Статті в журналах: "MACHINING VARIABLES"

1

Neto, João Cirilo da Silva, Evaldo Malaquias da Silva, and Marcio Bacci da Silva. "Intervening variables in electrochemical machining." Journal of Materials Processing Technology 179, no. 1-3 (October 2006): 92–96. http://dx.doi.org/10.1016/j.jmatprotec.2006.03.105.

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2

Churi, N. J., Z. J. Pei, and C. Treadwell. "ROTARY ULTRASONIC MACHINING OF TITANIUM ALLOY: EFFECTS OF MACHINING VARIABLES." Machining Science and Technology 10, no. 3 (September 2006): 301–21. http://dx.doi.org/10.1080/10910340600902124.

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3

Cong, W. L., Z. J. Pei, Timothy Deines, Q. G. Wang, and Clyde Treadwell. "Rotary Ultrasonic Machining of stainless steels: empirical study of machining variables." International Journal of Manufacturing Research 5, no. 3 (2010): 370. http://dx.doi.org/10.1504/ijmr.2010.033472.

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4

Nandhakumar, S., S. Sathish Kumar, and K. Sakthivelu. "Optimization of Machining Variables in Electric Discharge Machining Using Stainless Steel 317 in Full Factorial Method." Mechanics and Mechanical Engineering 22, no. 1 (August 12, 2020): 105–18. http://dx.doi.org/10.2478/mme-2018-0010.

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AbstractElectric Discharge Machining (EDM) is a non-conventional machining process and has a larger extent of application in manufacturing industry due to its accuracy. EDM simply uses electrical spark between the tool and workpiece in presence of dielectric medium to erode the workpiece in controlled manner. Improving the material removal rate and decreasing the tool wear rate (TWR), achieving higher surface finish, reducing machining time and enhancing dimensional accuracy are the major areas of focus in electrical discharge machining (EDM) process of SS 317 grade steel. In this research work effort to reduce the tool wear rate is concentrated by comparing the machining performance of two distinct electrodes namely copper and brass. Each electrode has their unique machining capabilities and the experimental results were compared in-terms of tool wear rate (TWR), Metal Removal Rate (MRR) and Machining Time (TM). Input variables were optimized based on the experimental output responses to achieve optimal level of input variables.

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5

Frumuşanu, Gabriel, and Alexandru Epureanu. "HOLISTIC MONITORING OF MACHINING SYSTEM." International Journal of Modern Manufacturing Technologies 13, no. 3 (December 25, 2021): 45–53. http://dx.doi.org/10.54684/ijmmt.2021.13.3.45.

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Nowadays, the part program describes only the process itself and not the obtained performance. The operator monitors just some of the variables describing the actually obtained product and appropriately adjusts the values of the programmed variables. This adjustment is realised with a considerable delay and without an adequate fundament (many times even intuitively). Moreover, process monitoring currently follows only to notice the occurrence of perturbations and, hence, of deviations from process plan. As consequence, the performance in accomplishing the manufacturing task might be diminished due to an insufficient knowledge about both the system dynamics and the conditions in which the process is performed. Starting from these premises, the challenge addressed here is to rebuild at conceptual level the monitoring system such us the monitoring becomes holistic, this meaning evaluation & reveal of machining system current state & dynamics. In other words, the holistic monitoring concerns both the values of the variables describing the system state and the relations of causality between them. In this paper, the holistic monitoring is introduced through an illustrative sample. The monitoring variables and functions are defined and sampled.

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6

Mehrvar, Ali, Ali Basti, and Ali Jamali. "Inverse modelling of electrochemical machining process using a novel combination of soft computing methods." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 234, no. 17 (April 2, 2020): 3436–46. http://dx.doi.org/10.1177/0954406220916495.

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Selection of optimal and suitable process parameters is a crucial issue in manufacturing processes especially in electrochemical machining (ECM). Since the utmost target is to find suitable machining parameters for gaining desired machining performances, a new hybrid approach has been applied for inverse modelling of ECM process. Four machining inputs, i.e. voltage, tool feed rate, electrolyte flowrate and concentration; and two machining responses, i.e. surface roughness (Ra) and material removal rate (MRR) are presented as input variables and responses, respectively. In the proposed approach, firstly, comprehensive mathematical equations have been established based on response surface methodology (RSM). The two machining performances are modeled in this step with machining parameters. Then, the differential evolution (DE) algorithm has been used for Pareto-based multi-objective optimization. Finally, group method of data handling (GMDH)-type neural networks is used through the Pareto table for inverse modelling. As a result, four models have been developed for each of the four machining parameters; therefore, each machining parameters is determined according to the machining performance as two new design variables. The results demonstrated that the suggested method is a helpful and promising tool for inverse modelling and determining such important relationships between optimized responses and input variables.

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7

Chainawakul, Adirake, Koji Teramoto, and Hiroki Matsumoto. "Statistical Modelling of Machining Error for Model-Based Elastomer End-Milling." International Journal of Automation Technology 15, no. 6 (November 5, 2021): 852–59. http://dx.doi.org/10.20965/ijat.2021.p0852.

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Elastomer end-milling has attracted attention for use in the small-lot production of elastomeric fragments because the technique is an applicable method for a large variety of materials and does not require the preparation of expensive and time-consuming moulds. In order to effectively utilize elastomer end-milling, it is necessary to ensure the machining accuracy of elastomeric parts machined through this technique. However, the control method of machining error in the elastomer end-milling has not been presented since most machining services of the elastomeric part are based on enterprise-dependent dexterities or know-how. The objective of this paper is to construct and utilize a machining error model for elastomer end-milling. A statistical model based upon physical states and machining conditions is introduced and investigated. In this paper, a framework for modelling the machining error in elastomer end-milling is also proposed. In the framework, the candidates of model variables are evaluated based on the preliminary experiments. Moreover, a statistical model is constructed by using the selected variables. Candidate variables are cutting conditions and predictable physical state variables such as workpiece deformation and cutting force. The framework is investigated by evaluating error prediction with the experimental results. An identified error model from limited machining cases can estimate the machining error of different machining cases. The results indicate that the proposed modelling method is capable of supporting to achieve model-based precision elastomer end-milling.

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8

Paul, Lijo, та S. Hiremath Somashekhar. "Effect of Process Parameters on Heat Affected Zone in Micro Machining of Borosilicate Glass Using μ-ECDM Process". Applied Mechanics and Materials 592-594 (липень 2014): 224–28. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.224.

