Screening Design and Multi-Criteria Decision-Making Approach.

End-milling operation of steel grade material is a challenging task as it is hard-to-cut material. Proper selection of cutting tools, cutting conditions, and cutting process parameters is important to improve productivity, surface quality, and tool life. Therefore, the present study investigated the end-milling operation of AISI 1522H steel grade under minimum-quantity lubrication (MQL) conditions using a novel blend of vegetable oils, namely canola and olive oil. Cutting process parameters considered were spindle speed (s), feed rate (f), depth of cut (d), width of cut (w), and cutting conditions (c), while responses were average surface roughness (Ra), cutting forces (Fc), tool wear (TW), and material removal rate (MRR). Experimental runs were designed based on the definitive screening design (DSD) method. Analysis of variance (ANOVA) results show that feed rate significantly affects all considered responses. Nonlinear prediction models were developed for each response variable, and their validity was also verified. Finally, multi-response optimization was performed using the combinative distance-based assessment (CODAS) method coupled with criteria importance through inter-criteria correlation (CRITIC). The optimized parameters found were: s = 1200 rpm, f = 320 mm/min, d = 0.6 mm, w = 8 mm, and c = 100 mL/h. Further, it was compared with other existing multi-response optimization methods and induced good results.

Experimental and numerical investigation of heat generation and surface integrity of ZrO2 bioceramics in grinding process under MQL condition.

Zirconia bioceramics has tremendous potential in medical applications owing to biocompatibility and high mechanical properties. Meanwhile, thermal damage and surface defects limit the grindability to achieve the desired properties. Therefore, this research provides an investigation of various grinding parameters on heat generation and surface morphology using a diamond wheel. In addition, a triangular and parabolic moving heat flux is used for heat distribution analysis based on FEM-model. The parabolic model more corresponds to experimental compared to the triangular heat flux, with an average deviation of <5% and 6.5% under dry and MQL, respectively. The response surface methodology is applied to extract a statistical representation of inputs and outputs. Dry grinding temperature obtained in range of 200-540 °C, which by applying MQL, it decreased by 16-35%. Increasing cutting depth would worsen the MQL efficiency in force and temperature. Results indicate the impact of cutting depth on temperature and force is greatest, followed by the effect of feed-rate, and that of wheel speed is the least. Thus, the increasing feed-rate should be utilized to preserve the high removal rate. SEM images indicate material removal mechanism is accomplished by plastic and brittle mode. Furthermore, MQL and a combination of low depth of cut could effectively decline the surface roughness and defects formation by decreasing the brittle material removal mechanism in one step. MQL reduced surface roughness by 46% compared with dry grinding, so that its performance increase in higher cutting depth. Because at higher cutting depths, the MQL changes the prevailing chip removal mechanism from brittle to ductile-regime grinding.

The Influence of the Depth of Grinding on the Condition of the Surface Layer of 20MnCr5 Steel Ground with the Minimum Quantity Lubrication (MQL) Method.

This paper describes the research on abrasive machining conditions and their influence on microhardness and residual stresses distribution in the technological surface layer of 20MnCr5 steel. The roughness of ground samples was also measured. Samples underwent a vacuum carburizing process (LPC) followed by high-pressure gas quenching (HPGQ) in a 4D quenching chamber. Processes were realized with a single-piece flow method. Then, the flat surfaces of samples were ground with a Vortex type IPA60EH20VTX alumina grinding wheel using a flat-surface grinder. The samples were ground to three depths of grinding (ae = 0.01; 0.02; 0.03 mm) with grinding fluid supply using either flood method (WET) or minimum quantity lubrication (MQL) method. The condition of the technological surface layer was described using microhardness and residual stresses, as well as some selected parameters of surface roughness. The results obtained revealed that changes in microhardness as compared to microhardness of the material before grinding were lower in samples ground with grinding fluid supplied with MQL method. At the same time, the values of residual stresses were also better for samples ground using MQL method. Furthermore, the use of grinding fluid fed with MQL method produced lower values of surface roughness compared to the parameters obtained with WET method. It was concluded that for the tested scope of machining conditions, the MQL method can be a favourable alternative to the flood method of supplying grinding fluid into the grinding zone.

Recent progress and evolution of coolant usages in conventional machining methods: a comprehensive review.

This paper reviews recent progress and applications of usage of cutting fluids in conventional machining processes. In addition to reviewing the various conventional and advanced cooling techniques during machining, the paper also discusses the use of minimum quantity lubrication (MQL) in several types on metals such as steel, aluminum, alloy, and titanium alloys. Due to the toxicity of conventional cutting fluid resulting in ecological problems, the demand for environmentally friendly cutting fluid is rising. Therefore, natural vegetable oil is chosen as potential replacement as an environmentally friendly cutting fluid which fulfills the important aspects of biodegradability and sustainability. Application of vegetable oil-based cutting fluids under MQL techniques are also discussed. Moreover, the potential of palm oil as biodegradable and environmentally friendly natural vegetable oil-based metal-working fluids in MQL are reviewed.

