Investigations of Machining Characteristics in the Upgraded MQL-Assisted Turning of Pure Titanium Alloys Using Evolutionary Algorithms

Effect of Ranque-Hilsch Vortex Tube Cooling to Enhance the Surface-Topography and Tool-Wear in Sustainable Turning of Al-5.6Zn-2.5Mg-1.6Cu-0.23Cr-T6 Aerospace Alloy

The aerospace metal cutting industry's search for environmentally friendly practices that do not compromise machining performance is well known. One of the major objectives is the reduction in use of cutting fluids, which play a major role in containing the harsh effects of severe heat generated during machining. Machining performance and product quality can be improved by controlling heat during machining. The purpose of this study was to determine the effectiveness of various environmentally friendly metalworking fluid (MF) strategies for the sustainable turning of aerospace aluminum alloy (Al-5.6Zn-2.5Mg-1.6Cu-0.23Cr-T6) for automotive, marine, and aerospace industrial applications. The SEM images were analyzed for worn tool surfaces and machined surfaces. Under dry conditions, heat does not dissipate well, and will enter the workpiece due to the absence of coolant. This causes extreme damage beneath a turned workpiece. Thus, at 10 µm, a drop in microhardness of approximately 20% can be observed. A similar observation was made in a Ranque-Hilsch vortex tube (RHVT) and in compressed air; however, the drop in hardness was relatively low compared to dry conditions. This evaluation of microhardness indicated a heat-based attention in the turned workpiece, and thus, the heat-based effect was found to be lowest in RHVT and compressed air compared to dry conditions. Results showed that RHVT reduces temperature up to 10%, surface roughness 13%, and tool wear 20% compared to dry turning. Overall, RHVT was identified as more effective environmentally friendly cooling strategy than dry and compressed air for the turning of aluminum alloy 7075-T6.

Contribution Ratio Assessment of Process Parameters on Robotic Milling Performance

Robotic milling has broad application prospects in many processing fields. However, the milling performance of a robot in a certain posture, such as in face milling or grooving tasks, is extremely sensitive to process parameters due to the influence of the serial structure of the robot system. Improper process parameters are prone to produce machining defects such as low surface quality. These deficiencies substantially decrease the further application development of robotic milling. Therefore, this paper selected a certain posture and carried out the robotic flat-end milling experiments on a 7075-T651 high-strength aeronautical aluminum alloy under dry conditions. Milling load, surface quality and vibration were selected to assess the influence of process parameters like milling depth, spindle speed and feed rate on the milling performance. Most notably, the contribution ratio based on the analysis of variance (ANOVA) was introduced to statistically investigate the relation between parameters and milling performance. The obtained results show that milling depth is highly significant in milling load, which had a contribution ratio of 69.25%. Milling depth is also highly significant in vibration, which had a contribution ratio of 51.41% in the X direction, 41.42% in the Y direction and 75.97% in the Z direction. Moreover, the spindle speed is highly significant in surface roughness, which had a contribution ratio of 48.02%. This present study aims to quantitatively evaluate the influence of key process parameters on robotic milling performance, which helps to select reasonable milling parameters and improve the milling performance of the robot system. It is beneficial to give full play to the advantages of robots and present more possibilities of robot applications in machining and manufacturing.

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 (E_corr) 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 E_corr ~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.

Surface Treatment of the Dental Implant with Hyaluronic Acid: An Overview of Recent Data

Recently, interest has grown by focusing on the evaluation of a molecule already produced in the human body such as hyaluronic acid (HA), as an application to the surface of the titanium implant. Its osteo-conductive characteristics and positive interaction with the progenitor cells responsible for bone formation, consequently, make it responsible for secondary stability. The aim of this work was to analyze the various surface treatments in titanium implants, demonstrating that the topography and surface chemistry of biomaterials can correlate with the host response; also focusing on the addition of HA to the implant surface and assessing the biological implications during early stages of recovery. Used as a coating, HA acts on the migration, adhesion, proliferation and differentiation of cell precursors on titanium implants by improving the connection between implant and bone. Furthermore, the improvement of the bioactivity of the implant surfaces through HA could therefore facilitate the positioning of the dental prosthesis precisely in the early loading phase, thus satisfying the patients’ requests. It is important to note that all the findings should be supported by further experimental studies in animals as well as humans to evaluate and confirm the use of HA in any field of dentistry.