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Application of borosilicate glass in Micro Electro Mechanical Systems (MEMS) devices are increasing due to many of its intrigue properties. Micro machining of glass for such applications needs hybrid technology so as to produce precise products. Electro Chemical Discharge Machining (ECDM) has proved immense potential in micro machining of glass. Present paper focuses on the effect of various process parameters of μ-ECDM on Heat Affected Zone (HAZ) while machining borosilicate glass. Grey Relation Analysis (GRA) is used to optimize the process variables. The optimized process variables are confirmed with experimental results.

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9

Pradhan, Mohan Kumar, and Chandan Kumar Biswas. "Response Surface Analysis of EDMED Surfaces of AISI D2 Steel." Advanced Materials Research 264-265 (June 2011): 1960–65. http://dx.doi.org/10.4028/www.scientific.net/amr.264-265.1960.

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In this study, the effects of the machining parameters in electrical-discharge machining (EDM) on the machining characteristics of AISI D2 steel using copper electrodes were investigated. The response functions considered material removal rate (MRR) and Surface Roughness (Ra),while machining variables are pulse current, pulse on time, pause time and gap voltage. A Response surface methodology was used to reduce the total number of experiments. Empirical models correlating process variables and their interactions with the said response functions have been established. The significant parameters that critically influenced the machining characteristics were examined, and the optimal combination levels of machining parameters for material removal rate, and surface roughness were determined. The models developed reveal that pulse current is the most significant machining parameter on the response functions followed by voltage and pulse off time for MRR. However for, for Ra also pulse current is most significant followed by pulse on time and discharge voltage the respectively. The model sufficiency is very satisfactory as the coefficientR2of is determination (R2) is found to these be greater than 98 %. These models can be used for selecting the values of process variables to get the desired

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10

Rehman, Gulfam Ul, Syed Husain Imran Jaffery, Mushtaq Khan, Liaqat Ali, Ashfaq Khan, and Shahid Ikramullah Butt. "Analysis of Burr Formation in Low Speed Micro-milling of Titanium Alloy (Ti-6Al-4V)." Mechanical Sciences 9, no. 2 (July 20, 2018): 231–43. http://dx.doi.org/10.5194/ms-9-231-2018.

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Abstract. The use of titanium based alloys in aerospace and biomedical applications make them an attractive choice for research in micro-machining. In this research, low speed micro-milling is used to analyze machinability of Ti-6Al-4V alloy as low speed machining setup is not expensive and it can be carried out on conventional machine tools already available at most machining setups. Parameters like feed per tooth, cutting speed and depth of cut are selected as machining variables and their effect on burr formation is analyzed through statistical technique analysis of variance to determine key process variables. Results show that feed per tooth is the most dominant factor in burr formation (81 % contribution ratio). The effect of depth of cut was found to be negligible. It was also observed that micro-milling at optimum process parameters showed minimum burr formation. In terms of burr formation, as compared to high speed machining setup, better results were achieved at low speed machining setup by varying machining parameters.

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11

Zhong, Gao Yan. "Ternary Regression Modeling Analysis of NC Ultrasonic Machining Efficiency." Applied Mechanics and Materials 37-38 (November 2010): 1388–92. http://dx.doi.org/10.4028/www.scientific.net/amm.37-38.1388.

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To explore the impact of abrasive granularity, feed pressure and cutting feed speed on NC ultrasonic machining efficiency, a three-factor four-level orthogonal test was carried out, and data were analyzed to establish a ternary nonlinear regression model of NC ultrasonic machining efficiency. Furthermore, significance of the regression model and impact of all independent variables on dependent variables were studied. The study showed that when significance level is α = 0.01, the combination of the three factors tested impacts significantly on machining efficiency indicators. However, among the three factors, the abrasive granularity has the highest impact and its impact on the machining efficiency is nonlinear.

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12

Katz, Z., and T. van Niekerk. "Implementation aspects of intelligent machining." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 217, no. 5 (May 1, 2003): 601–13. http://dx.doi.org/10.1243/095440503322011335.

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Анотація:

Intelligent machining is an advanced method in manufacturing, related to the recent developments in reconfigurable manufacturing equipment. A multilevel modular scheme for implementing integrated process monitoring, diagnosis and control is proposed. A PC-based hardware integrated within an object-based software structure is used to manipulate several machining parameters while performing on-line sensing of machining variables, through sampling and processing by means of digital signal processing (DSP). Indirect measurement of machining parameters, surface finish and tool wear monitoring, through the use of neurofuzzy (NF) sensor fusion modelling, is presented as a part of the integrated approach. A fuzzy relation (FR), indicating the nature of the connection between dependent and independent process-related variables, and acting as a knowledge node within a decision-making scheme, determines intelligently the variations in machining parameters when a performance parameter exceeds the predetermined functional limits. Such capability is utilized on-line. The integrated approach for further improvement in machining quality and overall productivity is described.

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13

Dyl, Tomasz, Adam Charchalis, and Mirosław Szyfelbain. "The Impact of Independent Variables Surface Machining Duplex Stainless Steel on the Flank Wear." Acta Metallurgica Slovaca 26, no. 1 (March 19, 2020): 27–30. http://dx.doi.org/10.36547/ams.26.1.306.

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Анотація:

Surface engineering is important for carried out to improve the quality of the surface layer of the material. It is important that in special applications of corrosion resistant steel, low surface roughness is obtained. Duplex stainless steel is becoming more widely used for example in the petrochemical industry or shipbuilding. Duplex stainless steel is a material classified as difficult-to-cut. It is therefore important to investigate the impact of machining parameters on the durability and wear of a cutting tool. In the paper has determined the influence of variables machining: feed rate, depth of cut, cutting speed, on the maximum tool flank wear. Surface machining was carry out with carbide tipped inserts. The criterion of the smallest roughness and the highest wear was proposed.

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14

Cherian, Jose, and Jeoju M. Issac. "Fatigue Performance in Abrasive Flow Machining." Applied Mechanics and Materials 592-594 (July 2014): 354–62. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.354.

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Surface finish and Manufacturing process has a prominent role in the fatigue life of a machine component. Fatigue strength of a material generally increases with the surface finish. But the super finishing process like electro polishing reduces the fatigue strength of the material. In Abrasive flow machining it is found that surface finish and fatigue strength always increasing. In Abrasive flow machining the fatigue strength is mainly governed by the process variables extrusion pressure, abrasive concentration and mesh size. This research studies the influence of the process variables on the fatigue strength of the material. In this study an approximate surface finish of 4μm is obtained after AFM. The effect of three process variables on the response function selected, fatigue strength, were studied. A statistical 23full factorial experimental technique is used to find out the main effect, interaction effect and contribution of each variable on fatigue strength. The instron machine is used to find out the number of cycles to failure of the material. The fatigue strength is obtained with S-N curve analysis.

