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Academic literature on the topic 'MACHINING VARIABLES'

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Published: 11 September 2023

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Journal articles on the topic "MACHINING VARIABLES"

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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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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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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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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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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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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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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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Paul, Lijo, and 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 (July 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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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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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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Dissertations / Theses on the topic "MACHINING VARIABLES"

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Duong, Tan Quang. "Commande à gains variables de l’erreur de contour pour l’usinage multiaxes." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLC009/document.

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Les techniques d’usinage avancées sont un élément indispensable du développement des industries manufacturières. L’une de ces techniques, l’usinage à grande vitesse, constitue le sujet principal de cette thèse de doctorat. Ainsi, l’objectif majeur des travaux vise à améliorer la précision de contour dans le contexte de l’usinage multiaxes à grande vitesse de surfaces de forme libre, en agissant directement au niveau des boucles de commande d’axe. Pour cela, une première étape consiste à élaborer une stratégie permettant d’estimer le plus précisément possible l’erreur de contour pour différentes configurations de l’outil. Cette erreur de contour est ensuite minimisée grâce à l’adaptation hors ligne, pour un profil de pièce donné, des gains proportionnel et d’anticipation des régulateurs des boucles d’asservissement de la position de chaque axe. L’adaptation de ces gains est réalisée via un algorithme d’optimisation à l’aide d’un modèle non-linéaire du comportement de la machine, en considérant en particulier les frottements sur chacun des axes. L’optimisation permettant d’obtenir les gains des correcteurs des boucles de régulation tient compte des contraintes en termes de limitations cinématiques des axes (vitesse, accélération et jerk), de stabilité des boucles d’asservissement et de limites au niveau des courants des moteurs. Afin d’en faciliter la mise en oeuvre dans un cadre industriel, les stratégies développées s’avèrent directement implantables au sein des commandes numériques actuellement sur le marché, exploitant toutes les possibilités de la structure de commande classique de l’entraînement d’axe
The advanced machining techniques are always the backbone of the manufacturing industries. Among such techniques, high speed machining is the main subject of this PhD thesis. Indeed, the main objective of this work is to improve the contouring accuracy in multi-axis high speed machining of free-form surfaces, directly acting inside the axis control loops. To do that, a first step aims at elaborating a strategy to estimate as accurately as possible the contour error for different tool configurations. This contour error is then minimized by means of an off-line adaptation for a given profile of the proportional and feedforward gains of the axis position loop controllers. This gain adaptation is performed via an optimization algorithm that considers a nonlinear model of the machine behaviour, in particular including friction related to each axis. This optimization leading to the controllers gains takes into account several constraints, including the axis kinematic (velocity, acceleration and jerk) limitations, the stability of the controlled loops and the motor current limits. Finally, to help their integration within an industrial framework, the developed strategies can be directly implemented in commercial CNC, by exploiting all possibilities of the classical control structure of axis drive
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Hussein, Wessam Mahmoud Elbestawi Mohamed A. A. Veldhuis Stephen C. "Machining process monitoring using multivariate latent variable methods." *McMaster only, 2007.

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Nagaraj, Arjun. "ANALYSIS OF SURFACE INTEGRITY IN MACHINING OF CFRP UNDER DIFFERENT COOLING CONDITIONS." UKnowledge, 2019. https://uknowledge.uky.edu/me_etds/142.

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Carbon Fiber Reinforced Polymers (CFRP) are a class of advanced materials widely used in versatile applications including aerospace and automotive industries due to their exceptional physical and mechanical properties. Owing to the heterogenous nature of the composites, it is often a challenging task to machine them unlike metals. Drilling in particular, the most commonly used process for component assembly is critical especially in the aerospace sector which demands parts of highest quality and surface integrity. Conventionally, all composites are machined under dry conditions. While there are drawbacks related to dry drilling, for example, poor surface roughness, there is a need to develop processes which yield good quality parts. This thesis investigates the machining performance when drilling CFRP under cryogenic, MQL and hybrid (CryoMQL) modes and comparing with dry drilling in terms of the machining forces, delamination, diameter error and surface integrity assessment including surface roughness, hardness and sub-surface damage analysis. Additionally, the effect of varying the feed rate on the machining performance is examined. From the study, it is concluded that drilling using coolant/ lubricant outperforms dry drilling by producing better quality parts. Also, varying the feed rate proved to be advantageous over drilling at constant feed.
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Laforce, Francois. "Zlepšení výroby aeronautické součásti." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-229843.

