Conventional Machining Operations Research Articles

Machine learning for multi-dimensional performance optimization and predictive modelling of nanopowder-mixed electric discharge machining (EDM)

AbstractAluminium 6061 (Al6061) is a widely used material for various industrial applications due to low density and high strength. Nevertheless, the conventional machining operations are not the best choice for the machining purposes. Therefore, amongst all the non-conventional machining operations, electric discharge machining (EDM) is opted to carry out the research due to its wide ability to cut the materials. But the high electrode wear rate (EWR) and high dimensional inaccuracy or overcut (OC) of EDM limit its usage. Consequently, nanopowder is added to the dielectric medium to address the abovementioned issues. Nanopowder mixed EDM (NPMEDM) process is a complex process in terms of performance predictability for different materials. Similarly, the interactions between the process parameters such as peak current (Ip), spark voltage (Sv), pulse on time (Pon) and powder concentration (Cp) in dielectric enhance the parametric sensitivity. In addition, the cryogenic treatment (CT) of electrodes makes the process complex limiting conventional simulation approaches for modelling inter-relationships. An alternative approach requires experimental exploration and systematic investigation to model EWR and overcutting problems of EDM. Thus, artificial neural networks (ANNs) are used for predictive modelling of the process which are integrated with multi-objective genetic algorithm (MOGA) for parametric optimization. The approach uses experimental data based on response surface methodology (RSM) design of experiments. Moreover, the process physics is thoroughly discussed with parametric effect analysis supported with evidence of microscopic images, scanning electron microscopy (SEM) and 3D surface topographic images. Based on multi-dimensional optimization results, the NT brass electrode showed an improvement of 65.02% in EWR and 59.73% in OC using deionized water. However, CT brass electrode showed 78.41% reduction in EWR and 67.79% improved dimensional accuracy in deionized water. In addition to that, CT brass electrode gave 27.69% less EWR and 81.40% improved OC in deionized water compared to kerosene oil.

State-of-the-art review of applications of image processing techniques for tool condition monitoring on conventional machining processes

AbstractIn conventional machining, one of the main tasks is to ensure that the required dimensional accuracy and the desired surface quality of a part or product meet the customer needs. The successful accomplishment of these parameters in milling, turning, milling, drilling, grinding and other conventional machining operations directly depends on the current level of tool wear and cutting edge conditions. One of the proven non-contact methods of tool condition monitoring (TCM) is measuring systems based on image processing technologies that allow assessing the current state of the machined surface and the quantitative indicators of tool wear. This review article discusses image processing for tool monitoring in the conventional machining domain. For the first time, a comprehensive review of the application of image processing techniques for tool condition monitoring in conventional machining processes is provided for both direct and indirect measurement methods. Here we consider both applications of image processing in conventional machining processes, for the analysis of the tool cutting edge and for the control of surface images after machining. It also discusses the predominance, limitations and perspectives on the application of imaging systems as a tool for controlling machining processes. The perspectives and trends in the development of image processing in Industry 4.0, namely artificial intelligence, smart manufacturing, the internet of things and big data, were also elaborated and analysed.

Evaluating Surface Quality of Inconel 617 by Employing Deep Cryogenically Treated Electrodes in Surfactant-Added Dielectrics of Transformer Oil

Over the past few decades, better surface quality has remained of great interest to researchers. It deteriorates the fatigue life of the workpiece. The criticality arises when a material of greater strength is selected to work in high-temperature areas such as nickel (Ni)-based superalloys, categorically Inconel 617. Conventional machining operations are not the best choice for the machining of this alloy because of its low density and greater strength. Therefore, electric discharge machining (EDM) is generally engaged. Still, there is a great necessity to make a more reliable surface using EDM, which performs better even in harsh working areas. Therefore, this study examined the potential of deep-cryogenically treated electrodes under the modified dielectrics of transformer oil in the said context, which has not been discussed so far. A set of 30 experiments was performed, designed using the full factorial technique. Deep-cryogenically treated electrodes provided better surface quality in comparison to the non-treated electrodes. Amongst the deep-cryogenically treated electrodes, brass performed outstandingly and provided the lowest value of surface roughness (SR), 6.65 µm, in the modified dielectric of transformer oil with Span 80. The surface finish of deep-cryogenically treated brass is 28.72% better compared to the average value of the overall deep-cryogenically treated electrodes. The lowest value of SR (8.35 µm) was gained by engaging a non-cryogenically treated Cu electrode with a T-20–transformer oil-modified dielectric. The said value of SR is 17.7% better than the highest value of SR achieved in the case of S-80–transformer oil with a non-cryogenically treated Cu electrode.

