Advanced Machining Technique Research Articles

Cylinder accuracy analysis of tangential turning of disk-like workpieces with increased cutting speed

Tangential turning, a precision high-speed finishing procedure, is crucial for achieving superior surface quality and dimensional accuracy in cylindrical workpieces. This advanced machining technique leverages tangentially applied cutting forces to minimize tool deflection and vibration, thereby enhancing the surface integrity of the final product. Despite its advantages, tangential turning poses challenges in maintaining cylindrical accuracy, necessitating a thorough investigation of cylindrical error. Cylindrical error, the deviation of the machined surface from a perfect cylinder, significantly impacts the functional performance of precision components. Factors such as tool wear, machine dynamics, and thermal effects can induce these errors, demanding comprehensive studies to optimize process parameters and tool paths. By thoroughly analyzing cylindrical error, manufacturers can refine tangential turning processes, ensuring high precision and consistency in high-speed finishing operations. This research underscores the importance of precision error analysis in advancing manufacturing capabilities and achieving stringent quality standards. Cylindrical accuracy is analyzed using the full factorial experimental design methodology to carry out practical cutting experiments, where the cutting speed, feed, and depth of cut were the altered variables. The cylindricity error, peak maximum departure, their ratio, and coaxiality are measured and analyzed. The main effect analysis and detailed study are elaborated using the determined equation. It is found that decreasing the studied parameters is advisable if increasing cylinder accuracy is needed.

Improvement of drilled holes quality by voice-activated ultrasonic vibration assisted drilling process of different orientation

Ultrasonic drilling enables drilling in difficult-to-machine materials, including ceramics and composites, with greater accuracy and precision. The localized and controlled energy application of ultrasonic frequency minimizes the risk of material fracture, cracks, or delamination. This capability ensures that the drilled hole maintains its intended dimensions, shape, and integrity, resulting in improved hole accuracy and overall drilled hole condition. Ultrasonic drilling is an advanced machining technique that utilizes high-frequency vibrations to improve the drilling process. In this designed voice-activated module, electrical energy has been converted into mechanical vibrations through piezoelectric transducers, generating ultrasonic waves in the range of 20 kHz to 80 kHz. Experiments has been conducted considering different process parameters with the changing different orientations of the emitters-horizontal and vertical positions and comparison was done with no vibration conditions. It has been observed that with the application ultrasonic vibration frequency the surface roughness improved by 45% in horizontal position, 28% in vertical position compared with no vibration conditions-conventional techniques. It has also been observed that the circularity index of the drilled holes also improved by 31% for horizontal and 7.6% for vertical position.

Application of Taguchi Method, ANOVA Analysis, and TOPSIS Technique in Optimization of Process Parameters for Surface Roughness and Material Removal Rate in Electrochemical Machining of Al-SiC MMCs

Objectives: To evaluate the significance of advanced machining techniques, such as EDM, ECM, and USM, in increasing productivity and overcoming challenges associated with outdated Al-SiC MMC machining. To assess the surface roughness, tool wear, and machining cost implications of employing advanced machining methods for Al-SiC MMCs. Methods The parameters studied were voltage (V), feed rate (F), and electrolyte concentration (C) in electrochemical machining (ECM) of Al/15%SiC composites. To optimise process parameters, the Taguchi method for Design of Experiments (DOE) with an L27 orthogonal array was used. Signal responsiveness is optimised using the Taguchi approach. The Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) is used to find optimal machining settings. Findings: The outcome of this research is that the parameters affecting surface roughness and material removal rate are voltage, electrolyte concentration and feed rate. The minimum Surface Roughness achieved by selecting the best combination level is A2, B3, C3 (smaller is better) i.e., voltage 20 V, feed rate (f) 0.4 mm/min., electrolyte concentration (c) 30 g/lit. The maximum Material Removal Rate achieved by selecting the best combination level is A3, B3, C3 (larger-is-better) i.e., voltage 25V, feed rate (f) 0.4 mm/min., electrolyte concentration (c) 30 g/lit. Novelty : In this work, TOPSIS technique paired with Taguchi method is used which is rarely studied by other researchers. TOPSIS technique provides the best optimal solution as compared to other techniques. Keywords: Al-SiC MMCs, ECM, MRR, Ra, Taguchi method, TOPSIS

