Metal-cutting Process Research Articles

Strategic selection of metal-cutting processes for thick steel plates using a hybrid decision methodology

Metal-cutting is indispensable in manufacturing, enabling precise component fabrication for industries like construction, automotive, aerospace, and shipbuilding, where accurate, efficient cutting of thick steel plates is crucial. This paper introduces a novel case study to strategically determine the optimal metal-cutting process for thick steel plates utilizing a hybrid MOORA-PSI approach. The use of the hybrid MOORA-PSI method simplifies decision-making by integrating weight assignment and ranking of alternatives. Five prominent metal-cutting processes, including oxygen flame, plasma arc, laser, wire EDM (wire electro-discharge machining), and abrasive water jet cutting, are commonly used for cutting thick steel plates, each with unique capabilities and limitations, and are considered potential alternatives. Eight evaluation criteria, capital cost, running cost, accuracy, edge quality, kerf width, maximum thickness, production flexibility, and production rate, are used to assess these metal-cutting alternatives. Wire EDM ranks as the optimal choice for cutting thick steel plates based on defined evaluation criteria, with laser cutting closely trailing, followed by oxygen flame, abrasive water jet, and plasma cutting successively. The results are validated by comparing them with those of other MCDM approaches and by conducting a Spearman’s rank correlation coefficient test, yielding consistent results. Additionally, sensitivity analysis, employing criteria weight exchange and dynamic variations in the decision-making matrix, further confirms the accuracy and reliability of the findings.

Effect of cutting process using cutting insert of grade UTi20T

In the metal-cutting industry, the precision of the metal-cutting process is of paramount importance. Errors in the metal-cutting process not only lead to damage to the cutting tool but also result in the production of low-quality materials. The incorporation of insert materials in the cutting process is aimed at maintaining cutting precision and achieving superior results. This research seeks to investigate the impact of the cutting process utilizing grade KC5410 cutting insert under minimum quantity lubrication (MQL) Conditions. In this study, machining tests were conducted using the ALPHA 1350S 2-axis computer numerical control (CNC) lathe machine under MQL conditions, employing cutting tool inserts UTi20T supplied by Mitsubishi. Two types of tools were utilized in the cutting process, namely UTi20T. Critical aspects such as cutting force, total power consumption, surface roughness, and tool life were analyzed to provide comprehensive insights into the efficiency of the cutting process. The findings of this study significantly contribute to the understanding of how the integration of Grade KC5410 cutting inserts under MQL conditions can enhance the overall efficiency of metal-cutting operations. The successful machinability assessment was conducted by implementing sustainable machining practices.

Application of 3D Imaging for Analyzing the Chip Groove Shapes of Cutting Inserts

An effective chip formation process is significant for an efficient metal-cutting process. Long continuous chips can lead to scratches on the machined surface, increasing the risk to operator safety and stability of the machining process. The use of chip grooves on cutting inserts allows for control of the chip formation and breaking process during machining. The shape of the rake surface and the design of the chip groove also affect the efficiency of the machining process. The article presents the use of 3D imaging to analyze changes in the selected chip groove shapes depending on the cutting depth ap = 0.10, 0.25, and 0.50 mm and the angular location of the cutting insert relative to the machined surface of the workpiece (i.e., major cutting-edge angle K = 60° and K = 90°). The analysis methodology was based on the use of 3D image registration and surface shape modeling. In the analysis based on the 3D imaging presented, the novelty was the adaptation of methods typically used to map and model the terrain surface, which have not been used previously in cutting processes. The evaluation of the shape of the chip groove surface was carried out using, e.g., watershed maps and 3D surface maps. The obtained results indicated a significant influence of the cutting depth and major cutting-edge angle on the surface shape, profile, and length of the chip former; chip groove volume; and the theoretical contact area of the formed chip with the cutting insert. It was observed that for small depths of cut, i.e., ap < 0.25 mm, the chip-curling process may be difficult due to the flattened shape of the rake surface. In addition, the influence of the convexity of the rake surface of the cutting insert on the chip formation process was demonstrated. The results of the experimental research that verified the conclusions are presented. The developed results may be useful in the process of selecting the parameters and conditions of the metal finishing through use of tools with a shaped rake surface.