Study of a Multicriterion Decision-Making Approach to the MQL Turning of AISI 304 Steel Using Hybrid Nanocutting Fluid.

The enormous use of cutting fluid in machining leads to an increase in machining costs, along with different health hazards. Cutting fluid can be used efficiently using the MQL (minimum quantity lubrication) method, which aids in improving the machining performance. This paper contains multiple responses, namely, force, surface roughness, and temperature, so there arises a need for a multicriteria optimization technique. Therefore, in this paper, multiobjective optimization based on ratio analysis (MOORA), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and technique for order of preference by similarity to ideal solution (TOPSIS) are used to solve different multiobjective problems, and response surface methodology is also used for optimization and to validate the results obtained by multicriterion decision-making technique (MCDM) techniques. The design of the experiment is based on the Box-Behnken technique, which used four input parameters: feed rate, depth of cut, cutting speed, and nanofluid concentration, respectively. The experiments were performed on AISI 304 steel in turning with minimum quantity lubrication (MQL) and found that the use of hybrid nanofluid (Alumina-Graphene) reduces response parameters by approximately 13% in forces, 31% in surface roughness, and 14% in temperature, as compared to Alumina nanofluid. The response parameters are analyzed using analysis of variance (ANOVA), where the depth of cut and feed rate showed a major impact on response parameters. After using all three MCDM techniques, it was found that, at fixed weight factor with each MCDM technique, a similar process parameter was achieved (velocity of 90 m/min, feed of 0.08 mm/min, depth of cut of 0.6 mm, and nanoparticle concentration of 1.5%, respectively) for optimum response. The above stated multicriterion techniques employed in this work aid decision makers in selecting optimum parameters depending upon the desired targets. Thus, this work is a novel approach to studying the effectiveness of hybrid nanofluids in the machining of AISI 304 steel using MCDM techniques.

Corrosion Resistance and Surface Bioactivity of Ti6Al4V Alloy after Finish Turning under Ecological Cutting Conditions.

The influence of cooling conditions and surface topography after finish turning of Ti6Al4V titanium alloy on corrosion resistance and surface bioactivity was analyzed. The samples were machined under dry and minimum quantity lubrication (MQL) conditions to obtain different surface roughness. The surface topographies of the processed samples were assessed and measured using an optical profilometer. The produced samples were subjected to electrochemical impedance spectroscopy (EIS) and corrosion potential tests (Ecorr) in the presence of simulated body fluid (SBF). The surface bioactivity of the samples was assessed on the basis of images from scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) analysis. The inspection of the surfaces of samples after turning under dry and MQL conditions revealed unevenly distributed precipitation of hydroxyapatite compounds (Ca/P) with a molar ratio in the range of 1.73-1.97. Regardless of the cutting conditions and surface roughness, the highest values of Ecorr ~0 mV were recorded on day 7 of immersion in the SBF solution. The impedance characteristics showed that, compared to the MQL conditions, surfaces machined under dry conditions were characterized by greater resistance and the presence of a passive layer on the processed surface. The main novelty of the paper is the study of the effect of ecological machining conditions, namely, dry and MQL cutting on the corrosion resistance and surface bioactivity of Ti6Al4V titanium alloy after finish turning. The obtained research results have practical significance. They can be used by engineers during the development of technological processes for medical devices made of Ti6Al4V alloy to obtain favorable functional properties of these devices.

Effect of Different Cooling Strategies on Surface Quality and Power Consumption in Finishing End Milling of Stainless Steel 316.

In this paper, an experimental investigation into the machinability of AISI 316 alloy during finishing end milling operation under different cooling conditions and with varying process parameters is presented. Three environmental-friendly cooling strategies were utilized, namely, dry, minimal quantity lubrication (MQL) and MQL with nanoparticles (Al2O3), and the variable process parameters were cutting speed and feed rate. Power consumption and surface quality were utilized as the machining responses to characterize the process performance. Surface quality was examined by evaluating the final surface roughness and surface integrity of the machined surface. The results revealed a reduction in power consumption when MQL and MQL + Al2O3 strategies were applied compared to the dry case by averages of 4.7% and 8.6%, respectively. Besides, a considerable reduction in the surface roughness was noticed with average values of 40% and 44% for MQL and MQL + Al2O3 strategies, respectively, when compared to the dry condition. At the same time, the reduction in generated surface roughness obtained by using MQL + Al2O3 condition was marginal (5.9%) compared with using MQL condition. Moreover, the results showed that the improvement obtained in the surface quality when using MQL and MQL + Al2O3 coolants increased at higher cutting speed and feed rate, and thus, higher productivity can be achieved without deteriorating final surface quality, compared to dry conditions. From scanning electron microscope (SEM) analysis, debris, furrows, plastic deformation irregular friction marks, and bores were found in the surface texture when machining under dry conditions. A slight smoother surface with a nano-polishing effect was found in the case of MQL + Al2O3 compared to the MQL and dry cooling strategies. This proves the effectiveness of lubricant with nanoparticles in reducing the friction and thermal damages on the machined surface as the friction marks were still observed when machining with MQL comparable with the case of MQL + Al2O3.