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15

Loginov, N., O. Khudyakova, and E. Orlova. "Modeling of Tribological Characteristics of Specimens with Wear-Resistant Coating Using Dummy Variables." Materials Science Forum 945 (February 2019): 919–25. http://dx.doi.org/10.4028/www.scientific.net/msf.945.919.

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In the process of machining, one of the main factors affecting machining tool wear is friction. A decrease in the coefficient of friction between the machining tool and a machined part is a key challenge for researchers. One of the methods to decrease the coefficient of friction and, consequently, to improve the endurance of the tool is the application of wear-resistant coatings. In the current study, modelling of triboprocesses using dummy variables is proposed. Since a peculiarity of modelling of manufacturing processes is a presence of a large number of quality parameters, the influence of all key parameters on the value of the coefficient of friction has been analysed. Also, an adequate model of the dependence of the conditions of the manufacturing process on the coefficient of friction has been developed. The results of the model are important not only for analysis of friction between contact surfaces itself, but also as supplementary and qualitative estimation of different manufacturing processes.

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16

Ma, Bao Ji, Yu Quan Zhu, and Xiao Li Jin. "Wire Electro Discharge Machining of Al/SiC Metal Matrix Composite." Applied Mechanics and Materials 121-126 (October 2011): 564–67. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.564.

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The machining characteristics of SiC/Al composite using wire electro discharge machining (WEDM) were investigated in this study. Material cutting speed and surface roughness value were adopted to evaluate the machinability. Peak current, pulse on time, pulse duration and working voltage were selected as the input variables to investigate the machining performance. Effects of input variables on the cutting speed and surface roughness were experimentally tested. Peak current, pulse on time and working voltage were confirmed to have positive effects on cutting speed and surface roughness value. Whereas the cutting speed and surface roughness value decrease with the increase of pulse duration.

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17

Umanath, K., and D. Devika. "Optimization of electric discharge machining parameters on titanium alloy (ti-6al-4v) using Taguchi parametric design and genetic algorithm." MATEC Web of Conferences 172 (2018): 04007. http://dx.doi.org/10.1051/matecconf/201817204007.

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Анотація:

The aim of this research work is to analyze the significant of process variables and find the optimum process variables in electric discharge machining (EDM) of Titanium alloy (Ti-6Al-4V) .The variables considered are peak current, pulse-on-time and pulse-off-time where as the responses are Material Removal Rate(MRR) and Surface Roughness(SR). MITSUBISHI EA8 spark erosion machine is employed for this work and copper tungsten electrode of ∅14 mm is used in experimental trials. The experimental runs are done based on Taguchi L27 orthogonal array. The signal-to-noise ratio, the analysis of variance (ANOVA), regression analysis and Genetic algorithm are used to determine the optimal levels of machining parameters on Metal removal rate and Surface roughness. Confirmation tests also done with the optimal levels of machining variables. Comparison of Taguchi’s and Genetic algorithm were employed to analyze the effective optimum value.

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18

Jozić, Sonja, Dražen Bajić, Ivana Dumanić, and Željko Bagavac. "Optimization for an efficient and highly productive turning process." Reports in Mechanical Engineering 2, no. 1 (December 15, 2021): 212–21. http://dx.doi.org/10.31181/rme2001021212j.

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The required quality of the product arises from the customer preferences and functional requirements of the product and is determined mostly by the machining operation. Properly selected machining parameters in machining processes are of great importance for improving process efficiency and product quality. The aim of this paper is to find cutting parameters with which above mentioned process and product characteristics will be achieved. Experiments were performed according to Box-Behnken design of experiments. Influential input variables were cutting speed, feed per revolution and depth of cut and output variables were surface roughness, power consumption and material removal rate. Multi-objective optimization function was developed to find the machining parameters with which the lowest power consumption, the best surface quality and the greatest material removal rate will be achieved.

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19

Luo, X. C., K. Cheng, and R. Ward. "Correlating Surface Functionality with Machining Conditions in Precision Machining Processes." Materials Science Forum 471-472 (December 2004): 112–16. http://dx.doi.org/10.4028/www.scientific.net/msf.471-472.112.

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This paper attempts to correlate surface functionality generation with machining conditions by computer simulation and machining trials. The linear and nonlinear machining conditions, such as feed rate, built-up-edge, shear- localized chip formation, regenerative chatter are modelled in the light of their physical features. They are the inputs to the integrated surface topography generation model. The dynamic tool path is calculated through the dynamic cutting force model and surface response model. The surface is generated by transforming the tool profile onto the workpiece surface along the dynamic tool path. All of these models are integrated in a user-friendly Matlab Simulink environment. On the basis of the Simulink model, the dynamic simulation is performed to predict the 3D machined surface topography and its functionality. The simulation results have been validated by precision turning trials. The spectrum analysis of the machining dynamics and surface topography shows that surface generation is highly affected by the nonlinear factors in precision turning process. A case study shows the feasibility of generating some functional surface for some product/component through controlling machining variables.

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20

Koo, Joon Young, Pyeong Ho Kim, Moon Ho Cho, Hyuk Kim, Jeong Kyu Oh, and Jeong Suk Kim. "Machining Evaluation of High-Speed Milling for Thin-Wall Machining of Al7075-T651." Applied Mechanics and Materials 541-542 (March 2014): 785–91. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.785.

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This paper presents finite element method (FEM) and experimental analysis on high-speed milling for thin-wall machining of Al7075-T651. Changes in cutting forces, temperature, and chip morphology according to cutting conditions are analyzed using FEM. Results of machining experiments are analyzed in terms of cutting forces and surface integrity such as surface roughness and surface condition. Variables of cutting conditions are feed per tooth, spindle speed, and axial depth of cut. Cutting conditions to improve surface integrity were investigated by analysis on cutting forces and surface roughness, and machined surface condition.

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21

Lin, Yan Cherng, Jung Chou Hung, Lih Ren Hwang, and A. Cheng Wang. "Optimal the Multiple Performances in EDM for SKH57 Using Grey Relational Analysis." Applied Mechanics and Materials 710 (January 2015): 99–105. http://dx.doi.org/10.4028/www.scientific.net/amm.710.99.

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The aim of this investigation is to optimize the multiple performancesof electrical discharge machining (EDM) process for SKH57 using grey relational analysis.Themachining performances namely electrode wear rate (EWR) and surface roughness (SR) were considered as theresponses. Aseries of experiments were conducted according to an L18 orthogonal array based on the Taguchi experimental design method.The main input variables such as machining polarity (P),peak current (Ip), auxiliary current with high voltage (IH), pulse duration (p), no-load voltage (V) and servo reference voltage (Sv) were selected to explore their effects on machining performances for high speed steel (HSS) graded SKH57.Moreover, analysis of variance (ANOVA) was conducted to explore the significant input variables crucially affecting the multiple performances. In addition, the optimal combinations of input variables were also determined from the response graph of grey relational grades. The experimental results confirmed the multiple performances of SKH57 would obviously be improved through optimizing the input variables using grey relational analysis.