An Extensive Review of Various Optimization Techniques for Electric Discharge Machining

In this paper, an investigation of wire and electric discharge machining has been provided. Wider possibilities for the creation of composites and sophisticated materials were made possible by advances in machining science. As research in this area continues, more materials with complicated meteorological structures and strong mechanical resistance capabilities are emerging. Because of the exceptional strength, toughness, and hardness of these materials, advanced machining techniques are replacing traditional machining techniques in this industry. One unique type of advanced machining technique used in this research is electrical discharge machining. It has also been discussed how these machining methods might develop in the future. This paper serves as both a research tool and a step in that direction. The best settings for the processes outlined above will aid in boosting diverse sectors' output. The research on non-conventional machining processes with diverse optimisation strategies is presented in this review. The optimisation techniques taken into account for the current work were Taguchi's, artificial neural networks, particle swarm optimisation, response surface approach, grey connection analysis, and genetic algorithm.

Comprehensive review on wire electrical discharge machining: a non-traditional material removal process

A highly advanced thermo-electric machining technique called wire electrical discharge machining (WEDM) can effectively produce parts with varying hardness or complicated designs that have sharp edges and are very difficult to machine using standard machining procedures. This useful technology for the WEDM operation depends on the typical EDM sparking phenomena and makes use of the commonly used non-contact material removal approach. Since its inception, WEDM has developed from a simple approach for creating tools and grown to an outstanding option for creating micro-scale components having the greatest degree of dimensional precision and surface finish characteristics. The WEDM method has endured over time as an efficient and affordable machining alternative that can meet the stringent operating specifications enforced by rapid manufacturing cycles and increasing expense demands. The possibility of wire damage and bent, nevertheless, has severely hindered the process’ maximum potential and decreased the precision as well as effectiveness of the WEDM process. The article examines the wide range of investigations that have been done; from the WEDM through the EDM process’ spin-offs. It describes WEDM investigation that required variables optimization and an assessment of the many influences on machining efficiency and accuracy. Additionally, the research emphasizes adaptive monitoring and control of the process while examining the viability of multiple approaches to control for achieving the ideal machining parameters. Numerous industrial WEDM applications are described with the advancement of hybrid machining techniques. The paper’s conclusion examines these advancements and identifies potential directions for subsequent WEDM research. The investigation on WEDM of metal matrix composites (MMCs) is also reviewed; along with the impacts of various cutting variables like wire feed rate (F), voltage (V), wire tension (WT), and dielectric flow rate on cutting processes outcomes like material removal rate (MRR), kerf width (Kw) and surface roughness (SR). In the present article, future directions for WEDM research were also suggested.

The state‐of‐art review of ultra‐precision machining using text mining: Identification of main themes and recommendations for the future direction

AbstractUltra‐precision machining (UPM), one of the most advanced machining techniques that can produce exact components, significantly impacts the technological community. The significance of UPM attracts the attention of academic and industrial partners. As a result of the rapid development of UPM caused by technological advancement, it is necessary to revisit the current stages and evolution of UPM to sustain and advance this technology. The state of the art in UPM is first investigated systematically in this study by identifying the current four major UPM themes. The UPM thematic network is then built, along with a structural analysis of the network, to determine the interactions between each theme and the primary roles of theme members responsible for the interactions. Furthermore, the “bridge” role is assigned to the specific UPM theme content. On the other hand, Sentiment analysis is conducted to determine how the academic community at UPM feels about the themes for UPM research to focus on those themes with a need for more confidence. Considering the above findings, the future perspective of UPM and suggestions for its advancement are discussed and provided. This study provides a comprehensive understanding and the current state‐of‐the‐art review of UPM technology by a text mining technique to critically analyze its research content, as well as suggestions to enhance UPM development by focusing on its current challenges, thereby assisting academia and institutions in leveraging this technology to benefit society.This article is categorized under: Algorithmic Development > Text Mining Application Areas > Science and Technology Application Areas > Industry Specific Applications

Human Experience in HSM Versus AI in HSM

Abstract High-Speed Machining (HSM) involves the use of advanced machining techniques to cut materials at significantly higher speeds than traditional methods. The comparison between human-operated machining and AI-driven machining can be analyzed in various aspects like we present in the paper below.