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Since aircrafts manufacturers intend to produce low consumption and efficient aircrafts, parts become more and more difficult to machine. Some processes like „air machining“ enables a one-step production for complex aluminium alloy shaped parts. Although the assembly offers a large access to cutting tool, the lack of stiffness for large parts, and especially for thin-walled aeronautics parts implies strong vibrations during machining. The aim of the study is to solve these difficulties in order to keep productivity and improve surface quality. Further innovative solutions are considered like modal analysis, in-phase machining, spindle speed variation, 3 flutes end mill and variable helix angle mill. All propositions are tested on DMG 65 machine tool with Siemens 840D controller. Although vibrations are intrinsic to flexible parts, surface quality has been improved with higher cutting continuity and variable helix angle cutting tool.
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YADAV, MANISH KUMAR. "EFFECTS OF MACHINING VARIABLES ON SURFACE ROUGHNESS IN WIRE-EDM." Thesis, 2015. http://dspace.dtu.ac.in:8080/jspui/handle/repository/14366.

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ABSTRACT Accompanying the development of industry, the demands for alloy materials having high hardness, toughness and impact resistance are increasing. Wire EDM machines are used to cut conductive metals of any hardness or that are difficult or impossible to cut with traditional methods. The machines also specialize in cutting complex contours or fragile geometries that would be difficult to be produced using conventional cutting methods. Machine tool industry has made exponential growth in its manufacturing capabilities in last decade but still machine tools are not utilized at their full potential. This limitation is a result of the failure to run the machine tools at their optimum operating conditions. The problem of arriving at the optimum levels of the operating parameters has attracted the attention of the researchers and practicing engineers for a very long time. The literature survey has revealed that a little research has been conducted to obtain the optimal levels of machining parameters that yield the best machining quality in machining of difficult to machine materials like die steel AISI D3. The die steel AISI D3 is extensively used for hot-work forging, extrusion, manufacturing punching tools, mandrels, mechanical press forging die, plastic mould and die-casting dies, aircraft landing gears, helicopter rotor blades and shafts, etc. The consistent quality of parts being machined in wire electrical discharge machining is difficult because the process parameters cannot be controlled effectively. These are the biggest challenges for the researchers and practicing engineers. Manufacturers try to ascertain control factors to improve the machining quality based on their operational experiences, manuals or failed attempts. Keeping in view the applications of material AISI D3 die steel, it has been selected and has been machined on wire-cut EDM (EZEECUT PLUS WIRECUT EDM) of Electronica Machine Tools Limited. The objective of the present work was to investigate the effects of the various WEDM process parameters on the surface roughness and to obtain the optimal sets of process parameters so that the quality of machined parts can be optimized. The working ranges and levels of the WEDM process parameters are found using one factor at a time approach. The linear regression analysis has been used to investigate the effects of the WEDM process parameters and subsequently to predict sets of optimal parameters for best surface finish.
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YADAV, MANEESH KUMAR. "EFFECTS OF MACHINING VARIABLES ON SURFACE ROUGHNESS IN WIRE-EDM OF AISI D3." Thesis, 2011. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19702.