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22

Bi, Xue Feng, Gautier List, G. Sutter, A. Molinari, and Yong Xian Liu. "Crater Wear Modeling in Conventional Speed Machining." Advanced Materials Research 97-101 (March 2010): 1891–94. http://dx.doi.org/10.4028/www.scientific.net/amr.97-101.1891.

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Wear modeling makes it possible to predict the evolution of wear profile and explain wear mechanism from process variables, such as temperature, pressure and sliding velocity etc. A composite crater wear model considering adhesive and diffusion wear is established by means of experiment and modeling in conventional speed machining. A series of cutting tests are performed to obtain wear profiles and corresponding process variables. The constants in wear model are fitted by regression analysis with crater wear tests. This crater wear model shows a good predictive capability in conventional cutting speed.

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23

Sridhar, Srinath, and Rajeswari Sellamani. "Investigation of input variables on temperature rise while end milling Al/SiC metal matrix composite." World Journal of Engineering 17, no. 4 (June 19, 2020): 599–607. http://dx.doi.org/10.1108/wje-01-2020-0031.

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Purpose The purpose of this paper is to find out the optimal level as well as the influence of end mill cutter geometrical and machining parameters while machining metal matrix composite. End milling is carried out on Al 356/SiC metal matrix composites (MMC) using high-speed steel (HSS) end mill cutter. The optimum level of input parameters such as helix angle, nose radius, rake angle, cutting speed, feed rate and depth of cut are calculated for minimum temperature rise. Design/methodology/approach L27 Taguchi orthogonal design, signal-to-noise (S/N) ratio, are applied for conducting experiments, and to find the optimal level of input parameters for minimum temperature rise, respectively. Analysis of variance (ANOVA) is used to analyze the significance of input parameters on temperature rise. Findings It is found that the optimal combination of helix angle 400, nose radius 0.8 mm, rake angle 80, cutting speed 30 m/min, feed rate 0.04 mm/rev and depth of cut 0.5 mm have generated minimum temperature rise. From ANOVA analysis, it is found that rake angle influence is more on output performance followed by cutting speed and nose radius compared with other machining and geometrical parameters. Originality/value The influence of geometrical parameters such as helix angle, nose radius and rake angle of end mill cutter on temperature rise while machining MMC has not been explored previously.

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24

Thangadurai, K. R., and A. Asha. "Parametric Optimization of EDM Process of Aluminium Boron Carbide Composite Using Desirability Function Approach and Genetic Algorithm." Applied Mechanics and Materials 592-594 (July 2014): 684–88. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.684.

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Electric discharge machining process is an unconventional machining process primarily used for machining the materials such as difficult to machine in conventional machining process, hardest material and composite materials. In the present work, a study is made to find out the optimum EDM process parameters during machining of AA6061-15% boron carbide composite fabricated through stir casting technique. Three process parameters such as Current, pulse on time and pulse of time are opted as machining parameter variables. Response surface methodology is used to formulate the mathematical model for material removal rate, tool wear rate and surface roughness. Response surface methodology and genetic algorithm are applied to optimize the machining parameters individually by taking combined objective function and compared. Genetic algorithm optimization techniques yields better results than desirability approach. Key words: Electric discharge machining, MRR, TWR, Ra, RSM, Genetic algorithm

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25

Konneh, Mohamed, Sudin Izman, Mirza Emmil Dzahi Padil, and Rosniza Roszat. "Surface Roughness Study of Milled Carbon Fiber Reinforced Polymer (CFRP) Composite Using 4 mm 2-Flute Titanium Aluminum Nitride (TiAlN) Coated Carbide End Mills." Advanced Materials Research 887-888 (February 2014): 1101–6. http://dx.doi.org/10.4028/www.scientific.net/amr.887-888.1101.

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Анотація:

As the goal for aircraft weight reduction and low fuel consumption becomes a dire concern in aerospace industries, there is driving desire for the increasing use of advanced exotic materials such as composites, titanium and Inconels in the aerospace industry because of their high strength to weight ratio. Nevertheless the inherent anisotropy, inhomogeneous properties of CFRP and low bonding strength within the laminates make machining of these composite materials results in several undesirable effects such as delamination, micro-cracking, burr, fiber pull out and breakage. This paper discusses an experimental investigation into the influence of machining parameters on surface roughness when milling CFRP using 4 mm-diameter 2-fluted carbide end-mill coated with Titanium Aluminium Nitride (TiAlN). Relationship between the machining variables and the output variables is established and a mathematical model is predicted for the surface roughness produced during the milling process for the machining conditions investigated.

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26

Srinivasan, V. P., Ch Sandeep, C. Shanthi, A. Bovas Herbert Bejaxhin, R. Anandan, and M. Abisha Meji. "Comparative Study on EDM Parameter Optimization for Adsorbed Si3N4–TiN using TOPSIS and GRA Coupled with TLBO Algorithm." Adsorption Science & Technology 2022 (September 30, 2022): 1–19. http://dx.doi.org/10.1155/2022/4112448.

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Анотація:

Electrical discharge machining is a thermo-physical-based material removal technique. 25 combinations of process variables were formulated with the aid of Taguchi technique for EDM of adsorbed Si3N4–TiN. Machining variables like pulse current, pulse-on time, pulse-off time, dielectric pressure, and spark gap voltage varied, and impact of each variables on the performance metrics (MRR, EWR, SR, ROC, θ, CIR, and CYL) was assessed. MCDM strategies like grey relational analysis and TOPSIS are utilized to find out the ideal arrangement of machining parameters to achieve most acute productivity of the multitude of reactions. Likewise, metaheuristic algorithm in particular GRA combined with teaching-learning-based optimization algorithm is utilized for getting global optimized input factors. Important factors like pulse current, pulse-on time, and spark gap voltage characteristically affect the outputs. It is recognized that the pulse-on time and the pulse current are the most significant input factors than others. The ideal machining parameters in view of GRA and TOPSIS techniques for acquiring better output factors are I, 12 amps; PON, 7 μsec; POFF, 4 μsec; DP, 12 kg/cm2; and SV, 36 volts.

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27

Wang, Hui, Weilong Cong, Fuda Ning, and Yingbin Hu. "A study on the effects of machining variables in surface grinding of CFRP composites using rotary ultrasonic machining." International Journal of Advanced Manufacturing Technology 95, no. 9-12 (December 16, 2017): 3651–63. http://dx.doi.org/10.1007/s00170-017-1468-6.