Development and solving of optimization model for WEDM of AISI D3 using TLBO algorithm

Manufacturing companies employ advanced machining techniques to create complex and accurate products, which require selecting optimum process parameters to achieve the desired quality and cost-effectiveness. Traditional techniques such as Design of Experiments and Response Surface Methodology optimize locally and may not be sufficient for complex systems. This study aims to optimize the Wire Electrical Discharge Machining process of AISI D3 material using Response Surface Methodology and Teaching and Learning-Based Optimization (TLBO), which can optimize globally. The proposed model can improve the quality and cost-effectiveness of the machining process, making it more suitable for various manufacturing applications.

Optimization of process parameters in wire electrical discharge machining using teaching learning based optimization

The Un-Conventional or Non-Traditional machining process is aimed to produce products at right quality. WEDM (Wire electrode discharge machining) is unconventional advanced machining technique for better accuracy. In WEDM a thin wire is used to remove the material from the work piece through electrical spark. Parameters optimization plays a major role in machining process to achieve better quality. In this paper, a technique TLBO (teacher and learner based optimization) was used to parameters optimization in WEDM process of high speed steel (HSS) plates. Experimental values were taken from Sivanaga Malleswara Rao et al. (2017) article..

Influence of Ceramic Particles Additives on the Mechanical Properties and Machinability of Carbon Fiber/Polymer Composites

Hybrid polymer composites have become the interest of the world, especially in mechanical and electronic applications. Recently, advanced machining techniques such as abrasive water jet machining of hybrid polymer composites have been used to solve many problems including the ability to form complex shapes, high performance, better surface features, and high levels of accuracy. In this study, the effect of ceramic particle (SiC and Al2O3) constituents on the mechanical properties and machinability of the hybrid polymer composites was investigated. The results of mechanical tests showed that an improvement in the tensile and flexural properties appeared using a hybrid polymer constituent (70 wt% Epoxy + 15 wt% CF + 10 wt% Sic + 5 wt% Al2O3). However, this hybrid polymer constituent includes the lowest value of impact strength. Also, the morphological analysis indicated the uniform distribution of particles, the best defect-free surface, and the bonding strength between the reinforcement and the epoxy matrix can be obtained using this constituent which has contributed to the improvement of the mechanical properties. The abrasive water jet automation process was also performed based on the design of experiment (Taguchi L18 design) to study the machinability the hybrid polymer composites in terms of surface roughness, hardness, and kerf width. The analysis of variance concluded that the constituent (70 wt% Epoxy + 15 wt% CF + 10 wt% Sic + 5 wt% Al2O3) has the most influential factor on the machinability of the hybrid polymer composite followed by traverse velocity, and then stand of distance that used during abrasive water jet machining. Moreover, the grey relational analysis was beneficially used to determine the multi-optimization of abrasive water jet machining parameters.

Tribological Properties and Cutting Performance of AlTiN Coatings with Various Geometric Structures

The development of advanced machining techniques requires high-performance tool coatings. To improve the wear resistance and cutting performance of AlTiN coatings, a structure optimization strategy involving bias control and a nano-multilayer architecture strategy is presented. The investigated AlTiN coatings were deposited by cathodic arc evaporation and studied with regard to phase structure, hardness, adhesion, and tribological properties by a combination of X-ray diffraction, nanoindentation, scratch, and ball-on-disk friction tests. A high bias potential (up to −120 V) with enhanced adatom mobility suppressed the formation of the wurtzite structure AlN in AlTiN. In addition, the epitaxial growth of Al0.67Ti0.33N on Al0.5Ti0.5N in the AlTiN nano-multilayer could also promote the single-phase structure. The hardness of AlTiN-based coatings with a dominated cubic structure was 3–4 GPa higher than conventional ones. In addition, the interlayer interfaces in the Al0.67Ti0.33N/Al0.5Ti0.5N multilayer could deflect the cracks and thus improve the fracture toughness. As a consequence, the Al0.67Ti0.33N/Al0.5Ti0.5N multilayer with enhanced mechanical properties obtained the lowest wear rate of 1.1 × 10−5 mm3/N·m and the longest cutting lifetime of 25 min during dry turning the SUS304 stainless steel.