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Accompanying the development of industry, the demands for alloy materials having high hardness, toughness and impact resistance are increasing. Wire EDM machines are used to cut conductive metals of any hardness or that are difficult or impossible to cut with traditional methods. The machines also specialize in cutting complex contours or fragile geometries that would be difficult to be produced using conventional cutting methods. Machine tool industry has made exponential growth in its manufacturing capabilities in last decade but still machine tools are not utilized at their full potential. This limitation is a result of the failure to run the machine tools at their optimum operating conditions. The problem of arriving at the optimum levels of the operating parameters has attracted the attention of the researchers and practicing engineers for a very long time. The literature survey has revealed that a little research has been conducted to obtain the optimal levels of machining parameters that yield the best machining quality in machining of difficult to machine materials like die steel AISI D3. The die steel AISI D3 is extensively used for hot-work forging, extrusion, manufacturing punching tools, mandrels, mechanical press forging die, plastic mould and die-casting dies, aircraft landing gears, helicopter rotor blades and shafts, etc. The consistent quality of parts being machined in wire electrical discharge machining is difficult because the process parameters cannot be controlled effectively. These are the biggest challenges for the researchers and practicing engineers. Manufacturers try to ascertain control factors to improve the machining quality based on their operational experiences, manuals or failed attempts. Keeping in view the applications of material AISI D3 die steel, it has been selected and has been machined on wire-cut EDM (EZEECUT PLUS WIRECUT EDM) of Electronica Machine Tools Limited. The objective of the present work was to investigate the effects of the various WEDM process parameters on the surface roughness and to obtain the optimal sets of process parameters so that the quality of machined parts can be optimized. The working ranges and levels of the WEDM process parameters are found using one factor at a time approach. The linear regression analysis has been used to investigate the effects of the WEDM process parameters and subsequently to predict sets of optimal parameters for best surface finish.
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Praharaj, Ami t. Kumar. "Simulation of Electrolyte Flow Pattern and Variation of MRR With Machining Variables in ECM for L-shaped Tool using CFD." Thesis, 2018. http://ethesis.nitrkl.ac.in/9702/1/2018_MT_216ME2374_AKPraharaj_Simulation.pdf.

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Electrochemical machining is one of the non-traditional machining processes. This is based on the principle of Faraday’s laws of electrolysis. ECM is very much helpful in machining complex and complicated shapes and difficult to cut materials. One of the main advantages of ECM over other machining process is negligible tool wear as there is no direct contact between tool and workpiece. But sometimes because of inappropriate design of complicated shaped tools there are chances of passivation and overheating of electrolyte which further leads to poor machining. So the analysis of this flow pattern is very much necessary to counteract this overheating tendency of the electrolyte. This research work is mainly to study the flow pattern by determining the variation in pressure pattern, temperature pattern, velocity pattern, turbulent kinetic energy pattern, and the current density distribution from the brine groove inlet to the outer wall. Simulation of this CFD problem is done by ANSYS-CFX 15.0 and FLUENT software. Two phase flow analysis of the electrolyte is done in this simulation. Geometrical modelling is done by ansys design modeler in which workpiece is taken as circular in shape with 60 mm diameter 20 mm height made with iron, electrolyte is taken as 20% brine solution and tool is taken as L-shaped copper tool. Material removal rate (MRR) of this model is calculated by varying the electrolyte flow velocity, inter electrode gap (IEG), feed rate and applied voltage. The result shows that material removal rate (MRR) increases with an increase in flow velocity, concentration of electrolyte, feed rate, applied voltage and reduction in inter electrode gap (IEG)
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Chen, Hsin-Hung, and 陳信宏. "On the design of tool profiles for machining line generated variable pitch helicoids." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/22367187145909021800.

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Sheng, Yu-Chun, and 盛玉君. "Studies on the Numerical Control Programming for Machining Variable Pitch Lead Screw on Four-AXIS MACHINE." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/38829237727428045433.

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碩士
國立成功大學
機械工程研究所
81
In this thesis , two kinds of tool path generation methods are developed for machining Variable Pitch Lead Screw with four cylindrical meshing elements (V.P.L.S.) on four-axis numerical control machine . The first method employs end-mill cutter , According to the geometry of V.P.L.S. mechanism , the machine tool settings is calculated and the tool path is generated , A 4-axis machine center with angle head attachment is used for the machining of the screw The second method employs ball-end mill cutter, Through the coordinate transformation , the surface normal vector operation and the tool offset calculation , this new method combined surface generating with surface sculpturing for the V.P.L.S. surface . Finally , an example for N C milling of Variable Pitch Lead Screw with four cylindrical meshing elements is presented . The results show that the mathematical errors of V.P.L.S. surface can be controlled within tolerance by the proposed methods .
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HONG, CHING-HUA, and 洪清華. "Application of Deep Learning to the Intelligent Control of Wire Electrical Discharge Machining of Variable Thickness Workpiece." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/72npak.