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28

Zhang, Yani, Haoshu Xu, Jun Huang, and Yongmao Xiao. "Low-Carbon and Low-Energy-Consumption Gear Processing Route Optimization Based on Gray Wolf Algorithm." Processes 10, no. 12 (December 4, 2022): 2585. http://dx.doi.org/10.3390/pr10122585.

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Анотація:

The process of gear machining consumes a large amount of energy and causes serious pollution to the environment. Developing a proper process route of gear machining is the key to conserving energy and reducing emissions. Nowadays, the proper process route of gear machining is based on experience and is difficult to keep up with the development of modern times. In this article, a calculation model of low-carbon and low-energy consumption in gear machining processes was established based on an analysis of the machining process. With processing parameters as independent variables, the grey wolf algorithm was used to solve the problem. The effectiveness of the method was proven by an example of the machining process of an automobile transmission shaft.

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29

Gupta, Vivudh, and Pawandeep Singh. "Turning of Aluminium Composites: Characteristics and Future Prospects." IOP Conference Series: Materials Science and Engineering 1248, no. 1 (July 1, 2022): 012077. http://dx.doi.org/10.1088/1757-899x/1248/1/012077.

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Анотація:

Abstract Aluminium matrix composites have widespread applications in different industrial areas including automobile and aerospace owing to their improved mechanical and tribological properties over conventional monolithic materials. As such, machining of these metal matrix composites is an important aspect to be studied in order to manufacture desired components with close tolerances. Presence of hard abrasive ceramic reinforcements in composites increases the chance of tool wear and hence, increased machining cost during conventional machining process. In order to improve machining characteristics of aluminium composites, machining is carried out using specialized carbide tools (both coated and uncoated), polycrystalline diamond inserts, CVD diamond coated inserts, etc. This paper presents a state-of-the-art review on turning of aluminium composites. Factors affecting machinability like content, size, and morphology of reinforcement along with matrix hardness are discussed. Effect of process variables such as cutting speed, feed rate, depth of cut, etc. on response variables such as tool wear, surface finish, cutting forces, cutting temperature, etc. has been highlighted. Moreover, failure mechanisms involved in turning process occurring due to debonding, plastic deformation, particle fracture, etc. are deliberated in this study. Various modelling and optimization studies in this area are discussed in detail as well. Furthermore, scope for future work in this area including sustainable machining is also elucidated.

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30

Sharma, Neeraj, Tilak Raj, and Kamal Kumar Jangra. "Parameter optimization and experimental study on wire electrical discharge machining of porous Ni40Ti60 alloy." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 231, no. 6 (March 31, 2015): 956–70. http://dx.doi.org/10.1177/0954405415577710.

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NiTi is a shape memory alloy, mostly employed in cardiovascular stents, orthopedic implants, orthodontic wires, micro-electromechanical systems and so on. The effective and net shape machining of NiTi is very critical for excellent response of this material in medical and other applications. The present experimental work on wire electrical discharge machining process identifies the influence of process parameters that affect the cutting rate, dimensional shift and surface roughness while machining of porous nickel–titanium (Ni40Ti60) alloy. Porous Ni40Ti60 alloy was produced in-house using powder metallurgy technique. Response surface methodology–based central composite rotatable design has been used for the planning of experiments on wire electrical discharge machining. Empirical relations have been developed between the process parameters (pulse on-time, pulse off-time, servo voltage and peak current) and response variables. Desirability approach has been used for optimizing the three response variables simultaneously. Confirmation experiments were also performed at the optimized settings and reflect a close agreement between the predicted and experimental values (percentage error varies from −6.13% to +6.85%). Using wire electrical discharge machining, NiTi alloy can be machined easily and successfully in single-cutting operation, but after the first cut in wire electrical discharge machining, a surface projection appears on work surface which is the unmachined material on work surface.

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31

Charles, Sarla Rubi, Udaya Prakash Jayavelu, Rajkumar Chinnaraj, and Sachin Salunkhe. "Optimization of drilling process variables using taguchi technique for LM6 aluminium alloy." International Journal for Simulation and Multidisciplinary Design Optimization 13 (2022): 19. http://dx.doi.org/10.1051/smdo/2022008.

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Анотація:

The abrasive characteristics of LM6 alloys are difficult to machine, so designing a technology that allows for effective machining is essential. This paper aims to evaluate the effect of process variables, namely feed rate, spindle speed and drill material, towards the responses like Thrust force, Surface roughness and burr height when drilling of LM6 alloy. LM6 aluminium alloy was fabricated by the stir casting process. Experiments were conducted using L9 orthogonal array in a Vertical Machining Centre coupled with a dynamometer for measuring thrust force. Surface roughness was found by Surface roughness tester and burr height was measured using Vision Measuring System. The findings show that the created model can accurately estimate the thrust force (TF), surface roughness (SR) and burr height (BH) in LM6 alloy drilling within the parameters examined.

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32

Ayadi, Badreddine, Lotfi Ben Said, Mohamed Boujelbene, and Sid Ali Betrouni. "Three-Dimensional Synthesis of Manufacturing Tolerances Based on Analysis Using the Ascending Approach." Mathematics 10, no. 2 (January 10, 2022): 203. http://dx.doi.org/10.3390/math10020203.

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Анотація:

The present paper develops a new approach for manufacturing tolerances synthesis to allow the distribution of these tolerances over the different phases concerned in machining processes using relationships written in the tolerance analysis phase that have been well developed in our previous works. The novelty of the proposed approach is that the treatment of non-conventional surfaces does not pose a particular problem, since the toleranced surface is discretized. Thus, it is possible to study the feasibility of a single critical requirement as an example. During the present approach, we only look for variables that influence the requirements and the others are noted F (Free). These variables can be perfectly identified on the machine, which can be applied for known and unknown machining fixtures; this can be the base for proposing a normalized ISO specification used in the different machining phases of a mechanical part. The synthesis of machining tolerances takes place in three steps: (1) Analysis of the relationship’s terms, which include the influence of three main defects; the deviation on the machined surface, defects in the machining set-up, and the influence of positioning dispersions; then (2) optimization of machining tolerance through a precise evaluation of these effects; and finally (3) the optimization of the precision of the workpiece fixture, which will give the dimensioning of the machining assembly for the tooling and will allow the machining assembly to be qualified. The approach used proved its efficiency in the end by presenting the optimal machining process drawing that explains the ordered phases needed to process the workpiece object of the case study.

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33

Deepanraj, B., N. Senthilkumar, G. Hariharan, T. Tamizharasan, and Tesfaye Tefera Bezabih. "Numerical Modelling, Simulation, and Analysis of the End-Milling Process Using DEFORM-3D with Experimental Validation." Advances in Materials Science and Engineering 2022 (September 13, 2022): 1–11. http://dx.doi.org/10.1155/2022/5692298.