An effect of process parameters during wire cut electrical discharge machining of Inconel 738

In the recent days, super alloys especially nickel based materials are used more than 50% of aerospace gas turbine components such as turbine disc, blades etc., It becomes very hard to shape these materials with the use of traditional machining processes due to its improved strength at higher temperature. To overcome the issues faced during conventional machining, the various advanced machining techniques are tried for machining these super alloys. In the present study, Inconel 738 was cut by wire electrical discharge machining using 0.25 mm diameter copper wire. Demineralized water was used as dielectric fluid between tool and workpiece electrode. During the process, voltage, wire feed rate, time of pulse on and pulse off were adjusted at four different values and totally sixteen slots were cut to analyze the machining characteristics. The machined surfaces were tested for its surface finish, rate of material removal and kerf width. The ANOVA was performed using Minitab software to find out the optimized variables and percentage contribution of each parameter in providing the influencing results. Wire feed rate was the most influencing parameter to have the lowest kerf width. As far as Material removal rate, the four parameters were had the significant impact in increasing the MRR. Voltage is the important process parameter to reduce the surface roughness.

Experimental investigation and optimization of WEDM process for AISI 420 stainless steel

AISI 420 Stainless steel is martensitic steel having sufficient corrosive resistance and outstanding hardness used for making knife blades, shear blades, hand tools, and surgical instruments for the medical industry. For the machining of this kind of high-strength material, WEDM is a popular advanced machining technique for creating items with complex forms and profiles. WEDM of AISI420 stainless steel is accomplished utilizing Zn coated copper wire as an electrode in this study. Machine input control parameters include pulse on time (Ton), pulse off time (Toff), peak current (Ip), and wire feed rate (Wf), whereas measured output response parameters include material removal rate (MRR), Kerf width (KW), and surface roughness (SR). Experiments were constructed using Taguchi L16 orthogonal arrays, and control parameters were optimized using Taguchi-based grey relational analysis (TGRA). Parametric analyses are done for multi-response optimization by obtaining grey relational grade (GRG). It has been found from the ANOVA table that Ton, Toff, Ip, and Wf are having % contributions of 85.67%, 4.38%, 8.47%, and 0.26% respectively. The optimal level of input parameters obtained by Taguchi-based GRA is Ton 125µs, Toff 40µs, Ip 220A, and Wf 8m/min. To validate the results confirmation tests are performed on optimal input parameters.

Multi-objective optimization using grey relational analysis for wire EDM of aluminium matrix composites

The creation of novel materials with high mechanical qualities necessitates the use of advanced machining techniques. Non-conventional machining processes alter the entire manufacturing scenario. Non-conventional machining processes swiftly replace conventional machining processes for obtaining better surface quality and a higher material removal rate. Based on grey relational analysis, this work proposes an efficacious method for optimising wire EDM machining parameters of AMCs with varied performance characteristics. Stir casting was used to make AMCs (413/B4Cp) using B4C of 3%, 6% and 9% by weight as reinforcement and 413 as the matrix material. In this study, performance features MRR and SR are taken into account while optimising input parameters. The experimented GRG is 0.772, while the anticipated value is 0.784. This method helped to improve the WEDM process.