Chatter Stability Prediction for Deep-Cavity Turning of a Bent-Blade Cutter.

The bent-blade cutter is widely used in machining typical deep-cavity parts such as turbine discs and disc shafts, but few scholars have studied the dynamics of the turning process. The existing mechanism of regenerative chatter in the metal-cutting process does not consider the influence of bending and torsional vibration, the change of tool profile and the complex machining geometry, so it cannot be directly used to reveal the underlying cause of the chatter phenomena in the deep inner cavity part turning process. This paper attempts to investigate the dynamic problem of the bent-blade cutter turning process. The dynamic model of a bent-blade cutter is proposed by considering the regenerative chatter effect. Based on the extended Timoshenko beam element (E-TBM) theory and finite element method (FEM), the coupling between the bending vibrations and the torsional vibrations, as well as the dynamic cutting forces, are modeled along the turning path. The vibration characteristics of the bending-torsion combination of cutter board and cutter bar, together with the dynamical governing equation, were analyzed theoretically. The chatter stability of a bent-blade cutter with a bending and torsion combination effect is predicted in the turning process. A series of turning experiments are carried out to verify the accuracy and efficiency of the presented model. Furthermore, the influence of cutting parameters on the cutting process is analyzed, and the results can be used to optimize the cutting parameters for suppressing machining vibration and improving machining process stability.

Application of Fuzzy Case-Based Reasoning and Fuzzy Analytic Hierarchy Process for Machining Cutter Planning and Control

Cutter planning and control are the crucial problems in machining processes. The current literature indicates that the issue of cutter planning and control problem was not adequately researched in the past in a metal-cutting process. Usually, cutter planning and control problems were addressed using different optimization, simulation, and computer-aided planning (CAP) methods. To bridge this knowledge gap, this study proposed a decision support system (DSS) that can integrate fuzzy case-based reasoning (F-CBR) and fuzzy analytic hierarchy process (F-AHP) methods. This integration was applied to determine hybrid similarity measures between new and prior cases. The study provides new insights into the integration of fuzzy set theory (FST), CBR, and AHP for solving machining cutter planning and control problems. Our proposed system retrieves the best similar prior cases to reuse and adapt them to new order arrivals. A numerical example was illustrated to validate the soundness of the researched DSS.

Experimental Investigation on the Machinability Improvement in Magnetic-Field-Assisted Turning of Single-Crystal Copper.

The single-point diamond-turning operation is a commonly used method for ultra-precision machining of various non-ferrous materials. In this paper, a magnetic field was introduced into a single-point diamond-turning system, and magnetic-field-assisted turning experiments were carried out. The results revealed that the magnetic field affects the metal-cutting process in the form of the cutting force, chip morphology, and surface quality. Compared with traditional turning, magnetic-field assisted turning increases the cutting force by 1.6 times, because of the additional induced Lorentz force, and reduces the cutting-force ratio and friction coefficient on the rake surface by 16%, with the improved tribological property of the tool/chip contact-interface. The chip morphology in the magnetic-field-assisted turning shows the smaller chip-compression ratio and the continuous side-morphology. With the magnetoplasticity effect of the metal material and the friction reduction, magnetic-field-assisted turning is helpful for improving metal machinability and achieving better surface-quality.

실시간 절삭 계수 식별 기반의 공구 마모 모니터링 시스템

Among the monitoring technologies in the metal-cutting process, tool wear is the most critical monitoring factor in real machining sites. Extensive studies have been conducted to monitor equipment breakdown in real-time. For example, tool wear prediction studies using cutting force signals and deducting force coefficient values from the cutting process. However, due to many limitations, those wearable monitoring technologies have not been directly adopted in the field. This paper proposes a novel tool wear predictor using the cutting force coefficient with various cutting tools, and its validity evaluates through cutting tests. Tool wear prediction from the cutting force coefficient should conduct in real-time for adoption in real machining sites. Therefore, a real-time calculation algorithm of the cutting force coefficient and a tool wear estimation method proposes, and they compare with actual tool wear in cutting experiments for validation. Validation cutting tests are conducted with carbon steel and titanium, the most commonly used materials in real cutting sites. In future work, validation will be conducted with different materials and cutting tools, considering the application in real machining sites.