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Анотація:

In this present work, finite element analysis (FEA)-based simulation of end-milling of AISI1045 steel using tungsten carbide tool was performed using DEFORM-3D simulation software. Usui tool wear model, Johnson-cook material model and adaptive remeshing are considered during machining simulation. The impact of machining variables rate of feed, tool speed, and depth of cut was investigated, and the best integration of variables was distinguished for lower cutting temperature, principal stress, cutting forces, effective stresses, tool wear, and effective strain. The obtained results were correlated using experimentation in a vertical machining center attached with a Kistler tool dynamometer with data acquisition setup for capturing the cutting forces, and an infrared (IR) thermometer was used to measure the cutting temperature, and a comparison was done. Results showed a good correlation. There is a relationship between experimental and numerical results, and simulation findings can be utilised for interpreting the influence of machining parameters.

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34

Virk, Gurpreet Singh, Balkar Singh, Yadvinder Singh, Shubham Sharma, R. A. Ilyas, and Vikas Patyal. "Abrasive water jet machining of coir fiber reinforced epoxy composites: a review." Functional Composites and Structures 4, no. 1 (March 1, 2022): 014001. http://dx.doi.org/10.1088/2631-6331/ac586c.

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Анотація:

Abstract Natural-fiber-reinforced composites are progressively attracting interest in the aerospace, automotive, aeronautics, and marine sectors due to their good strength-to-weight ratios, long lifetimes and cost-effectiveness. Traditional machining methods have trouble machining such composite materials. However, abrasive water jet machining (AWJM) provides an alternative quality machining method that can be accomplished by regulating various process variables. The efficiency of the AWJM method has been the subject of extensive study, due to its negligible heat-affected zone. This review attempts to focus on an exploration of the thermal and mechanical properties and the AWJM efficiency of various coir-fiber-based composites in relation to various parameters and to determine the best AWJM operating conditions. There are numerous process variables that influence AWJM machined surface quality. However, the standoff distance, hydraulic pressure, abrasive mass flow rate, nozzle diameter, and transverse speed are all important factors to consider. Kerf taper, kerf width, and surface roughness are considered key response factors.

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35

Zhu, Xiaolong, Sitong Xiang, and Jianguo Yang. "Novel thermal error modeling method for machining centers." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 229, no. 8 (July 28, 2014): 1500–1508. http://dx.doi.org/10.1177/0954406214545661.

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Анотація:

Thermal deformation is one of the main contributors to machining errors in machine tools. In this paper, a novel approach to build an effective thermal error model for a machining center is proposed. Adaptive vector quantization network clustering algorithm is conducted to identify the temperature variables, and then one temperature variable is selected from each cluster to represent the same cluster. Furthermore, a non-linear model based on output-hidden feedback Elman neural network is adopted to establish the relationship between thermal error and temperature variables. The output-hidden feedback Elman network is adopted to predict the thermal deformation of the machining center. Back propagation (BP) neural network is introduced for comparison. A verification experiment on the machining center is carried out to validate the efficiency of the newly proposed method. Experimental verification shows that the adaptive vector quantization network clustering algorithm and output-hidden feedback Elman neural network is an accurate and effective method.

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36

Khan, Akhtar, and Kalipada Maity. "Parametric Optimization of Some Non-Conventional Machining Processes Using MOORA Method." International Journal of Engineering Research in Africa 20 (October 2015): 19–40. http://dx.doi.org/10.4028/www.scientific.net/jera.20.19.

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Анотація:

Non-conventional manufacturing techniques are most widely used in industries in order to achieve high accuracy and desirable product quality. Therefore, the selection of an appropriate machining parameter has become a crucial job before starting the operation. Several optimization methods are available to resolve the upstairs situation. The current study explores a novel technique namely multi-objective optimization on the basis of ratio analysis (MOORA) to solve different multi-objective problems that are encountered in the real-time manufacturing industries. This study focuses on the application of MOORA method for solving some non-conventional machining processes that have multiple criteria problems. Wire-Electric Discharge Machining (WEDM), Plasma Arc Cutting (PAC), Electro Chemical Micro Machining (ECMM), Electro Chemical Machining (ECM), Abrasive Jet Machining (AJM), Abrasive Water Jet Machining (AWJM), Ultrasonic Machining (USM), Laser Beam Machining (LBM) and Laser cutting process are the major attentions in the current study. Total nine NTM multi-criteria problems which include selection of proper machining parameters have been studied. The optimal settings of input variables obtained by using MOORA method nearly tie with those derived by the earlier investigators.

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37

Chang, Yoonsang, and Myeong-Woo Cho. "Flexible optimization of machining variables using constrained R-T characteristic curve." International Journal of Production Research 39, no. 17 (January 2001): 4065–75. http://dx.doi.org/10.1080/00207540110071787.

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38

Ma, Zhi Yan, Guang You Yang, and Xu Wu Su. "Research on Technologies of Augmented Reality for CNC Machining Process Simulation." Key Engineering Materials 579-580 (September 2013): 276–82. http://dx.doi.org/10.4028/www.scientific.net/kem.579-580.276.

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Анотація:

Based on Virtual Numerical Control machining system (VNC), a new method of Augmented Numerical Control machining system (ANC) which aims at the realization of NC machining process simulation in real machining environment is put forward. The System inputs continuous video images of real NC processing environment through camera to identify and locate the major machining and positioning parts of real machine in the image stream. And the virtual parts of VNC will be matched to the corresponding real ones of real machining system to achieve the registration of ANC. The NC system drives the virtual machining models for processing through a real machine. On the other hand, the actual running information of CNC machine are imported into the ANC system to drive some models of process variables such as cutting force, material removal rate, chip shape, tool temperature, cutting tool wear. ANC provides the platform to integrate the geometry and physical simulation based on actual information from real CNC machining environment.

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39

Dhanalakshmi, S., and T. Rameshbabu. "Multi-Aspects Optimization of Process Parameters in CNC Turning of LM 25 Alloy Using the Taguchi-Grey Approach." Metals 10, no. 4 (March 31, 2020): 453. http://dx.doi.org/10.3390/met10040453.