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碩士
國立臺灣大學
機械工程學研究所
107
The purpose of this study is to establish a deep learning intelligent control system that can combine processing efficiency, stability and kerf consistency in variable thickness processing. In the past, the wire electrical discharge machining Control for variable thickness workpiece, and focus on improving processing efficiency and stability. The research on the problem that the kerf difference affects the accuracy of the variable thickness workpiece is relatively lacking. The true straightness is not good after processing, and it may lead to error fitting of future workpieces. Deep Learning is used to automatically extract features that are representative of data characteristics by transforming data through multiple nonlinear hidden layers, that is, from a variety of discharge signals that are highly correlated with the thickness of the workpiece. The recessive feature function has strong robustness and is not sensitive to noise or some of extreme values, so the thickness of the workpiece can be accurately known. The second stage is the setting of processing parameters. In the past, it relied on experienced operators. Therefore, the deep learning technique was used again to normalize the hidden features of the input data, so that the model output is like a experience operator to determination what the parameters should be setting. Intelligent control strategy not only reduce the operator''s technical threshold, but also achieve a goal of uniform material removal rate during the trim cutting and reduce the occurrence of line marks. The experimental results show that the deep learning workpiece thickness online estimation system established in this study which can accurately estimate the thickness of the workpiece, and the processing parameter intelligent control system can adjust the discharge TOFF and TAOFF according to different workpiece thicknesses. The discharge frequency is controlled within the desired value, and the processing efficiency can be effectively improved when the thickness of the workpiece is thin to thick; when the thickness of the workpiece is thick to thin, the feed rate will be accelerated and the wire is broken by discharge concentration phenomenon. On the other hand, the strategy of this study effectively balances the kerf uniformity, that is, the average value and variation of the kerf of each class thickness can be effectively maintained within a stable value when processing different workpiece thicknesses.
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Book chapters on the topic "MACHINING VARIABLES"

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Davis, Rahul, Abhishek Singh, Tanya Singh, Subham Chhetri, V. Vikali Sumi, Alomi P. Zhimomi, and Stephen Dilip Mohapatra. "Optimization of Input Control Variables in Electric Discharge Machining of Inconel-718." In Lecture Notes in Mechanical Engineering, 541–49. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2696-1_53.

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Thellaputta, Gopala Rao, P. S. C. Bose, C. S. P. Rao, and C. S. Raju. "Effect of Machining Variables on Cutting Temperature While Rotary Milling of Inconel 625." In Lecture Notes on Multidisciplinary Industrial Engineering, 27–36. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7643-6_3.

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Sonawane, Sachin Ashok, and Akshay P. Pawar. "Effect of Cutting Variables of End Milling Process on Surface Roughness and Machining Vibrations." In Techno-Societal 2018, 661–70. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16962-6_67.

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Santhi Priya, P., Subramanyam Pavuluri, and Yogesh Madaria. "Experimental Investigations of Process Variables on Wire Electrical Discharge Machining (WEDM) of AISI 52100 Steel." In Lecture Notes in Mechanical Engineering, 571–80. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7909-4_53.

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Pramanik, D., A. S. Kuar, and D. Bose. "Effects of Wire EDM Machining Variables on Material Removal Rate and Surface Roughness of Al 6061 Alloy." In Renewable Energy and its Innovative Technologies, 231–41. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2116-0_19.

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Sharma, Khushboo, Jai Kishan Sambharia, and Alok Khatri. "Optimization of Process Variables in Plasma Arc Machining of Inconel-718 Alloy Using Taguchi with Grey Relational Analysis." In Lecture Notes in Mechanical Engineering, 37–58. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-9117-4_4.

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Das, Sudhansu Ranjan, and Anshuman Das. "Study the Influences of Various Input Variables on Material Removal Rate During μEDM Machining of Super Alloy Material." In Lecture Notes in Mechanical Engineering, 681–92. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4606-6_62.