Characterization and Evaluation of Engineered Coating Techniques for Different Cutting Tools-Review.

Coatings are now frequently used on cutting tool inserts in the metal production sector due to their better wear resistance and heat barrier effect. Protective hard coatings with a thickness of a few micrometers are created on cutting tools using physical or chemical vapor deposition (PVD, CVD) to increase their application performance. Different coating materials are utilized for a wide range of cutting applications, generally in bi-or multilayer stacks, and typically belong to the material classes of nitrides, carbides, carbonitrides, borides, boronitrides, or oxides. The current study examines typical hard coatings deposited by PVD and CVD in the corresponding material classes. The present state of research is reviewed, and pioneering work on this subject as well as recent results leading to the construction of complete “synthesis–structure–property–application performance” correlations of the different coatings are examined. When compared to uncoated tools, tool coatings prevent direct contact between the workpiece and the tool substrate, altering cutting temperature and machining performance. The purpose of this paper is to examine the effect of cutting-zone temperatures on multilayer coating characteristics during the metal-cutting process. Simplified summary and comparisons of various coating types on cutting tools based on distinct deposition procedures. Furthermore, existing and prospective issues for the hard coating community are discussed.

Loaded and unloaded tooth contact analysis of spiral bevel gears in consideration of misalignments

Bevel gear pairs are employed extensively in transmission systems, such as vehicle transmissions (rear axle drive), aircraft engines/turbines and helicopter gears, to transfer power between non-parallel shafts at high speed or high torque. The most complex form of bevel gear is the spiral bevel gear (SBG). SBG pairs are commonly used in applications that require high load capacity at higher operating speeds than are typically possible with other types of bevel gear. When manufactured in a metal-cutting process, spiral bevel gears can either be produced using single indexing (a face-milling method, which is considered in this study) or continuous indexing (a face-hobbing method). Due to manufacturing imperfections and the flexibility of components, the system might experience misalignments that intensify or exert a destructive effect on the gear vibration, which causes disruption in the stress distribution, thereby decreasing the lifetime of the gearbox. The main purpose of this study is to carry out loaded tooth contact analysis (LTCA) and unloaded tooth contact analysis (UTCA) for an SBG pair in the presence of two types of misalignment, axial and radial misalignment, and represent their effects on the mesh stiffness (MS). To calculate the MS, it is essential to determine the geometrical mismatch between two mating tooth profiles by means of UTCA. To conduct LTCA, three main approaches can be utilised: the finite element method (FEM) and experimental and analytical approaches. Due to the development of software packages during the last decade, Transmission3D-Calyx, an FEM-based software, is used in this study to carry out LTCA and UTCA. Finally, the MS for different misalignment cases is compared to represent the effect of misalignment on the SBG pair.

Surface Roughness Prediction using Empirical Modelling Techniques: - A Review

Optimization of process parameters for minimum surface, along with its prediction and monitoring has long been studied, for it is one of the important indices of machining quality. This study continues to attract several researchers as development of newer work materials, tool materials, machining process, and quest for improved product quality because of increased market competition never cease to end. All the different approaches have a common aim of determining the relationships between the input- machining parameters and output-surface roughness.The empirical- AI based methods have been increasingly used for machining performance prediction due to their ability to acknowledge and address imprecision and uncertainty in the machining process, while learning from the experimental data. In this paper the different empirical AI based techniques are reviewed that employ surface roughness as a response variable for more conventional machining operations like turning, milling. The main purpose of this work is to review and re-evaluate machining process modelling literature related to surface roughness as modelling metal cutting process is highly dynamic in nature and highly interconnected to the technological developments.