Optimization of process parameters for turning of titanium alloy (Grade II) in MQL environment using multi-CI algorithm

The advancement of materials science during the last few decades has led to the development of many hard-to-machine materials, such as titanium, stainless steel, high-strength temperature-resistant alloys, ceramics, refractories, fibre-reinforced composites, and superalloys. Titanium is a prominent material and widely used for several industrial applications. However, it has poor machinability and hence efficient machining is critical. Machining of titanium alloy (Grade II) in minimum quantity lubrication (MQL) environment is one of the recent approaches towards sustainable manufacturing. This problem has been solved using various approaches such as experimental investigation, desirability, and with optimization algorithms. In the group of socio-inspired optimization algorithm, an artificial intelligence (AI)-based methodology referred to as Cohort Intelligence (CI) has been developed. In this paper, CI algorithm and Multi-CI algorithm have been applied for optimizing process parameters associated with turning of titanium alloy (Grade II) in MQL environment. The performance of these algorithms is exceedingly better as compared with particle swarm optimization algorithm, experimental and desirability approaches. The analysis regarding the convergence and run time of all the algorithms is also discussed. It is important to mention that for turning of titanium alloy in MQL environment, Multi-CI achieved 8% minimization of cutting force, 42% minimization of tool wear, 38% minimization of tool-chip contact length, and 15% minimization of surface roughness when compared with PSO. For desirability and experimental approaches, 12% and 8% minimization of cutting force, 42% and 47% minimization of tool wear, 53% and 40% minimization of tool-chip contact length, and 15% and 20% minimization of surface roughness were attained, respectively.

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.

Precision Hard Turning of Ti6Al4V Using Polycrystalline Diamond Inserts: Surface Quality, Cutting Temperature and Productivity in Conventional and High-Speed Machining

This article presents the results of an experimental investigation into the machinability of Ti6Al4V alloy during hard turning, including both conventional and high-speed machining, using polycrystalline diamond (PCD) inserts. A central composite design of experiment procedure was followed to examine the effects of variable process parameters; feed rate, cutting speed and depth of cut (each at five levels) and their interaction effects on surface roughness and cutting temperature as process responses. The results revealed that cutting temperature increased with increasing cutting speed and decreasing feed rate in both conventional and high-speed machining. It was found that high-speed machining showed an average increase in cutting temperature of 65% compared with conventional machining. Nevertheless, high-speed machining showed better performance in terms of lower surface roughness despite using higher feed rates compared to conventional machining. High-speed machining of Ti6Al4V showed an improvement in surface roughness of 11% compared with conventional machining, with a 207% increase in metal removal rate (MRR) which offered the opportunity to increase productivity. Finally, an inverse relationship was verified between generated cutting temperature and surface roughness. This was attributed mainly to the high cutting temperature generated, softening, and decreasing strength of the material in the vicinity of the cutting zone which in turn enabled smoother machining and reduced surface roughness.

MQL Strategies Applied in Ti-6Al-4V Alloy Milling-Comparative Analysis between Experimental Design and Artificial Neural Networks

This paper presents a study of the Ti-6Al-4V alloy milling under different lubrication conditions, using the minimum quantity lubrication approach. The chosen material is widely used in the industry due to its properties, although they present difficulties in terms of their machinability. A minimum quantity lubrication (MQL) prototype valve was built for this purpose, and machining followed a previously defined experimental design with three lubrication strategies. Speed, feed rate, and the depth of cut were considered as independent variables. As design-dependent variables, cutting forces, torque, and roughness were considered. The desirability optimization function was used in order to obtain the best input data indications, in order to minimize cutting and roughness efforts. Supervised artificial neural networks of the multilayer perceptron type were created and tested, and their responses were compared statistically to the results of the factorial design. It was noted that the variables that most influenced the machining-dependent variables were the feed rate and the depth of cut. A lower roughness value was achieved with MQL only with the use of cutting fluid with graphite. Statistical analysis demonstrated that artificial neural network and the experimental design predict similar results.

Reduction of Power Consumption by Chip Breakability Control in Ti6Al4V Titanium Alloy Turning

The paper concerns the problem of energy savings in turning of titanium alloy Ti6Al4V. Since this alloy belongs to difficult to cut materials, there is a problem with chip forming and breaking. The turning process is often supported by implementing a high-pressure cooling (HPC) system. Based on the observations and the adopted chip classification method, the authors proved that it is not necessary to use this method in roughing operations, however it helps with the chips breaking process in finishing operations. A general algorithm for machining optimization due to the chip geometry is presented and described. In the presented case, it was shown that the acceptable chip geometry could be obtained with a reduced power consumption by approximately Pc = 0.5 kW. The authors concluded that it was not necessary to apply cutting data and a coolant system to achieve perfect chip geometry. An acceptable form was often sufficient, while requiring less energy. An additional factor resulting from the operation of systems supporting the cutting process, such as an HPC device, should be taken into account in the formula concerning the energy consumption (EC) of a computerized numerical control (CNC) machine tool.

Repairing Hybrid Mg-Al-Mg Components Using Sustainable Cooling Systems

This paper focused on the maintenance or repair of holes made using hybrid Mg–Al–Mg components by drilling, using two sustainable cooling techniques (dry machining and cold compressed air) and taking surface roughness on the inside of the holes as the response variable. The novelty of the work is in proving that the repair operations of the multi-material components (magnesium–aluminum–magnesium) and the parts made of aluminum and magnesium (separately) but assembled to form a higher component can be done simultaneously, thus reducing the time and cost of the assembly and disassembly of this type of component. The study is based on a design of experiments (DOE) defined as a product of a full factorial 2³ and a block of two factors (3 × 2). Based on our findings, we propose that the analyzed operations are feasible under sustainable conditions and, in particular, under dry machining. Also, the results depend on the machining order.