Optimization of electric discharge drilling of Waspaloy using desirability function analysis

Electric discharge drilling (EDD) is a very competent advanced machining technique utilized to fabricate drill holes, but minimum MRR, high TWR, and Ra limit the overall performance of the operation. Achieving precision accuracy holes on superalloys such as Waspaloy is not easy using the traditional machining technique. The investigating effect on responses has been found by conducting EDD experiments under the stipulated range of process parameters. The current, TON, TOFF, TES, and Voltage were chosen as input variables, whereas MRR, TWR, and Ra were selected as output variables. The experimentation was designed based on the Taguchi L16 orthogonal array in which Waspaloy and copper tool electrodes were used for the investigation. The optimization is essential for achieving the maximum performance of EDD. Therefore, in this study, DFA technique was used for the optimizations of EDD of Waspaloy. The optimal parameter settings are determined by using DFA technique. Trial experiments were performed based on optimal settings, improving measured responses positively.

Improving surface integrity when drilling CFRPs and Ti-6Al-4V using sustainable lubricated liquid carbon dioxide

In the quest for decreasing fuel consumption and resulting gas emissions in the aeronautic sector, lightweight materials such as Carbon Fiber Reinforced Polymers (CFRPs) and Ti-6Al-4V alloys are being used. These materials, with excellent weight-to-strength ratios, are widely used for structural applications in aircraft manufacturing. To date, several studies have been published showing that the use of metalworking fluids (MWFs), special tool geometries, or advanced machining techniques is required to ensure a surface quality that meets aerospace component standards. Conventional MWFs pose a number of environmental and worker health hazards and also degrade the mechanical properties of CFRPs due to water absorption in the composite. Therefore, a transition to more environmentally friendly cooling/lubrication techniques that prevent moisture problems in the composite is needed. This research shows that lubricated LCO2 is a viable option to improve the quality of drilled CFRP and titanium aerospace components compared to dry machining, while maintaining clean work areas. The results show that the best combination of tool geometry and cooling conditions for machining both materials is drilling with Brad point drills and lubricated LCO2. Drilling under these conditions resulted in a 90 % improvement in fiber pull-out volume compared to dry machined CFRP holes. In addition, a 33 % reduction in burr height and a 15 % improvement in surface roughness were observed compared to dry drilling of titanium.

INSIGHTS ON ABRASIVE WATER JET MILLING OF BLIND POCKETS

Abrasive water jet (AWJ) machining is one of the advanced machining techniques used in the industries for processing materials that are extremely difficult to machine using conventional machining techniques. Based on the flexibility of AWJ, this process is currently employed for milling blind pockets over different materials. The most frequent method for making blind pockets in AWJ is the controlled depth milling mode. This approach was carried out with the raster tool paths. The quality of the blind pocket surface is influenced by different AWJ parameters such as water jet pressure, traverse speed, step-over distance, abrasive flow rate, and abrasive types. Among these, the traverse rate was found to be an influencing factor in most of the AWJ milling operations as it determines the nozzle speed followed by the energy density of the abrasive particle drops while striking across the target material surface, which resulted in a controlled depth of cut. This review paper highlights the performance of the AWJ pocket milling operations with various materials. From these results, it is reported that most of the AWJ milled surfaces were found to be of rough quality even though they were using different milling tool path strategies and parameter conditions. In addition, the milled pocket defects, namely uneven flatness, grit embedment, and undercut were observed. Besides, future research and directions have been addressed in which some of the novel concepts/approaches have been introduced including the scale effect examination in AWJ with the use of different nozzle, orifice, and abrasive sizes. This study will be more helpful to produce blind pockets with tight tolerances and a significant reduction in the process defects. The outcomes of this study will bring new innovations to the AWJ milling technique in order to make a significant footprint in the manufacturing industries for machining quality blind pockets over the target materials.

