Browse Topic: Nonconventional machining processes

Items (132)
ABSTRACT The armor research and development community needs a more cost-effective, science-based approach to accelerate development of new alloys (and alloys never intended for ballistic protection) for armor applications, especially lightweight armor applications. Currently, the development and deployment of new armor alloys is based on an expert-based, trial-and-error process, which is both time-consuming and costly. This work demonstrates a systematic research approach to accelerate optimization of the thermomechanical processing (TMP) pathway, yielding optimal microstructure and maximum ballistic performance. Proof-of-principle is being performed on titanium alloy, Ti-10V-2Fe-3Al, and utilizes the Hydrawedge® unit of the Gleeble 3800 System (a servo-hydraulic thermomechanical testing device) to quickly evaluate mechanical properties and simulate rolling schedules on small samples. Resulting mechanical property and microstructure data are utilized in an artificial intelligence (AI
Lillo, ThomasChu, HenryAnderson, JeffreyWalleser, JasonBurguess, Victor
Related to traditional engineering materials, magnesium alloy-based composites have the potential for automobile applications and exhibit superior specific mechanical behavior. This study aims to synthesize the magnesium alloy (AZ61) composite configured with 0 wt%, 4 wt%, 8 wt%, and 12 wt% of silicon nitride micron particles, developed through a two-step stir-casting process under an argon environment. The synthesized cast AZ61 alloy matrix and its alloy embedded with 4 wt%, 8 wt%, and 12 wt% of Si3N4 are subjected to an abrasive water jet drilling/machining (AJWM) process under varied input sources such as the diameter of the drill (D), transverse speed rate (v), and composition of AZ61 composite sample. Influences of AJWM input sources on metal removal rate (MRR) and surface roughness (Ra) are calculated for identifying the optimum input source factors to attain the best output responses like maximum MRR and minimum Ra via analysis of variant (ANOVA) Taguchi route with L16 design
Venkatesh, R.
This specification provides processing and acceptance requirements for electrical discharge machining (EDM) when applied to the manufacturing of parts
AMS B Finishes Processes and Fluids Committee
The EN24 and EN42 materials were machined by the electric discharge machine (EDM). The study aimed to optimize the input variables for the multiple outputs, such as metal removal rate (MRR), tool wear rate (TWR), and surface roughness. The machining of the metal is essential to analyze the surface quality and the production rate. The MRR is a prediction of the production rate and surface roughness resembling the quality of the surface. The input variables were current (A), pulse on time (ton), and pulse duty factor (T). The three levels of current were 3A, 6A, and 9A. The ton time was selected as 30 μs, 50 μs, and 70 μs. The pulse duty factors were selected as 4, 5, and 6. The Taguchi optimization techniques are used to optimize process parameters. The L9 orthogonal array was selected for the process. ANOVA analysis was employed to check the rank of the input parameters relative to the output. The maximum MRR were at 9A, 70 μs, and 4 duty factor for the EN24. The best MRR were at 9A
Sahu, Kapil DevSingh, RajnishChauhan, Akhilesh Kumar
This specification covers the engineering requirements for laser beam machining, such as cutting and drilling
AMS B Finishes Processes and Fluids Committee
Have you ever gazed at the vastness of the stars and wondered what else your CNC machine can create? Greg Green had the opportunity to find out when he joined the staff at the Canada-France-Hawaii Telescope (CFHT) in Waimea, Hawaii
With the progress of manufacturing industries being critical for economic development, there is a significant requirement to explore and scrutinize advanced materials, particularly alloy materials, to facilitate the efficient utilization of modern technologies. Lightweight and high-strength materials, such as aluminium alloys, are extensively suggested for various applications requiring strength and corrosion resistance, including but not limited to automotive, marine, and high-temperature applications. As a result, there is a significant necessity to examine and evaluate these materials to promote their effective use in the manufacturing sectors. This research paper presents the development of an Artificial Neural Network (ANN) model for Computer Numerical Control (CNC) drilling of AA6061 aluminium alloy with a coated textured tool. The primary aim of the study is to optimize the drilling process and enhance the machinability of the material. The ANN model utilizes spindle speed, feed
Katta, Lakshmi NarasimhamuPasupuleti, ThejasreeNatarajan, ManikandanSiva Rami Reddy, NarapureddySomsole, Lakshmi Narayana
A wide range of engineering domains, such as aeronautical, automobiles, and marine, rely on the use of Metal Matrix Composites (MMC). Due to the excellent properties, such as hardness and strength, Aluminum base MMC are generally adopted in various uses. Due to the increasing number of reinforcement materials being added to the MMC, its properties are expected to improve. In this exploratory analysis, an effort was given to develop a new aluminium-based MMC. The analysis of the machinability of the composite was also performed. The process of creating a new MMC using a stir casting technique was carried out. It resulted in a better and more reinforced composite than its base materials. The reinforcement materials were fabricated using different weight combinations and process parameters, such as the temperature and duration required to stir. Due to the improved properties of the composite, the traditional machining method is not feasible for machining of these materials. Wire Electro