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Madhavarao, S., Ravi Varma Penmetsa, Ch Rama Bhadri Raju, and Hema T. Raju Gottumukkala. "Optimization of Process Variables in Abrasive Water Jet Machining of Nimonic C-263 Super Alloy Using Taguchi Method." In Advances in Sustainability Science and Technology, 167–77. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4321-7_15.

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Yadav, Rajat, and Pradeep Kumar Singh. "Variation in Unevenness of Surface in Machining Ti–6Al–4 V Due to Change in Key Variables of Micro-Electric Discharge Milling Process." In Lecture Notes in Mechanical Engineering, 1083–91. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2188-9_99.

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Nandurkar, Santosh, Sachin Kulkarni, Tushar Hawal, Niranjan Pattar, and Nagaraj Kelageri. "Investigation of Effect of EDM Process Variables on Material Removal Rate and Tool Wear Rate in Machining of EN19 Steel Using Response Surface Methodology." In Lecture Notes in Mechanical Engineering, 71–82. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2278-6_7.

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Conference papers on the topic "MACHINING VARIABLES"

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Cong, W. L., Q. Feng, Z. J. Pei, T. W. Deines, and C. Treadwell. "Dry Machining of Carbon Fiber Reinforced Plastic Composite by Rotary Ultrasonic Machining: Effects of Machining Variables." In ASME 2011 International Manufacturing Science and Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/msec2011-50116.

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Rotary ultrasonic machining (RUM) has been used to drill holes in brittle, ductile, and composite materials. However, all these experiments were conducted with help of water or oil based coolant. This paper presents an experimental study on RUM of carbon fiber reinforced plastic (CFRP) composite using cold air as coolant. It reports effects of machining variables (ultrasonic power, spindle speed, and feedrate) on outputs (cutting force, torque, surface roughness, and burning) in RUM of CFRP using vortex-tube (VT) generated cold air as coolant.
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Chen, Xiaoxu, Hui Wang, Yingbin Hu, Dongzhe Zhang, Weilong Cong, and Anthony R. Burks. "Rotary Ultrasonic Machining of CFRP Composites: Effects of Machining Variables on Workpiece Delamination." In ASME 2019 14th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/msec2019-3019.

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Abstract Carbon fiber reinforced plastic (CFRP) composites were widely used in machinery, automobile, and aerospace industries due to the superior properties of high stiffness, high strength-to-weight ratio, high fatigue resistance, and good wear resistance. In these applications, hole making on CFRP composites was needed for assembly purpose. In different hole making processes, delamination was considered as a crucial issue, leading to premature failure of products. Compared with the conventional CFRP hole making processes (such as twist drilling, milling, grinding, etc.), rotary ultrasonic machine (RUM) had advantages of low cutting force and torque, low surface roughness, and long tool life. Therefore, numbers of researchers worked on RUM processes. The reported investigations mainly focused on the effects of input variables (including machining variables, tool variables, and workpiece properties) on cutting force, torque, surface roughness, and tool life, etc. In addition, effects of cutting tool variables on delamination were also reported. However, there were no reported investigations on effects of machining variables on delamination in RUM of CFRP composites. This investigation, for the first time, reported the effects of ultrasonic power, tool rotation speed, and feedrate on delamination as well as its associated cutting force. Based on the experiments, the results showed that delamination decreased with ultrasonic power increasing, tool rotation speed increasing, or feedrate decreasing. The relationships between cutting force and delamination were also studied.
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Qin, Na, Z. J. Pei, and D. M. Guo. "Ultrasonic-Vibration-Assisted Grinding of Titanium: Cutting Force Modeling With Design of Experiments." In ASME 2009 International Manufacturing Science and Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/msec2009-84325.