Optimization of Plasma Arc Cutting Parameters on Machining of Inconel 718 Superalloy

Nickel‐based super composites are widely applied in the industry. These alloys withstand high thermal debility conditions and give better strength to machine parts in aviation, biomechanical, marine, and vehicle commerce. Nickel‐based alloys have high quality, corrosion resistance, and high heat refusal. Inconel 718 is one such composite extensively utilized in these loading circumstances because of chemical stability, mechanical friction, high thermal corrosion, and high stability. During the cutting procedure, these qualities will bring a lot of processing issues, for example, surface roughness, machining efficiency, and wear of tool. Plasma arc cutting (PAC) is an upsetting metal‐cutting process to perform slicing of hard to cut materials even for complex profiles. The present work analyzes the impact of PAC process factors, for instance, gas pressure (GP), arc current (AC), cutting speed (CS), and stand-off distance (SOD) on assessing the kerf width (KW), kerf taper (KT), and heat-affected zone (HAZ) of Inconel 718 superalloy. This work deliberates about the cutting parameters required for the machining of Inconel 718 to provide least surface roughness and low instrument wear. The experiments conducted to validate the ingenuity of the process are in accordance with the optimal parameter settings necessary for machining purposes. The divergence from actuality has been extremely minimal with a relative error of 4.45% for kerf width and 4.36% for the extent of heat-affected zone postmachining.

Adaptive Control for the Metal Cutting Process

The adaptive control of metal cutting processes is a logical extension of the CNC systems. In CNC systems of metal-cutting processes the machining variables (e.g., the cutting speed and feedrate) are prescribed by the part programmer. The determination of these variables depends on experience and knowledge regarding the workpiece and tool materials, coolant conditions, and other factors.The determination of these operating parameters depends on experience and knowledgeregarding the workpiece and tool materials, coolant conditions, and other factors. By contrast,the main idea in adaptive control is the improvement of the production rate, or the reductionof machining costs, by calculation and setting of the optimal operating parameters duringmachining itself. This calculation is based upon measurements of process variables in real time and is followed by a subsequent on-line adjustment of the machining variables subject to constraints with the objective to optimize the performance of the overall system.The adaptive control is basically a feedback system, in which the operatingparameters automatically adapt themselves to actual condition of the process. AC system formachine tools can be classified into two categories:1.Adaptive control with optimization(ACO);2.Adaptive control with constraints(ACC);ACO refers to systems in which a given performance index (usually an economicfunction) is extremized subject to process and system constraints. With ACC, the machiningparameters are maximized within a prescribed region bounded by process and systemconstraints, such as maximum torque or power. ACC systems, however, do not use aperformance index. In both systems an adaptation strategy is used to vary the operatingparameters in real time cutting progresses. Although there has been considerable research onthe development of ACO systems, few, if any, of these systems are used in practice. The major problems with such systems have been difficulties in defining realistic indexes of performance and the lack of suitable sensors which can reliably measure on-line thenecessary parameters in a production environment. The objective of most AC systems isimprovement in productivity, which is achieved by increasing the metal removal rate (MRR)during rough cutting operations. The increases in productivity range from approximately 20 to 80 percent and clearly depend on the material being machined and the complexity of the part tobe produced.

Implementation of the nonlinear programming algorithm when optimizing the final turning mode

For computer-aided multi-variant design of machining technologies, it is important to optimize the cutting parameters at the final pass in each technological operation. When carrying out designing procedures, there emerge problems relating to the algorithm of choosing the decision-making method, the objective function, and the regions of feasibility at final machining steps. Linear programming is time-consuming for multi-variant and multi-pass machining, if the algorithm is to be clear. It is known that when simulating the optimal metal-cutting process, the optimization criterion and the system of constraints are non-linear. Therefore, a computational algorithm can be made significantly more efficient if it is a non-linear algorithm based on Lagrange multipliers Such approach to design helps simplify automating the computational algorithm for multi-pass single-tool machining with a precision cutting tool (a reamer) This is the method discussed herein.