Natarajan, ManikandanPasupuleti, ThejasreeKumar, VKiruthika, JothiSilambarasan, RKrishnamachary, PC
Electrical steel, also known as silicon steel, is a ferromagnetic material that is often used in electric vehicles (EVs) for stator and rotor applications. Since the design and manufacturing of rotors require the use of laminated thin electrical steel sheets, the fatigue characterization of these single sheets is of interest. In this study, a 0.27mm thick non-oriented electrical steel sheet was tested under cyclic loading in the load-controlled mode with the load ratio R = 0.1 at room temperature. The specimens were prepared using the Computer Numerical Control (CNC) machining method. The Smith-Watson-Topper mean stress correction was used to find the equivalent fully reversed stress-life (S-N) curve. The Basquin equation was used to describe the fatigue strength of the electrical steel and the fatigue parameters were extracted. Furthermore, a design curve with a reliability of 90% and a confidence level of 90% was generated using Owen’s Tolerance Limit method. The fracture mechanisms
Tolofari, Tamuno-IbimBehravesh, BehzadSaha, DulalChen, JimMills, MarieZhang, WenshengLamonaca, GianniJahed, Hamid
Strict environmental regulations are driving the automotive industry toward electric vehicles as they offer zero emissions. A key component in electric vehicles is the electric motor, where the stator and rotor are manufactured from stacks of thin electrical steel sheets. The electrical steel sheets can be cut in different ways, and the cutting methods may significantly affect the fatigue strength of the component. It is important to understand the effect of the cutting processes on the fatigue properties of electrical steel to ensure there is no premature failure of the electric motor resulting from an improper cutting process. This investigation compared the effect of three different edge preparation methods (stamping, CNC machining, and waterjet cutting) on the fatigue performance of 0.27mm thick electrical steel sheets. To investigate the effect of the edge finish on fatigue behavior, surface roughness was measured for these different samples. It was determined that the CNC
Gill, GurmeetBehravesh, BehzadSaha, DulalZhang, WenshengChen, JimLamonaca, GianniMills, MarieJahed, Hamid
A comprehensive literature review of the optimization techniques used for the process parameter optimization of Abrasive Jet Machining (AJM), Ultrasonic Machining (USM), Laser Beam Machining (LBM), Electrochemical Machining (ECM), and Plasma Arc Machining (PAM) are presented in this review article. This review article is an extension of the review work carried out by previous researchers for the process parameter optimization of non-traditional machining processes using various advanced optimization algorithms. The review period considered for the same is from 2012 to 2022. The prime motive of this review article is to find out the sanguine effects of various optimization techniques used for the optimization of various considered objectives of selected non-traditional machining processes in addition to deemed materials and foremost process parameters. It is found that most of the researchers have more inclination towards the minimization of Surface Roughness (SR) compared to the
Pandey, Arun Kumar SriramSaroj, AnkitSrivastava, Anshuman
The use of planetary gearboxes in heavy-duty industries is dominant due to their compact size, large transmission ratio and torque delivery capability with different configurations. Due to their harsh operating conditions, localised gear tooth faults such as cracking and chipping are more common in such gearboxes. Furthermore, localised gear tooth failure initiates distributed gear faults such as pitting and wear on the gear tooth. Therefore, it is necessary to monitor such localised gear faults continuously and detect them at an early stage to prevent sudden and catastrophic failure. In this study, gear tooth localised defects on various gear elements of the planetary gearbox are seeded using Electrical Discharge Machine (EDM). Then the vibration signals from the gearbox are captured. Afterwards, a decision tree algorithm selects the most prominent statistical features from many extracted features. Further, to automate the fault detection process, the k-nearest neighbours (k-NN
Syed, Shaul HameedV, MuralidharanD, Pradeep KumarS PhD, Ravikumar
The numerous applications and desirable attributes of Monel 400 urge many researchers to undertake multiple systematic evaluation studies for diverse manufacturing operations. Because of their exceptional mechanical qualities and great corrosion resistance, nickel-based alloys, particularly Monel 400, are increasing in popularity in a variety of applications. Because of their tendency for rapid work hardening and low thermal conductivity, these materials are particularly difficult to machine using traditional manufacturing techniques. Advanced material removal methodologies have been applied to eliminate such drawbacks and are regarded as a suitable alternative approach to traditional machining processes. Based on the Electrical Discharge Machining technique, Wire Electrical Discharge Machining was developed, which a sophisticated machining technology is used to machine hard materials with complex forms in any electrically conducting materials. The machinability performance of Monel