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Анотація:

LM 25 is an aluminum alloy that has numerous applications such as in the manufacturing of automobile components and food industries, and especially in marine and seawater applications, due to its exceptional properties. An exertion has been taken for attaining the best-suited group of machining variables to attain improved and better performance in machining such as increased rate of material removal, lessened roughness values at the machined surface and the total cost incurred during machining. Taguchi’s design methodology has been implemented for devising the experimental combinations and also for single aspects optimization of deemed performance measures. Grey’s theory concept has been adopted for attaining Grey Relational Coefficient values and the values have been further utilized for evolving Grey Relational Grade. Analysis of Variance (ANOVA) has been employed to determine the significance of input process variables on the desired performance measures and interaction analysis also has been performed to determine the interaction effect between the selected process variables. As a result of optimization, the optimal combination of cutting parameters in turning LM25 aluminum alloy is cutting speed (A) = 150.79 m/min, feed (B) = 0.15 mm/min, depth of cut (C) = 0.9 mm and cutting fluid flow rate (D) = 75 mL/h. Compared with the initial parameter settings, surface roughness (Ra) decreases by 67.97%, material removal rate (MRR) increases by 88.12% and total machining cost (TMC) decreases by 93.86%. The proposed approach helps the manufacturer to attain better machining performance at an affordable cost.

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40

Kumar, Rajinder, Neel Kanth Grover, and Amandeep Singh. "Process Optimization of Electric Discharge Machining Using Response Surface Methodology." Applied Mechanics and Materials 813-814 (November 2015): 393–97. http://dx.doi.org/10.4028/www.scientific.net/amm.813-814.393.

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Анотація:

Electric Discharge Machining (EDM) is one of the most commonly used non-traditional machining processes. Complex geometries can be easily manufactured using EDM. Material removal is achieved by producing continuous spark occurring between well shaped tool electrode and work piece. EDM does not involve direct contact of tool and work piece. Machining process involves a number of input variables like, current, voltage, pulse on/off which in turn affect the machining efficiency of EDM. These process parameters must be optimized to attain high material removal rate and low tool wear rate. The present paper presents theoptimization of tool wear rate of copper and brass electrode on machining of EN-47 using Response Surface Methodology (RSM).

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41

Konneh, Mohamed, Mohammad Iqbal, M. Asnawi B. Kasim, and Nurbahiah B. Mohd Isa. "High Speed Milling of Silicon Carbide with Diamond Coated End Mills." Advanced Materials Research 576 (October 2012): 535–38. http://dx.doi.org/10.4028/www.scientific.net/amr.576.535.

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Анотація:

The primary applications of silicon carbide SiC-based materials, which include include micro-structures, optoelectronic devices, high temperature electronics, radiation hard electronics and high power/high frequency devices to name a few have necessitated the need for machining SiC. The paper presents the outcome of milling of silicon carbide using diamond coated end mill under different machining conditions in order to determine the surface roughness parameter after the machining processes. Relationship between the machining parameters and response variables has been established and a mathematical model has been predicted, the minimum roughness value, Rz being 0.19 µm.

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42

Pratap, Raj, and Dr S. K. S. Yadav. "Experimental Study of Electro Discharge Machining (EDM) on Mild Steel (E-250) using Copper Electrode." International Journal for Research in Applied Science and Engineering Technology 11, no. 8 (August 31, 2023): 2184–88. http://dx.doi.org/10.22214/ijraset.2023.55550.

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Анотація:

Abstract: Electro-discharge machining is used for machining different types of hard materials which are electrically conductive and these materials are particularly challenging to manufacture using any other machining method. In electro-discharge machining electrical energy is transformed into thermal energy which is approximately 8000 to 12000 degrees Celsius and due to high thermal energy material melting and vaporising. In electro-discharge machining, three types of electrode materials are used which are copper, brass and graphite, Of all three materials, graphite has the highest electrical conductivity and brass has the lowest electrical conductivity. Electro-discharge machining process suitable for generating complex shapes and profiles. In this paper, a Copper electrode was used for machining mild steel (E-250) and analysed the MRR and Ra with a variation of discharge current keeping other variables constant and studying the consequence of different discharge currents on MRR and Ra.

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43

Izelu, Christopher Okechukwu, and Samuel Chike Eze. "An Investigation on Effect of Depth of Cut, Feed Rate and Tool Nose Radius on Induced Vibration and Surface Roughness during Hard Turning of 41Cr4 Alloy Steel Using Response Surface Methodology." International Journal of Engineering and Technologies 7 (May 2016): 32–46. http://dx.doi.org/10.18052/www.scipress.com/ijet.7.32.

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Анотація:

This paper describes an aspect of a set of turning experiments performed in attempt to model, predict and optimize the machining induced vibration and surface roughness as functions of the machining, tool and work-piece variables during hard turning of 41Cr4 alloy special steel, with standard cutting tool, on a conventional lathe. Amongst others, the input variables of interest include the depth of cut, feed rate and tool nose radius. The response surface methodology, based on central composite design of experiment, was adopted, with analysis performed in Design Expert 9 software environment. Quadratic regression models were suggested, and proved significant by an analysis of variance, for the machining induced vibration of the cutting tool and surface roughness of the work-piece. They also have capability of being used for prediction within limits. Analysis of variance also showed the depth of cut, feed rate and tool nose radius have significant effect on the machining induced vibration and surface roughness. Whereas the depth of cut has dominant effect on the machining induced vibration, the tool nose radius has dominant effect on the surface roughness. The optimum setting of the depth of cut of 1.33095 mm, feed rate of 0.168695 mm/rev, and the tool nose radius of 1.71718 mm is required to minimize the machining induced vibration at 0.08 mm/s2 and surface roughness at 6.056 μmm with a desirability of 0.830.

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44

Izelu, Christopher Okechukwu, and Samuel Chike Eze. "An Investigation on Effect of Depth of Cut, Feed Rate and Tool Nose Radius on Induced Vibration and Surface Roughness during Hard Turning of 41Cr4 Alloy Steel Using Response Surface Methodology." International Journal of Engineering and Technologies 7 (May 16, 2016): 32–46. http://dx.doi.org/10.56431/p-08ad20.

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Анотація:

This paper describes an aspect of a set of turning experiments performed in attempt to model, predict and optimize the machining induced vibration and surface roughness as functions of the machining, tool and work-piece variables during hard turning of 41Cr4 alloy special steel, with standard cutting tool, on a conventional lathe. Amongst others, the input variables of interest include the depth of cut, feed rate and tool nose radius. The response surface methodology, based on central composite design of experiment, was adopted, with analysis performed in Design Expert 9 software environment. Quadratic regression models were suggested, and proved significant by an analysis of variance, for the machining induced vibration of the cutting tool and surface roughness of the work-piece. They also have capability of being used for prediction within limits. Analysis of variance also showed the depth of cut, feed rate and tool nose radius have significant effect on the machining induced vibration and surface roughness. Whereas the depth of cut has dominant effect on the machining induced vibration, the tool nose radius has dominant effect on the surface roughness. The optimum setting of the depth of cut of 1.33095 mm, feed rate of 0.168695 mm/rev, and the tool nose radius of 1.71718 mm is required to minimize the machining induced vibration at 0.08 mm/s2 and surface roughness at 6.056 μmm with a desirability of 0.830.