Modelling of a shear-type piezoelectric actuator for AFM-based vibration-assisted nanomachining

Recent research investigations have reported the benefit of enhancing conventional AFM-based nanoscale machining operations by the introduction of high frequency vibrations between the AFM tip and the processed material. The technique relies on piezoelectric actuation and is relatively straight forward to implement in practice. However, the non-linearity of piezoelectric actuators when operated under high electric field and frequency conditions can affect the dimensional accuracy of the fabricated nanostructures. To address these issues, the paper reports a method based on coupled mechanical-electrical Finite Element (FE) modelling to predict the relative motion between an AFM tip and a workpiece for vibration-assisted AFM-based nanomachining applications. In particular, the novelty of the proposed method is that it combines two classical approaches for modelling the nonlinear behaviour of piezoelectric materials. More specifically, two sources of non-linearity are considered simultaneously by combining the field-dependant model from Muller and Zhang with the frequency-dependant model from Damjanovic. The resulting combined model is employed to establish the piezoelectric constitutive equations implemented in the developed coupled field FE model. A further distinguishing characteristic of the work is that the proposed approach was subsequently validated by comparing the predicted widths of nanoscale grooves against those machined with a custom AFM-based vibration-assisted nanomachining configuration.

Flat-end mill machining analysis of processed CrMnFeCoNi high-entropy alloys

ABSTRACT High-entropy alloys are emerging materials and are widely studied at the synthesis and characterization levels. Their machinability study and product realization are still at a nascent stage. Conventional machining operations are necessary to ensure part assembly and surface quality. Hence, end-mill machining is carried out to check the machinability of the most ductile equiatomic and non-equiatomic CrMnFeCoNi high-entropy alloy (HEA) with a green manufacturing concept. Theoretical and experimental analyses examined the effect of percent composition of an element in a high-entropy alloy and machining parameters (spindle speed, depth of cut and feed per tooth) on the cutting forces, chip morphology, machined surface topography, surface micro-hardness and tool wear mechanism. Kistler dynamometer installed in CNC vertical milling machine is used with AlTiN-coated tungsten carbide tool to record the cutting forces and moments. The microstructure anisotropy induced by low vacuum induction melting of varying compositions of elements in high-entropy alloys influenced the machining results. Feed force values were higher for the non-equiatomic HEA sample than for the equiatomic CrMnFeCoNi HEA. SEM and EDS mapping has revealed microhole and microcrack surfaces after machining. Equiatomic CrMnFeCoNi HEA has shown the highest microhardness of 984 Hv than the non-equiatomic HEA sample.

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.

State of the art review on the sustainable dry machining of advanced materials for multifaceted engineering applications: progressive advancements and directions for future prospects

In this article, the comprehensive review on the application, and indeed, a comparative analysis on dry machining of different types of materials (Inconel, steel, aluminum, cast iron, magnesium and advanced materials) used in machining (turning, drilling and milling operations) were carried out in the light of utmost works published in the literature. The work describes the scientific findings of the past twenty years, including sustainable methods (surface texture, solid lubricants, vibration-assisted machining, laser-assisted machining), tool coatings, and geometry of tools. Vibration-assisted machining is another direction that researchers have investigated without the use of cutting coolants, where the complete disposal of coolants is not possible. Various researchers have carried out rigorous experimental work on milling, drilling, and turning operations under dry conditions to machine numerous materials. A significant proportion of experimental data about tool wear, tool wear machining, surface quality, surface integrity, etc, has been analyzed under dry conditions. However, the critical analysis of dry machining for different conventional machining operations for a variety of industrial materials is still lacking for establishing dry machining as a sustainable process for industrial applications. Thus, the critical analysis of various machining parameters and their consequences on tool wear and the surface quality of machined work was carried out in this work. Finally, scientific recommendations based on critical findings were proposed for industrial implementation of dry machining.