Natarajan, ManikandanPasupuleti, Thejasree
The research aims to optimize the surface roughness, material removal rate (MRR), tool wear, and spark gap for input machining parameters such as Pulse on-off time and wire feed rate. The experiment results of WEDM of Duplex stainless steel are optimized by ANOVA and Response surface methodology (RSM) approach. Taguchi’s orthogonal array L9 (3*3) was used to design the test condition for the experiment. After the model validation, ANOVA was used to identify the most significant input factor on the output. Response surface methodology was used to find the ideal cutting conditions which produce the best-desired output in terms of less tool wear, lower surface roughness, lower spark gap, and higher material removal rate. The optimal MRR, Spark Gap, surface roughness, and tool wear parameters for Duplex Stainless Steel are obtained at Pulse on 110.23, Pulse off time of 56.0, and a wire feed rate of 1.0. The proposed RSM model is significant and suited for all machining conditions due to
A Modi, VinayakGovindasamy, RajamuruganKrishnasamy, PrabuKumar, PrashantRaju, Sasikumar
Stainless Steel 304 (SS304) is a nickel–chromium–based alloy that is regularly used in valves, refrigeration components, evaporators, and cryogenic containers due to its greater corrosion resistance, high ductility, and non-magnetic properties, as well as good weldability and formability. Multiple regression analysis was used to establish empirical relationships between process variables. Additionally, the established regression equations are employed to predict and compare experimental data. Due to the increasing demands for high-quality surface finishes and complex geometries, traditional methods are being replaced by non-conventional techniques such as wire EDM. This process, which emerged from the electrical discharge machining concept, mainly involves creating intricate components. WEDM results in a high degree of precision and excellent surface quality. Due to the complexity of WEDM, the processing parameters cannot be selected by using the trial-and-error method. The various
Natarajan, ManikandanPasupuleti, ThejasreeSilambarasan, RR, RameshKatta, Lakshmi Narasimhamu
The advanced lifestyle demands materials that are light and robust, and aluminum and its alloys are commonly used in various engineering components due to their exceptional properties such as light weight, enhanced strength, and being economically affordable. Due to their superior mechanical properties, such as strength and flexibility, are commonly used in various industrial applications. Metal Matrix Composites (MMCs) are very essential materials used in several applications as they are more robust and harder than any conventional material. In this study, a metal matrix composite made of aluminum and Boron Nitride (BN) is investigated to analyze its various properties. The study is performed by using Wire Electrical Discharge Machining (WEDM). The three independent parameters of the composite are its pulse on time, peak current, and pulse off time. The study aims to analyze the effects of various process variables on the desired performance of the metal matrix composite. Through
Naidu, B Vishnu VardhanaNatarajan, ManikandanR, RameshSOMSOLE, Lakshmi NarayanaPasupuleti, Thejasree
California-based 3DEO unveiled in February its new metal 3D printing platform and patented technology, Saffron. The proprietary platform has been in development for the past five years. “Until now, we have revealed very little about our patented technology, and for good reason - we felt we had a tiger by the tail and wanted to gain as much advantage as possible,” said Matt Sand, 3DEO's co-founder and president. Using a hybrid additive manufacturing (AM) process that leverages binder jetting and CNC machining, the next-generation printer achieves superior results in terms of surface finish, material properties and dimensional accuracy, Sand said. The build area is 81 sq. in. (523 sq. cm), covered by eight spindles operating at 60,000 rpm with micron-level positional accuracy. Depending on part geometry or print speed required, the printer can automatically vary layer thickness anywhere from 50 to 500 microns
Gehm, Ryan
The impact of Laser Beam Machining (LBM) process parameters on Surface Roughness (SR) and kerf width during machining is investigated in this work. Stainless Steel is a material that is resistant to corrosion. LBM is a nontraditional machining method in which material is removed by melting and vaporizing metal when a laser beam collides with the metal surface. There are numerous process variables that influence the quality of the LBM-cut machined surface. However, the most essential factors are laser power, cutting speed, assist gas pressure, nozzle distance, focus length, pulse frequency, and pulse width. SR, Material Removal Rate (MRR), and kerf width and heat affected zone are significant performance indicators in LBM. The influence of LBM process parameters on SR and kerf width while machining stainless steel material is investigated in this study. Experiments are carried out using the L27 orthogonal array by varying laser power, cutting speed, and assisting gas pressure for