Sustainable Lubrication Methods for the Machining of Titanium Alloys: An Overview

Titanium is one of the most interesting materials in modern manufacturing thanks to its good mechanical properties and light weight. These features make it very attractive for use in the aeronautical and aerospace industries. Important alloys, such as Ti6Al4V, are extensively used. Nevertheless, titanium alloys present several problems in machining processes. Their machinability is poor, affected by low thermal conductivity, which generates very high cutting temperatures and thermal gradients in the cutting tool. Lubricants and cutting fluids have traditionally been used to solve this problem. However, this option is unsustainable as such lubricants represent a risk to the environment and to the health of the operator due to their different chemical components. Therefore, novel, sustainable and green lubrication techniques are necessary. Dry machining is the most sustainable option. Nevertheless, difficult-to-machine materials like titanium alloys cannot be machined under these conditions, leading to very high cutting temperatures and excessive tool wear. This study is intended to describe, analyse and review the non-traditional lubrication techniques developed in turning, drilling and milling processes since 2015, including minimum quantity of lubricant, cryogenic lubrication, minimum quantity of cooling lubrication or high-pressure coolant. The aim is to provide a general overview of the recent advances in each technique for the main machining processes.

Modelling of Guillotine Cutting of a Cold-Rolled Steel Sheet

In this paper, the modelling of a cutting process of a cold-rolled steel sheet using a symmetrical cutting tool is presented. The fast-changing nonlinear dynamic cutting process was elaborated by means of the finite element method and the computer system LS-DYNA. Experimental investigations using scanning electron microscopy were performed and the results are presented in this work. The numerical results were compared with experimental ones. The comparison shows a good agreement between the results obtained by means of numerical modelling and those received from experimental investigations. The numerical simulations of the cutting process and the experimental investigations aimed to understand the mechanism of the cutting process. They serve as a highly professional tool for carrying out research investigating the behavior of complex nonlinear fast-changing dynamical cutting processes in the future.

Performance Evaluation of Vegetable Oil-Based Nano-Cutting Fluids in Environmentally Friendly Machining of Inconel-800 Alloy

Recently, the application of nano-cutting fluids has gained much attention in the machining of nickel-based super alloys due their good lubricating/cooling properties including thermal conductivity, viscosity, and tribological characteristics. In this study, a set of turning experiments on new nickel-based alloy i.e., Inconel-800 alloy, was performed to explore the characteristics of different nano-cutting fluids (aluminum oxide (Al₂O₃), molybdenum disulfide (MoS₂), and graphite) under minimum quantity lubrication (MQL) conditions. The performance of each nano-cutting fluid was deliberated in terms of machining characteristics such as surface roughness, cutting forces, and tool wear. Further, the data generated through experiments were statistically examined through Box Cox transformation, normal probability plots, and analysis of variance (ANOVA) tests. Then, an in-depth analysis of each process parameter was conducted through line plots and the results were compared with the existing literature. In the end, the composite desirability approach (CDA) was successfully implemented to determine the ideal machining parameters under different nano-cutting cooling conditions. The results demonstrate that the MoS₂ and graphite-based nanofluids give promising results at high cutting speed values, but the overall performance of graphite-based nanofluids is better in terms of good lubrication and cooling properties. It is worth mentioning that the presence of small quantities of graphite in vegetable oil significantly improves the machining characteristics of Inconel-800 alloy as compared with the two other nanofluids.

Sandblasted and Acid Etched Titanium Dental Implant Surfaces Systematic Review and Confocal Microscopy Evaluation

The field of dental implantology has made progress in recent years, allowing safer and predictable oral rehabilitations. Surely the rehabilitation times have also been reduced, thanks to the advent of the new implant surfaces, which favour the osseointegration phases and allow the clinician to rehabilitate their patients earlier. To carry out this study, a search was conducted in the Pubmed, Embase and Elsevier databases; the articles initially obtained according to the keywords used numbered 283, and then subsequently reduced to 10 once the inclusion and exclusion criteria were applied. The review that has been carried out on this type of surface allows us to fully understand the features and above all to evaluate all the advantages or not related. The study materials also are supported by a manufacturing company, which provided all the indications regarding surface treatment and confocal microscopy scans. In conclusion, we can say that, thanks to these new surfaces, it has been possible to shorten the time necessary to obtain osseointegration and, therefore, secondary stability on the part of implants. The surfaces, therefore, guarantee an improved cellular adhesion and thanks to the excellent wettability all the biological processes that derive from it, such as increases in the exposed implant surface, resulting in an increase in bone-implant contact (BIC).