Machining Character Analysis of Coated and Uncoated End Mill on Heat Treated C45 Steel

Abstract: Machining operations are used to produce shapes or surface characteristics for a product. Some common conventional machining operations are turning, boring, drilling, reaming, milling, and tapping. Conditions for machining operations were chosen based on geometry and surface finish requirements rather than profit when costs were comparatively low on labor, resource, machines, and tools. However, nowadays, many researchers proposed optimizing machining parameters to maximize profit when using expensive modern machine tools. The purpose of machining operations is to make specific shapes or surface characteristics for a product. Conditions for machining operations were traditionally selected based on geometry and surface finish requirements. This study was investigated the parameter optimization of end milling operation various parameter and coated tools and ordinary tool with heat treated C45 steel with single objective function criteria based on the Taguchi orthogonal array with the Taguchi design. Comparison of coated and uncoated end mill process of heat-treated C-45 steel fine Ra is obtained with coated tool. Kerf width almost equal of both tools it did not show any major difference Optimum level and ANOVA were calculated for both tools. Keywords: Ra, PVD coated, Heat treatment, End mill

Secondary Processing of Aramid with AWJ and Optimization with NSGA-III

The secondary operations of composite parts are performed following thermal cure processes, which generate the final dimensions with desired tolerance and quality specifications. High-strength composites, on the other hand, especially aramid fiber-reinforced polymers (AFRP), are not suitable for conventional machining operations due in part to high operational costs and limited surface quality characterized by fuzziness and delamination. Abrasive Water Jet (AWJ) has been recently shown promising results in obtaining improved surface quality while ensuring significant cost advantages. This study investigates the AWJ processing of AFRP by implementing the analysis of variance and response surface methods. The effects of the control parameters (sand ratio, pressure, stand-off-distance, and feed rate) on the surface quality metrics (surface roughness, kerf angle, and dimensional error) are identified and comparatively evaluated. The surface quality of the AWJ processed AFRP specimens are investigated using Scanning Electron Microscopy (SEM). The trade-offs between the measured tolerances and surface roughness values are identified via a new genetic algorithm approach: Non-dominated Sorting Genetic Algorithm (NSGA-III). Also, operation regions are determined using the generated Pareto curves while improving the quality of various features of an AFRP component, critical to its functional performance during extended service life. As a result, the lowest Ra values obtained were 4.135 µm for trimming, 5.962 µm for pocketing, and 4.696 µm for the hole-making operation. The maximum error in the accuracy of operating regions yields to 7% with independent measurements for validation.

Unconventional milling of zirconia-based bioceramic material with nanosecond pulsed laser

Fabrication of dental restorations made of zirconia-based biomaterials with enhanced mechanical and tribological properties together with customized surface topography and microstructure for promoting enamel adhesion and cell proliferation while hindering bacterial spreading is a very challenging task to accomplish through conventional machining operations. In fact, traditional milling processes of sintered ceramics are typically labor-intensive, therefore expensive and time-consuming, and these aspects can be further exasperated when microsized features are required. On the other hand, unconventional techniques such as laser milling can represent a suitable solution to produce miniaturized individualized structures on advanced ceramics since it is a non-contact thermal process that ensures the elimination of cutting forces and allows hard and brittle materials to be machined without the need for special equipment which requires high investments and long processing times. In this context, this study aims to investigate the capability of a nanosecond pulsed fiber laser to machine samples made of yttria-stabilized zirconia through a systematic experimental approach in order to identify the most suitable process operational parameters combinations that ensure the obtainment of specific surface topographies while minimizing the machining time. The milling process is carried out by using a 30 W Q-switched Yb:YAG fiber laser by controlling laser beam scan speed, scan strategy and hatch distance and following a multi-level factorial design-based experimentation. The adoption of the laser technology to machine yttria-stabilized zirconia results in a high-repeatable, accurate and time-saving process allowing easy control of the process outcomes.

Investigation of the Effect of Wire Electrical Discharge Machining on the Fracture Toughness of Aluminum-Boron Carbide Composite

Aluminum metal matrix composites reinforced by ceramic particles have a wide acceptance in engineering applications due to their mechanical and physical properties. One of the major challenges in machining these composites by the conventional machining operations is the presence of the abrasive particles, which affects the tool life and the required surface finish. Electro discharge machining process is widely used instead of conventional methods to overcome these challenges. Therefore, it is essential to study the influence of the electro-discharge machining on its fracture toughness, as it is the most important structural integrity indicator in the wide range applications of the studied composites. In this work, all samples were prepared by the stir casting method with using a squeezing pressure during the solidification. Samples were reinforced by (0, 2, 4, and 6wt %) of B4C particles with a size of 0.387μm. The fracture toughness studied were based on the stress intensity factor, determined experimentally by using compact tensile test and numerically using the finite element method. The fracture toughness improvement was recorded for the samples containing 4wt% of B4C.