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Titanium and its alloys (Ti) have wide applications in industry. However, since Ti is notorious for its poor machinability, their applications have been hindered by the high cost and low efficiency. Ultrasonic-vibration-assisted grinding (UVAG) is a hybrid machining process that combines the material removal mechanisms of diamond grinding and ultrasonic machining, and it is a cost-effective machining process for Ti. The relations between cutting force and input variables have been investigated and reported. But these relations have been studied by changing one variable at time. Therefore, the interactions between cutting force and input variables have not been revealed. In this paper, a two-level five-factor full factorial design is used to study the relations between cutting force and input variables based on a cutting force model for UVAG of Ti. The main effects of these variables, and two-factor interactions and three-factor interactions of these variables are also revealed.
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Ning, Fuda, and Weilong Cong. "Rotary Ultrasonic Machining of CFRP: Design of Experiment With a Cutting Force Model." In ASME 2015 International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/msec2015-9227.

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Drilling is one of very important machining processes in many applications of carbon fiber reinforced plastic (CFRP) composites. Rotary ultrasonic machining (RUM) has been successfully used in drilling of CFRP composites to overcome poor machinability. Cutting force is one of the most important output variables for evaluating drilling process, since it will greatly influence cutting temperature, tool wear, and surface conditions. Currently, there are no reported investigations on effect of input variables on cutting force using design of experiment (DOE) method in RUM of CFRP composites. Five-variable two-level full factorial design has been conducted to study cutting force based on a mechanistic predictive model in RUM of CFRP composites. Main effects as well as interaction effects of five process variables (vibration amplitude, tool rotation speed, feedrate, abrasive size, and abrasive concentration) on cutting force are revealed.
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Zeng, W. M., Z. C. Li, N. J. Churi, Z. J. Pei, and C. Treadwell. "Experimental Investigation Into Rotary Ultrasonic Machining of Alumina." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-61700.

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Many experimental studies have been conducted to explore the relations between control variables and process outputs in rotary ultrasonic machining (RUM). However, there are few reports on the comparison between RUM and conventional diamond drilling. In this paper, the cutting force and surface roughness are compared when machining alumina with RUM method and with conventional diamond drilling method. Furthermore, the effects of the control variables (rotational speed, feed rate, and ultrasonic power) on RUM outputs (such as cutting force and surface roughness) are studied. It is found that in comparison with conventional diamond drilling, the cutting force can be reduced significantly and the surface roughness can be improved by using RUM. It is also found that rotational speed, feed rate, and ultrasonic power have significant effects on RUM process.
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Lo, Chih-Hao, Jun Ni, and Jingxia Yuan. "Thermal Sensor Placement Strategy for Machine Error Compensation." In ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-0355.

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Abstract A method was developed to determine the suitable temperature variables for thermal error modeling on a machine structure. An optimality analysis of the best temperature variables is discussed using the analytical solutions of a one-dimensional spindle model. Finite element analyses for transient heat transfer and thermoelastic deformation are also performed on the column structure of a machining center. Different combinations of heat sources are applied to simulate diverse machining operations. From the results of FEA runs, 155 sets of 411 nodal temperatures and the 7 transformed error components are used as the database for multivariate temperature variable selection. Through an optimization method of searching unknown-order variables, 19 optimal sensor locations for the 7 error components are obtained and categorized into 6 clusters. Experiments and comparisons are presented to validate the applicability of the optimal sensor placement strategy. Superior to empirical method with trial-and-error sensor placement, this method is capable to select thermal variables globally and increases the robustness of thermal error models.
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Kumanotani, Maho, Hitoshi Kusino, and Keiichi Nakamoto. "Proposal of a Tool Path Generation Method to Ensure Workpiece Stiffness for Efficient Rough Machining." In JSME 2020 Conference on Leading Edge Manufacturing/Materials and Processing. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/lemp2020-8543.