Performance evaluation and multi-response hybrid optimization of grinding assisted rotary disk ECDM during cutting of Al-6063 SiCp MMC

The Metal Matrix Composites (MMCs) are being used in many applications, including aerospace, shipbuilding, anddefence industries owing to their high strength to weight ratio. However, the machining of these materials is stillchallenging, necessitating advanced machining techniques. The current investigation aimed to analyze the performance ofthe grinding-assisted rotary disc-electrochemical discharge machining (GA-RD-ECDM) process during cutting Al-6063SiCp MMC. Detailed experimentation was performed to study the energy interaction behavior and effect of input processvariables viz. applied voltage, pulse on time, electrolyte concentration, and disc rotation speed on performance measures.The responses selected were taper, overcut (WOC), and Materials Removal Rate (MRR). The experimentation work wasperformed by adopting response surface methodology. Regression models were developed and statistically analyzed throughanalysis of variance (ANOVA). Eventually, the GA-RD-ECDM process was optimized using the VIKOR methodology ofmulti-criteria decision-making by considering accuracy and productivity simultaneously to obtain minimum taper and WOCand maximum MRR. The results of ANOVA revealed that input variables were statistically significant. Applied voltagemost significantly affects the performance of the GA-RD-ECDM process performance. The optimal values of input processvariables obtained by VIKOR method were applied voltage = 100 V, pulse-on time = 3 ms, Electrolyte concentration = 18%wt/vol. and disc rotation speed = 30 rpm. The present work can provide a productive solution for cutting of difficult-to-cutmaterials. Thus, in future, the GA-RD-ECDM process can be investigated for other advanced materials (i.e., glass, polymercomposites and ceramics) for fabrication of microchannels for microfluidic applications.

Machining of composite materials through advance machining process

This study explores those composite materials are difficult to machinate because of their variability, heat sensitivity, and high abrasiveness. This leads to damages to the material and extremely high tool wear and damage to the tool. A thorough overview of advanced machining techniques for composite materials is presented in this article. There is an emphasis on glass and carbon fiber reinforced polymeric composites and long fiber reinforced metal matrix composites in the area of fiber-reinforced composites. Particulate composites cannot be machined in the same way as metal matrix composites, though conventional machining processes due to their advanced properties. As per the previous research we concluded that advance machining process is used to cut hard material such as ceramics, composites, Titanium, etc. It is the opposite of traditional machining when a wedge-shaped tool is used to remove material in the form of chips by causing friction coefficient. These techniques have been used in a number of ways to remove material. One approach is to produce stresses via various methods but not with a well-directed wedge-shaped instrument in the material. Some of the techniques like ultrasonic machining, water jet machining, and abrasive jet machining, to name a few of them. The thermal effect may also be used to dissolve or evaporate the materials. Successful and cheap, advanced machining techniques are finding application in sectors.

A Fuzzy Logic Model for the Analysis of Ultrasonic Vibration Assisted Turning and Conventional Turning of Ti-Based Alloy.

Titanium and its alloys are largely used in various applications due its prominent mechanical properties. However, the machining of titanium alloys is associated with assured challenges, including high-strength, low thermal conductivity, and long chips produced in conventional machining processes, which result in its poor machinability. Advanced and new machining techniques have been used to improve the machinability of these alloys. Ultrasonic vibration assisted turning (UVAT) is one of these progressive machining techniques, where vibrations are imposed on the cutting insert, and this process has shown considerable improvement in terms of the machinability of hard-to-cut alloys. Therefore, selecting the right cutting parameters for conventional and assisted machining processes is critical for obtaining the anticipated dimensional accuracy and improved surface roughness of Ti-alloys. Hence, fuzzy-based algorithms were developed for the ultrasonic vibration assisted turning (UVAT) and conventional turning (CT) of the Ti-6Al7Zr3Nb4Mo0.9Nd alloy to predict the maximum process zone temperature, cutting forces, surface roughness, shear angle, and chip compression ratio for the selected range of input parameters (speed and depth-of-cut). The fuzzy-measured values were found to be in good agreement with the experimental values, indicating that the created models can be utilized to accurately predict the studied machining output parameters in CT and UVAT processes. The studied alloy resulted in discontinued chips in both the CT and UVAT processes. The achieved results also demonstrated a significant decline in the cutting forces and improvements in the surface quality in the UVAT process. Furthermore, the chip discontinuity is enhanced by the UVAT process due to the higher process zone temperature and the micro-impact imposed by the cutting tool on the workpiece.