Mathematical modeling of cutting layer geometry and cutting force in orthogonal turn-milling

Abstract Orthogonal turn-milling is a highly efficient and precise cutting technology by combining low-speed rotation of the workpiece, high-speed rotation of the cutter, and moving the cutter along the workpiece. The technology is widely used in aeronautics and astronautics industries to cut various hard-to-machine materials. Orthogonal turn-milling involves more motions than conventional machining operations, for instance turning and milling, and therefore, it is difficult to set the optimum cutting parameters. Cutting force prediction based on cutting layer geometry can be used to optimize cutting parameters in orthogonal turn-milling. However, the cutting layer geometry in orthogonal turn-milling is not well understood. In this work, a method is proposed for assessing different types of cutting layer geometries in orthogonal turn-milling. Each geometry of cutting layer is modelled analytically, which leads to a mathematical model of the corresponding cutting force. The models are validated by cutting experiments. Finally, the cutter wear experiments validate the trends of cutting forces corresponding to the different cutting layer geometries. The present models offer a theoretical guidance for efficient machining strategies in orthogonal turn-milling.

An Investigation on Turning of Hard Steel using Coated Carbide Inserts

Employing conventional machining operations in material removal type manufacturing processes for processing difficult-to-machine hard materials through some ways and means is the focus of research by machining research groups across the globe since long. This gives considerable advantages over the grinding process in terms of higher material removal rate, better surface integrity of the work surface, etc., although grinding is commonly used for material removal of quite hard materials along with their finishing. In this paper, machinability of hard AISI 4340 steel is explored employing groove-type chip breaking coated carbide inserts under various cutting velocity and feed at dry condition. Hardened AISI 4340 is considered to be a difficult-to-machine material, and hence, recommendable machining conditions need to be found out. Favourable flat continuous chip is acquired at a cutting velocity of 231 m/min and at a feed of 0.08 mm/rev. At 391 m/min cutting velocity, cutting edges are detected to have worn-out quite fast.

An outlook on the sustainable machining aspects of minimum quantity lubrication during processing of difficult to cut materials

Modern machining scenario is facing intense pressure to adopt sustainable machining to fulfill the demand of future energy need without compromising the reserve of conventional energy resources. The water crisis, energy deficit, global warming and profitability have generated the need of handsome debate on sustainable manufacturing in present scenario of industry 4.0. The technological development have raised the comfort level of living being with context to transportation, telecommunication and medical facilities as a result of processing harder grade materials utilizing conventional and modern machining operations. However, during processing of aforementioned materials the advanced level of process parameters require higher energy, consequently, resulted into elevated cutting temperature leading to poor product quality as well as uneconomical machining. Hence to lower the excessive cutting temperature the metal working fluids are utilized to absorb the heat evolved at different zones of machining operation. Consequently, the temperature get reduced, but raises the scarcity of negative effects such as skin rashes, itching, asthma, water pollution, soil pollution, mist generation and sometimes unprofitable conditions. So, to bridge the gap between the limitations of dry machining and conventional flood lubrication, the concept of minimum quantity lubrication has been exercised to achieve the challenges and goals of sustainable machining. In this papers, the sustainable machining aspects of minimum quantity lubrication has been while processing the titanium, Inconel, magnesium and other ferrous alloys which are widely used. The Investigation indicated that the sustainable machining is dominant in present era of machining employing minimum quantity lubrication, cryogenic cooling and other hybrid cooling methodologies. Furthermore, several technological advancements, such as UAG, ECT, UAM and LAM have been reported to ease conventional machining operations during processing of harder grades materials.

Dry machining of Inconel 718 super alloys using uncoated tool: Experimental and numerical analysis

Aerospace super alloy Inconel 718 is difficult to process through conventional machining operation. Alloys with high strength at high temperatures and high strain hardening, high chemical affinity (towards tool material, and Co binder) etc. impose adverse effects towards smooth machining. Poor thermal conductivity of Inconel 718 promotes excessive temperature rise at the chip-tool interface which causes rapid tool wear, and degraded surface integrity of the end product. Adequate understanding of machining process phenomena along with precise control of machining parameters may yield satisfactory result. Trial, and error experimentation is indeed uneconomical; hence, in the present reporting, Finite Element (FE) based numerical simulation is attempted to model machining responses in the extent of cutting force, tool-tip temperature, depth of flank wear progression, chip-tool contact length, and finally, chip reduction coefficient. Simulation results are verified through experimental tests. Simulation results are found in good agreement with experimental results. Therefore, simulation results can reliably be used as an alternative instead of actual experimental effort.