MaxQuant.Live Enables Enhanced Selectivity and Identification of Peptides Modified by Endogenous SUMO and Ubiquitin.

Small ubiquitin-like modifiers (SUMO) and ubiquitin are frequent post-translational modifications of proteins that play pivotal roles in all cellular processes. We previously reported mass spectrometry-based proteomics methods that enable profiling of lysines modified by endogenous SUMO or ubiquitin in an unbiased manner, without the need for genetic engineering. Here we investigated the applicability of precursor mass filtering enabled by MaxQuant.Live to our SUMO and ubiquitin proteomics workflows, which efficiently avoided sequencing of precursors too small to be modified but otherwise indistinguishable by mass-to-charge ratio. Using precursor mass filtering, we achieved a much higher selectivity of modified peptides, ultimately resulting in up to 30% more SUMO and ubiquitin sites identified from replicate samples. Real-time exclusion of unmodified peptides by MQL resulted in 90% SUMO-modified precursor selectivity from a 25% pure sample, demonstrating great applicability for digging deeper into ubiquitin-like modificomes. We adapted the precursor mass filtering strategy to the new Exploris 480 mass spectrometer, achieving comparable gains in SUMO precursor selectivity and identification rates. Collectively, precursor mass filtering via MQL significantly increased identification rates of SUMO- and ubiquitin-modified peptides from the exact same samples, without the requirement for prior knowledge or spectral libraries.

Performance Assessment of Minimum Quantity Castor-Palm Oil Mixtures in Hard-Milling Operation.

The necessity to progress towards sustainability has inspired modern researchers to examine the lubrication and cooling effects of vegetable oils on conventional metal cutting operations. Consequently, as an eco-friendly vegetable product, castor oil can be the right choice as Minimum quantity lubrication (MQL) base fluid. Nonetheless, the high viscosity of castor oil limits its flowability and restricts its industrial application. Conversely, palm oil possesses superior lubricity, as well as flowability characteristics. Hence, an attempt has been made to improve the lubrication behavior of castor oil. Here, six castor-palm mixtures (varying from 1:0.5-1:3) were utilized as MQL-fluid, and the values of machining responses viz. average surface roughness, specific cutting energy, and tool wear were evaluated. Furthermore, an integrated Shannon's Entropy-based Technique for order preference by similarity to ideal solution (TOPSIS) framework was employed for selecting the most suitable volume ratio of castor-palm oil mixture. The rank provided by the TOPSIS method confirmed that 1:2 was the best volume ratio for castor-palm oil mixture. Afterward, a comparative analysis demonstrated that the best castor-palm volume fraction resulted in 8.262 and 16.146% lowering of surface roughness, 5.459 and 7.971% decrement of specific cutting energy, 2.445 and 3.155% drop in tool wear compared to that of castor and palm oil medium, respectively.

Experimental Investigation and Statistical Evaluation of Optimized Cutting Process Parameters and Cutting Conditions to Minimize Cutting Forces and Shape Deviations in Al6026-T9.

Precise, economical and sustainable cutting operations are highly desirable in the advanced manufacturing environment. For this aim, the present study investigated the influence of cutting parameters (i.e., the cutting speed (c), feed rate (f), depth of cut (d) and positive rake angle (p)) and sustainable cutting conditions (dry and minimum quantity lubricant (MQL)) on cutting forces (i.e., feed force (Ff), tangential forces (Ft), radial force (Fr) and resultant cutting forces (Fc) and shape deviations (i.e., circularity and cylindricity) of a 6026-T9 aluminum alloy. The type of lubricant and insert used are virgin olive oil and uncoated tungsten carbide tool. Turning experiments were performed on a TAKISAWA TC-1 CNC lathe machine and cutting forces were measured with the help of a Kistler 9257B dynamometer. Shape deviations were evaluated by means of a Tesa Micro-Hite 3D DCC 474 coordinate measuring machine (CMM). Experimental runs were planned based on Taguchi mixture orthogonal array design L16. Analysis of variance (ANOVA) was performed to study the statistical significance of cutting parameters. Taguchi based signal to noise (S/N) ratios are applied for optimization of single response, while for optimization of multiple responses Taguchi based signal to noise (S/N) ratios coupled with multi-objective optimization on the basis of ratio analysis (MOORA) and criteria importance through inter-criteria correlation (CRITIC) are employed. ANOVA results revealed that feed rate, followed by a depth of cut, are the most influencing and contributing factors for all components of cutting forces (Ff, Ft, Fr, and Fc) and shape deviations (circularity and cylindricity). The optimized cutting parameters obtained for multi responses are c = 600 m/min, f = 0.1 mm/rev, d = 1 mm and p = 25°, while for cutting conditions, MQL is optimal.