Role of energy consumption, cutting tool and workpiece materials towards environmentally conscious machining: A comprehensive review

Metal-cutting process deals with the removal of material using the shearing operation with the help of hard cutting tools. Machining operations are famous in the manufacturing sector due to their capability to manufacture tight tolerances and high dimensional accuracy while simultaneously maintaining the cost-effectiveness for higher production levels. As metal-cutting processes consume a great amount of input resources and generate some material-based waste streams, these processes are highly criticized due to their high and negative environmental impacts. Researchers in the metal-cutting sector are currently exploring and benchmarking different activities and best practices to make the cutting operation environment friendly in nature. These eco-friendly practices mainly cover the wide range of activities directly or indirectly associated with the metal-cutting operation. Most of the literature for sustainable metal-cutting activities revolves around the sustainable lubrication techniques to minimize the negative influence of cutting fluids on the environment. However, there is a need to enlarge the assessment domain for the metal-cutting process and other directly and indirectly associated practices such as enhancing sustainability through innovative methods for workpiece and cutting tool materials, and approaches to optimize energy consumption should also be explored. The aim of this article is to explore the role of energy consumption and the influence of workpiece and tool materials towards the sustainability of machining process. The article concludes that sustainability of the machining process can be improved by incorporating different innovative approaches related to the energy and tool–workpiece material consumptions.

A Framework for Integration of Internet of Things with Minimum Quantity Lubrication System

The aim of this paper is to provide a framework for the integration of internet of things with minimum quantity lubrication system during metal-cutting process, focusing to provide cleaner environment to manpower at shop floor. In last decade, minimum quantity lubrication system was studied and implemented effectively to optimize the metal cutting process at shop floor. Minimum quantity lubrication system was found to be most promising technique with respect to technical, economic and environmental aspects. Internet of things was also implemented in various domains of industry & delivered excellent outcomes. The internet of things has reduced production cost, cycle time and provides assistance to machine operator for improvement method insights. Thus, in this paper, prior research work of eminent investigators related to internet of things and minimum quantity lubrication were discussed and analysed. After review, it was found that if internet of things is integrate with minimum quantity lubrication system then it leads to new research area in the field of smart manufacturing. Internet of things-minimum quantity lubrication (IoT-MQL) integration provides a platform to automatic control the effect of cutting temperature generated during metal cutting process, due to which tool life and productivity affects significantly. This paper briefed an evaluation of manufacturing – socio based manual operation of minimum quantity lubrication system and propose scope for integration of it with internet of things for an economic and an environmental viewpoint. This investigation provides an outline of integration of internet of things with minimum quantity lubrication system. Proposed framework can be used to create an architecture based on lab-scale system with usually accessible, small cost electronic devices like sensors. Micro Electro-Mechanical System is the main base for this integrated framework of IoT-MQL system. This integrated framework represent a kind of key thing for empowering the ‘Smart Factory’ revolution.

Minimum Quantity Lubrication System for Metal-Cutting Process: Sustainable Manufacturing Process

Abstract The purpose of this paper is to deliver a review of the implementation of the minimum quantity lubrication (MQL) system for manufacturing method, centring on the application of the MQL during the metal-cutting of workpiece. The application of MQL system was implemented & studied by various eminent investigators in last two decades. Thus, in this paper, experimental investigations of prior research work were discussed and analysed to light on review with significant facts for investigators and industries to optimize the metal-cutting process. During metal-cutting process, previous investigators considered three independent parameters like cutting speed, depth of cut and feed rate. Out of these parameters, feed rate was found to be most influencing parameter for response variables. But, for specific metal-cutting operation specific types of feed rate is required. Hence, the selection of optimum value & type of feed rate for specific machining operation is yet to investigated. This paper explored an evaluation of industry-socio based trial and error approaches and propose scope for improvement from both an economic and an environmental viewpoint. This paper delivers an outline of formerly conducted analysis to propose zones of enhancement in metal-cutting process employing minimum quantity lubrication system

Experimental investigation and optimization of PAC parameters on Monel 400™ superalloy

ABSTRACTNickel-based superalloys are predominantly used to manufacture marine, automotive, and aerospace parts due to its excellent corrosion resistance in acidic environments and high-strength characteristics. Machining of these alloys are extremely difficult through conventional process because of their tendency to quickly work harden and poor thermal conductivity. Plasma arc cutting (PAC) is a disruptive metal-cutting process to perform cutting of difficult to cut materials even for intricate profiles. The present work examines the effect of PAC process variables such as arc current, gas pressure, cutting speed, and stand-off distance on evaluating the surface roughness, kerf width, and micro hardness of Monel 400™ superalloy. Experiments are designed and conducted using Box–Behnken design (BBD) of response surface methodology. The quadratic models are developed and assessed for its performance using analysis of variance (ANOVA). Optimal machining process conditions, cutting speed of 2427.08 mm/min, gas pressure of 3.83 bar, arc current of 45 A, and stand-off distance of 2.14 mm are obtained through multiobjective desirability approach. From the confirmation experiments, the relative error is found to be 2.68% for surface roughness, 4.45% for kerf width, and 4.36% for micro hardness which confirms the feasibility and efficiency of proposed methodology.