3D Finite Element Analysis of milling process for non-ferrous metal using deform-3D

Milling is one of the most important conventional machining operations used in Industry. The milling operation is influenced by many parameters. This paper deals with the acquirement and comparison of surface roughness values obtained during milling operation done on aluminum with the simulated values through FEA. The material was chosen bacause of its importance in industry and its susceptibility to degradation through surface. The parameter chosen were speed, feed and depth of cut. Material selected for the tool is carbide (15% cobalt), having tensile strength of about 400 N/mm2. Finite Element Analysis using DEFORM 3D software is done on the milling operation by varying the parameters of mill cutter on the work piece, roughness values are obtained during each individual process. The material is defined in software by using John-cook’s equation. The same procedure is done in real time for the same processing conditions used in software on a CNC vertical milling machine.

Analysis of the surface integrity induced by face milling of Laser Metal Deposited Ti-6Al-4V

The Laser Metal Deposition (LMD) is an additive manufacturing process which is gaining good competence in manufacturing and repairing complex functional parts. However, the produced parts require conventional machining operations in order to enhance the surface quality and the material properties. Due to the highly localized heat input experienced by the sample during the building process, significant variation of the local material properties can appear within the produced components. This could affect the machinability of the parts produced by the LMD process. This study aims to investigate the milling process and its effect on the resulted surface integrity of Ti-6Al-4V components produced by the LMD process. The heat treatment was performed in order to homogenize the microstructure of the material. The conventional Ti-6Al-4V was taken as a reference material sample. Depending on the cutting process parameters, the cutting forces and the surface roughness of the machined LMD parts were 10-40% and 18-65% respectively higher than the conventional samples. The compressive residual stress in the machined LMD samples were 11-30 % higher than the conventional specimen. These differences are related to microstructure and grain size differences between the tested parts.

Ambient Acoustic Energy Harvesting using Two Connected Resonators with Piezoelement for Wireless Distributed Sensor Network

In this article, an acoustic energy harvester (AEH) is conceptualized, designed, fabricated and tested. The developed AEH (DAEH) consists of two Helmholtz cavities (HCs) and a commercially available piezoelement. The HCs were fabricated from Teflon material using conventional machining operations. An indigenous test bench for in-lab characterization of DAEH has also been developed. Various experiments were performed to experimentally record the frequency response function, loading and power characteristics. Additionally, the in-lab and open-air characterization of the DAEH is also reported. Furthermore, the proposed prototype of DAEH is compared on the basis of various benchmarks with the prototypes available in the literature. The experimental results indicate a maximum power density of 32.7 μW/cm3 at 130 dB.

Exploring the contribution of unconventional parameters on spark gap formation and its minimization during WEDM of layered composite

Cladded materials are heterogenous in nature and considered as difficult-to-cut especially via conventional machining operations. Gas and/or plasma cutting are common in practice to cut clad materials. However, these processes induce deeper heat-affected zones and provide very rough surface integrity. Wire electric discharge machining (WEDM) is a capable alternate yielding better cut quality. Formation of a significant spark gap between the cut surfaces is the iconic problem of WEDM which is addressed in this study. WEDM has been performed on stainless-clad steel with a focus on identifying the significant parameters affecting the amount of spark gap and its minimization in the final cut. Eight input control factors, namely workpiece orientation, thickness of individual layer, servo voltage, pulse on-time, wire diameter, wire feed, and pressure ratio, have been employed to investigate their effects on spark gap development. Experimentation has been performed according to L18 orthogonal array followed by comprehensive statistical analyses. ANOVA shows that wire diameter and pressure ratio are the two main influential parameters for spark gap having percentage contribution of 71% and 16%, respectively. Optimal settings of control variables are also achieved through S/N ratio analysis. Improvement of 23.4% towards spark gap reduction is realized.

WED-machining characteristics of Ti6Al4V alloy based on central composite design

The paper presents the optimisation of process parameters during wire electrode discharge machining (WEDM) of Ti6Al4V (grade 5) alloy using the response surface methodology (RSM) and desirability approach, as unique set of properties of Ti6Al4V is being increasingly utilised in various industries including biomedical and aerospace. However, due to low thermal conductivity and being highly reactive at elevated temperatures tool wear is a significant problem during conventional machining operations. Hence, WEDM may be a viable alternative in certain applications when machining titanium alloys. In this investigation the effect of WEDM process parameters such pulse on time, pulse off time, servo voltage and wire feed are evaluated for material removal rate (MRR) and surface roughness. The optimum process parameters were obtained for the selected range of experiments using a desirability approach. Confirmation experiments were conducted to validate the empirical models of MRR and surface roughness that indicated developed models are suitable for predicting the response parameters.