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45

Rachman, Farizi, Dhika Aditya Purnomo, Ridhani Anita Fajardini, and Rena Riza Umami. "Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method." JTAM (Jurnal Teori dan Aplikasi Matematika) 5, no. 1 (April 17, 2021): 50. http://dx.doi.org/10.31764/jtam.v5i1.3291.

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Анотація:

This research aims to obtain optimal value for the surface roughness of the material AISI P20 on the Electrical Discharge Machining (EDM) Sinking process. In the present research, the Taguchi method is used to investigate the signiﬁcant influence of process variables on the machining performance and determine the combination of process variables on the EDM process. Orthogonal array L18 (21 × 33) based on the Taguchi method is chosen for the design of experiment. The experiment is replicated twice to finding out the influence of four process variables such as type of electrode, voltage gap, on-time, and off-time on the response performance. Machining performance is evaluated by surface roughness as a response variable that had quality characteristics, smaller is better. These experimental data were analyzed using the Signal-to-noise ratio and Analysis of Variance. The analysis results show that the surface roughness is influenced by the type of electrode and on time. Combination of process variables to obtain optimal surface roughness are using graphite electrodes, and setting values of gap voltage 40 volt, on-time 250 μs, and off-time 20 μs. This combination of process variables can be applied to the manufacturing process using EDM sinking in order to produce a good quality product that determined based on the surface roughness value.

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46

Stevenson, Robin, and David A. Stephenson. "The Mechanical Behavior of Zinc During Machining." Journal of Engineering Materials and Technology 117, no. 2 (April 1, 1995): 172–78. http://dx.doi.org/10.1115/1.2804526.

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Анотація:

It is well known that a nonzero force is obtained when cutting forces measured at different feed rates but otherwise constant cutting conditions are extrapolated to zero feed rate. In the literature, this nonzero intercept has been attributed to a ploughing effect associated with the finite sharpness of the cutting tool. However, the standard extrapolation method does not account for other variables such as strain, strain rate and temperature which also vary with feed rate and influence the work material flow stress. In this paper, the apparent flow stresses measured in high and low speed machining tests on zinc are compared with the flow stresses measured in compression tests. The results show that the flow stress measured in cutting is consistent with that measured in compression when all deformation variables are properly accounted for and that, contrary to the results obtained using the extrapolation approach, the ploughing force is negligible.

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47

Qi, H., J. M. Fan, and Jun Wang. "An Experimental Study of the Abrasive Water Jet Micro-Machining Process for Quartz Crystals." Advanced Materials Research 565 (September 2012): 339–44. http://dx.doi.org/10.4028/www.scientific.net/amr.565.339.

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Анотація:

An experimental study of the machining process for micro-channels on a brittle quartz crystal material by an abrasive slurry jet (ASJ) is presented. A statistical experiment design considering the major process variables is conducted, and the machined surface morphology and channelling performance are analysed to understand the micro-machining process. It is found that a good channel top edge appearance and bottom surface quality without wavy patterns can be achieved by employing relatively small particles at shallow jet impact angles. The major channel performance measures, i.e. material removal rate (MRR) and channel depth, are then discussed with respect to the process parameters. It shows that with a proper control of the process variables, the abrasive water jet (AWJ) technology can be used for the micro-machining of brittle materials with high quality and productivity.

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48

Zakaria Mohd Zain, Mir Akmam Noor Rashid, Sher Afghan Khan, and Ahsan Ali Khan. "MRR and TWR Study of Powder Mix EDM and Pure EDM Based on Response Surface Methodology." Journal of Advanced Research in Applied Mechanics 103, no. 1 (April 11, 2023): 13–26. http://dx.doi.org/10.37934/aram.103.1.1326.

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Анотація:

Powder-mixed electrical discharge machining (PMEDM) is the process of enhancing the output of the machined surface by combining dielectric fluid with various types of powders. This process is quickly gaining acceptance in the electrical discharge machining (EDM) sector. The purpose of this study is to determine whether a dielectric fluid containing tantalum carbide (TaC) powder can improve material removal rate (MRR) also lessen tool wear rate (TWR) during the subsequent EDM machining of stainless steel material. During the machining, the material removal rates, tool wear rate, and mathematical models of two different EDM mediums were examined. For the machining procedure, kerosene dielectric fluid containing TaC powder at a concentration of 25.0 g/L was used. The machining input variables were used peak current, pulse on time, and pulse off time. We determined how these variables affected the MRR and TWR of the copper-based EDMed electrode tools. During electrical discharge machining, the MRR for stainless steel (SUS 304) was increased by MRRPMEDM by 4.3 to 5.3% and TWRpEDM was reduced by 37.9% when TaC powder additive was used. Optimized results also show that TWR and maximum MRR can be achieved at 81.98% and 13.779mm3/min respectively with 83.50% desirability whenever the pulse on-time and pulse off-time are 6.20 µs and 6.50 µs respectively. The models are reliable and can be used to forecast the machining responses within the experimental region, it can be said. The MRR and TWR model for EDM with TaC powder additive (MRRPMEDM) identifies current as the most significant factor, followed by pulse on time and pulse off-time.

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49

Han, Jian, Li Ping Wang, Ning Bo Cheng, and Xu Wang. "Thermal Error Modeling of Machine Tools Based on M-RAN." Applied Mechanics and Materials 121-126 (October 2011): 529–33. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.529.

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Анотація:

Thermal error in machine tools is one of the most significant causes of machining errors. This paper presents a new modeling method for machine tool error. Minimal-resource allocating networks (M-RAN) are used to establish the relationships between the temperature variables and thermal errors. Pt-100 thermal resistances and eddy current sensors are used to measure the temperature variables and the thermal errors respectively. A machining center is used to experiment. The test results show that method with minimal-resource allocating networks can predict the thermal errors of the machine accurately.

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50

Jegan, T. M. Chenthil, D. Ravindran, and M. Dev Anand. "ECM Parameters Modeling and Optimization Using WSGA." Applied Mechanics and Materials 423-426 (September 2013): 925–30. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.925.

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Анотація:

Electrochemical machining (ECM) is a non tradition process used for the machining of metal matrix composites. Metal matrix composites are used for applications in aero scope, automobile industries and medical field. Determination of optimal process parameter is difficult in ECM machining process for obtaining maximum Material Removal Rate (MRR) and good Surface Roughness (SR).The multiple regression model was used to obtain the relationship between process parameters and output parameters and Weighted Sum Genetic Algorithm (WSGA) optimization was proposed to optimize the ECM process parameter. .The Voltage, Current, Feed Rate and Electrolyte Concentration are considered as decision variables, MRR and SR are the machining parameters used in the proposed work.

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