On the performance of modified Zerilli-Armstrong constitutive model in simulating the metal-cutting process

The accuracy of prediction made by finite element modeling of machining processes significantly depends on the constitutive model used to describe the material behaviour at typical values of strain, strain rate and temperature encountered in cutting. In this paper a new constitutive relationship is established by modifying the Zerilli-Armstrong model based on the concept of dislocation mechanics. The efficacy of the proposed model has been demonstrated by implementing it as a constitutive law for Inconel 718, a nickel based super alloy. The constitutive data generated by using the distributed primary zone deformation model is utilised for calculating the material constants. The efficacy of the proposed model is validated by using a three-pronged evaluation process. The first evaluation procedure involved comparing flow stress predictions made by the proposed model with data generated by the distributed primary zone deformation model. The second evaluation process involved finite element simulations of the orthogonal machining process with the proposed material model as the constitutive relation. A user material subroutine is used for implementing the proposed constitutive relation into a finite element model of orthogonal machining process through ABAQUS/Explicit platform. Good agreement has been achieved between model predictions and experimental data in simulating chip formation with attendant cutting forces. In the third evaluation process, proposed constitutive law is further validated by comparing its flow stress predictions with the split Hopkinson pressure bar test data available in literature.

Sensorless cutting force estimation for full-closed controlled ball-screw-driven stage

Process monitoring technology has been studied in order to realize higher efficiencies and greater automation of the machining process. The cutting force is widely regarded as being the most valuable physical quantity to be gathered when monitoring a metal-cutting process. However, a practical, wideband, and indirect means of measuring the cutting force has not yet been attained for ball-screw-driven machine tools. In recent years, full-closed ball-screw-driven stages mounting linear encoder have been widely used for high-end machine tools. Considering indirect cutting force estimation using servo information from a full-closed controlled ball-screw-driven stage, three pieces of information are available as servo signals of the feed drive: the motor current command, the rotation angle of the motor, and the displacement of the stage. In this study, a high-precision and wideband sensorless cutting force estimation method was proposed for full-closed controlled ball-screw-driven stages using a multi-encoder-based disturbance observer (MEDOB). The MEDOB was originally proposed for estimating the external force on the load side of flexible robots, and was used for resonance ratio control, which was intended to suppress low-frequency vibration. This study aimed to develop an estimation technique for high-frequency cutting forces that exceed the bandwidth of current control loops for the highly stiff ball-screw-driven stage. The influence of extra phase lag on the control signals was considered in order to apply MEDOB to an actual ball-screw-driven stage. The validity of the proposed method was verified using both an analytical simulation and cutting experiments.

Investigation of the solid lubrication effect of commercial boron-based compounds in end milling

Solid lubricants are environmental friendly (green) because they reduce tool wear, the usage of chemical-based cutting fluids, friction and heat during the manufacturing process. In addition, solid lubricants are reusable and easy to handle. Therefore, the solid lubricants that are required in manufacturing processes are efficient, inexpensive, and easily acquired. The present work investigates the usage of different commercial boron compounds (boric acid, boron oxide, boron pentahydrate, and Etidot-67) as lubricants and their performances regarding surface quality, cutting forces and tool wear while machining AISI 1020 steel using HSS end mills. The performance of boron compounds was studied in comparison with that of dry machining. During the metal-cutting process, constant values of the depth of cut, cutting speed and feed rate were used. In the process of milling, the cutting forces were measured with the dynamometer simultaneously. The results indicate that there is a considerable improvement in the machining performance with commercial boron compounds. As a result of using boric acid as a solid lubricant, tool wear resistance improved, the surface roughness values decreased approximately 20 to 32%, and the values of the cutting forces decreased by approximately 15 to 50% compared with dry end milling.