Rahman, AbdulChatterjee, PrasunMondal, Raj ShekharHusain, Md Murtuja
During aircraft wing assembly, machined fiberglass shims are often used between mating parts to compensate for inherent geometric variability due to manufacturing. At present, fiberglass shims for large aerospace structures, such as shims attached to wing ribs, are manufactured either manually or by precision machining, both of which pose a challenge due to tight tolerance requirements and wide geometric variations in the aircraft structures. Relative to articulated arm industrial robots, gantry-style computer numerical control (CNC) machines are costly, consume large footprints, and are inflexible in the application. Therefore, industrial robots are viewed as potential candidates to replace these gantry systems to facilitate metrology, shim machining, and permanent joining of aircraft structure, with all these processes taking place in the assembly process step. However, the accuracy of articulated arm robots is limited by errors in kinematic calibration, gear backlash, joint
Nguyen, VinhCvitanic, ToniBaxter, MatthewAhlin, KonradJohnson, JoshuaFreeman, PhilipBalakirsky, StephenBrown, AllisonMelkote, Shreyes
Aluminum Metal Matrix Composite (AMMC) materials have loftier individualities and are known as an alternative material for a range of aerospace and automotive engineering applications. Reinforcement inclusion makes the components tougher, resulting in low performance of machining by traditional conservative machining practices. The present study presents a detailed review of the machinability of AMMC (Pure Aluminum + Graphene nanoplatelets) using Wire Electric Discharge Machining (WEDM). For WEDM of AMMC, a multi-objective optimization method is proposed to evaluate possible machining parameters in order to achieve better machining efficiency. Taguchi’s approach to the design of experiments is used to organize the experiments. For performing experiments, an L27 orthogonal array was selected. Five input process variables were considered for this study. The Grey Relational Analysis (GRA) is used to achieve the best features of multi-performance machining. The experimental results show
Prakash, P. BhanuMahesh, R.Rajesh, D. MerwinBabu, D.Devika, B.
Stellite is a nickel based superalloy and expansively adopted in higher temperature engineering applications. This alloy possesses better mechanical properties such as strength and hardness. Due to its lesser thermal conductivity, it is difficult to machine by conventional methods of machining. For avoiding such kind of demerits, advanced methods of machining have been introduced. Wire Electrical Discharge Machining (WEDM) is one of category of thermal energy based machining methods which is developed from the concept of Electrical Discharge Machining. This kind of machining method is preliminarily engaged for making complex shaped components especially in harder and electrically conductive materials. In this present experimental study, an endeavour has been taken to analyse the optimized process parameters for achieving better machining performance during WEDM of Stellite using Taguchi-Grey approach. The experimental runs are planned by Taguchi design approach and also the combination
N, MANIKANDANJoseph Selvi, BinojKRISHNAMACHARY, P.CThejasree, P
AA 2014 is a copper based aluminium alloy which is having exceptional mechanical characteristics such as better strength, ductility and lesser fatigue. AA 2014 is most generally employed in various engineering applications such as fabrication of structural components, defence applications and manufacturing of aerospace components. Also, this material possess better resistant to corrosion which makes this material best suitable for numerous engineering applications. Unconventional methods of machining have been evolved for producing intricate shapes in electrically conductive components. Wire Electrical Discharge Machining (WEDM) is one among the unconventional machining method which is used for making intricate shape on any electrically conductive work material. In this work, an experimentation has been carried out on WEDM of AA 2014 alloy, employing Taguchi’s technique. The experimental runs have been conducted by taking into account, the process variables such as pulse-on-time, pulse
Navya, C.Chandra Sekhara Reddy PhD, M
SS304 (Stainless Steel 304) is a nickel- chromium based alloy, that is extensively used for the applications like cryogenic vessels, valves, refrigerator equipment and evaporators because of its high corrosion resistance, ductility and ability to remain as solid up to a temperature of 14000 C. SS304 is one of the tough to machine materials by conventional methods of machining. Wire Electrical Discharge Machining (WEDM) facilitates the ease of machining complicated cuts with hard to machine, conductive materials where high surface finish is required. In this investigation, a study has been done on WEDM of SS304 and mainly to optimize the process parameters during the machining of SS304 by using Taguchi’s analysis. Taguchi’s DoE approach is used to plan the experimental runs and by considering the process parameters such as pulse on time, pulse off time and peak current at three different levels the experiments were conducted. The performance measures considered in present analysis are
Thejasree, P.N, ManikandanKrishnamachary, PCVaraprasad, K CJoseph Selvi, Binoj
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