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Abstract Recently, the demand of complex shape parts has increased in the aircraft and medical industries. In these parts machining, the displacement and vibration of workpiece that strongly affect the machining efficiency are induced due to the heavy change of the unmachined workpiece shape and stiffness during rough machining. However, it is difficult to automatically determine machining parameters of operation planning by using a commercial CAM software because there is a large number of combinations. Therefore, in order to improve the efficiency of complex parts machining, the authors proposed a determination method of workpiece shapes during rough machining based on topology optimization relevant to maximizing static stiffness. On the other hand, tool paths that directly affect the workpiece stiffness are not generated automatically to create the calculated workpiece shapes in the previous study. From these reasons, this study proposes a generation method of tool paths by using design variables obtained through the calculation of topology optimization. The tool paths are simply generated based on design variables and enables to ensure the workpiece stiffness during rough machining because design variables are strongly related to the objective function. By conducting a machining experiment assuming complex parts machining, it is confirmed that the proposed method has a potential to realize efficient rough machining.
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Lee, Cheol W. "Multirate Estimation for the Machining Process Under Multirate Noise." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-42187.

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Asynchronous measurement of process output characterizes a typical machining process in batch production. Various sensors are used for in-process measurement of process variables such as powers, forces, and vibration while the quality of parts and the tool conditions can be measured only by the postprocess inspection in most applications. The multirate scheme is being proposed as an efficient tool for integrating real-time sensor signals with postprocess inspection data for estimating immeasurable variables of the machining process. The machining process is subject to the process noise of varying frequencies including the within-cycle drift, cycle-to-cycle variation, and batch-to-batch variation. A multirate observer for simultaneous state and parameter estimation is built after the propagation of errors along a series of machining cycles is derived. Case studies with the grinding process demonstrate the efficacy of the developed algorithm.
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Zhang, Dongzhe, Hui Wang, Yingbin Hu, Xiaoxu Chen, Weilong Cong, and Anthony R. Burks. "Rotary Ultrasonic Machining of CFRP Composites: Effects of Carbon Fiber Reinforcement Structure." In ASME 2019 14th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/msec2019-3014.

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Abstract Carbon fiber reinforced plastic (CFRP) composites have been widely used in many applications due to their superior properties of high strength-weight ratio, high stiffness, and high wear resistance. For assembly purposes, hole making is necessary for different applications of CFRP composites. Rotary ultrasonic machining (RUM) has been proposed and investigated for hole making of CFRP composites. Studies on the effects of machining variables, tool variables, workpiece orientation, and cooling conditions on output variables in RUM of CFRP composites have been investigated. The carbon fiber reinforcement structures of CFRP composites also affect the machining performances and part’s quality. However, there is no reported investigation on studying carbon fiber reinforcement structures’ influences in RUM of CFRP composites. Experiments were conducted for this paper to investigate the effects of carbon fiber reinforcement structure on cutting force, torque, and surface roughness. Three major conclusions can be drawn from the results of this experimental investigation. First, CFRP composites with unidirectional structure led to the smallest cutting force and torque, followed by CFRP composites with plain woven structure and twill woven structure. Second, the surface roughness on CFRP composites with plain woven structure was the smallest, followed by the CFRP composites with unidirectional structure and twill woven structure. In addition, CFRP composites with different reinforcement structures have the same tendencies of output variables with different machining variables.
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10

Wentz, John E., and Andrew J. Coleman. "Energy Analysis of Machining and Machining Facilities Based on the Micro-Factory Concept." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7222.

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The micro-factory concept has gained wide support and acceptance based on the ability of small machine tools to accomplish the same tasks as traditionally sized machine tools while using a fraction of the space. Although it is frequently mentioned that a micro-factory is an energy saving endeavor, there is a dearth of hard data on how much energy is actually saved. The intent of this report is to quantify the difference in energy consumed in a micro-factory and a macro-factory though experimentation with a micro- and a macro-mill. This quantification allows for the potential of unit life cycle analyses to be performed in the future. A fluidic channel was machined in workpieces of aluminum and steel by both micro- and macro-mills under a variety of machining conditions and the recorded data has been analyzed to this end. The variables investigated were the spindle speed, the mill type, and the material the cutting process was performed on. The conclusions reached through experimentation were that the micro-mill used between 13.5% and 21.7% of the energy used for the macro-mill. Additionally the energy differences in climate control were investigated for comparable macro- and micro-factories. The mock macro-factory used for this analysis was three times the size of the micro-factory. Due to the larger size of the macro-building, the climate control energy usages were also about three times as high as in the micro-building.
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