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1

Deng, Chao, Yao Xiong, Yuan Hang Wang, and Jun Wu. "Machining Process Parameters Optimization Based on Grid Optimization Algorithm." Advanced Materials Research 562-564 (August 2012): 2021–25. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.2021.

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Machining process parameters directly affect the machining quality and efficiency of heavy-duty CNC machine tools, selecting correctly machining process parameters can improve the machine’s machining performance effectively. This paper presents a machining process parameters optimization method based on grid optimization algorithm for heavy-duty CNC machine tools. In this method, a multi-objective optimization model will be established, which considers not only the linear constrains of machining process parameters, such as machining time and machining cost, but also the non-linear constrain, s
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2

Florin, Chichernea. "Value Analysis and Optimization a Machining Process." Global Journal For Research Analysis 3, no. 3 (2012): 107–11. http://dx.doi.org/10.15373/22778160/mar2014/37.

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3

Urbikain, Gorka, and Daniel Olvera-Trejo. "Special Issue on “Machining Dynamics and Parameters Process Optimization”." Applied Sciences 10, no. 24 (2020): 8908. http://dx.doi.org/10.3390/app10248908.

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4

Mat Deris, Ashanira, Azlan Mohd Zain, Roselina Salehuddin, and Safian Sharif. "Overview of Harmony Search (HS) Algorithm for Green Manufacturing Industries." Applied Mechanics and Materials 815 (November 2015): 413–16. http://dx.doi.org/10.4028/www.scientific.net/amm.815.413.

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The successful optimization process of machining parameters is significantly important to the green manufacturing industries. However, the optimization process of machining problem is difficult to solve using conventional optimization techniques. Hence, the computational approach methodology such as Harmony Search (HS) is considered as an alternative way for optimization process in manufacturing industries. This paper discusses the overview of Harmony Search (HS) to optimize the machining parameters in machining process. Example of previous works that applied HS algorithm in machining optimiza
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5

Zhao, Hang, Jian Guang Li, Ying Xue Yao, and Chang Qing Liu. "Cutting Parameters Optimization for Constant Cutting Force in Milling." Applied Mechanics and Materials 10-12 (December 2007): 483–87. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.483.

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Due to cutting parameters playing an important role in machining economics and machining qualities, much attention has been paid to select optimum cutting parameters. In this paper, cutting parameters optimization for constant cutting force was discussed based-on virtual machining comprehensively. Particle swarm optimization (PSO) was used to seek for the optimal spindle speed and feed rate. The framework of virtual machining based cutting parameters optimization was established. Then two controlled experiments were conducted to demonstrate the effectiveness of cutting parameters optimization
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6

Naresh, P., S. A. Hussain, and B. D. Prasad. "A review on multiple responses process parameters optimization of turning Al-TiC[sub]p[/sub] metal matrix composites." Journal of Achievements in Materials and Manufacturing Engineering 1, no. 80 (2017): 32–40. http://dx.doi.org/10.5604/01.3001.0010.1445.

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Purpose: In this paper the Metal Matrix Composites of AL 7068 and TiC with differentproportions of (2%, 4%, 6%, 8%, and 10%) by using stir casting process, mechanicalproperties and machining responses are investigating.Design/methodology/approach: The samples are fabricated using stir casting, machiningof turning the samples by using Kilster Tool Lathe Dynamometer machining responses wereidentifying.Findings: In this research to find mechanical characterizations like flexural strength, Wearratio, impact strength, hardness, microstructure and also machining responses like surfaceroughness, cutt
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7

Luo, Jiayuan, Xiangyang Xu, Peitang Wei, Chengxiang Shi, and Guofeng Liu. "Machining Path Optimization of 3C Locking Robots Using Adaptive Ant Colony Optimization." Mobile Information Systems 2021 (September 27, 2021): 1–12. http://dx.doi.org/10.1155/2021/2642805.

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The motion smoothness of 3C locking robot directly affects the machining performance. Improving the motion smoothness can optimize the motion trajectory and reduce the processing time. In this paper, a novel machining path optimization model including motion smoothness is built by employing the coordinate boundary of velocity and acceleration after evaluating the machining motion smoothness of the 3C locking robot. Secondly, based on the creation of the ant colony of adaptive function algorithm, the optimization model of the 3C locking robot in the situation of fixed bolt hole position and flo
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8

Matras, Andrzej, and Wojciech Zębala. "Machining Efficiency Increase when Nickel Based Alloy Machining." Solid State Phenomena 261 (August 2017): 22–27. http://dx.doi.org/10.4028/www.scientific.net/ssp.261.22.

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Paper presents some investigations, concerning simulation of the nickel based alloy machining. The aim of the research was an optimization of the cutting data for the purpose to increase the machining efficiency and stabilization of the tangential component of the total cutting force at the assumed level. A dedicated physical material model was built and then included to the simulation strategy. Authors demonstrated the influence of the feed rate optimization on the tangential component of the total cutting force value changes and the chip area and in this way the improvement of the cutting pr
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9

Zhang, Xiao Hong, and Guo Fu Yin. "Milling Parameters Optimization by Grey Relation Theory." Applied Mechanics and Materials 117-119 (October 2011): 1708–13. http://dx.doi.org/10.4028/www.scientific.net/amm.117-119.1708.

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Propose the grey relation theory for influence of electric milling on machining targets in achieving parameter optimization, when an engine cylinder head milling processing under plane milling tool. The experiment was designed via orthogonal experimental design technique. Some parameters such as machining distortion, surface roughness and machining efficiency were chosen as machining targets, and the milling speed, feed per tooth and milling depth were chosen as milling parameters, calculate and analyze the grey relational degree and relational coefficient between milling parameters and machin
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10

Arun Ramnath, R., PR Thyla, N. Mahendra Kumar, and S. Aravind. "Optimization of machining parameters of composites using multi-attribute decision-making techniques: A review." Journal of Reinforced Plastics and Composites 37, no. 2 (2017): 77–89. http://dx.doi.org/10.1177/0731684417732840.

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An in-depth literature survey of machining study on fiber-matrix composites is presented in this review paper. The review work mainly focuses on optimization of machining parameters in composite materials with different machining factors. Conventional machining processes such as turning, drilling and milling as well as composite materials which are reinforced with fibers are considered in this study. Machining aspects on various fiber matrix composites has been carried out over a long period of time. In this review work, conflicting conditions of multi-attribute decision-making techniques and
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11

Wang, Lei, and Jiang Ning Gai. "Study on Optimization of Machining Parameters in Electrochemical Machining." Advanced Materials Research 476-478 (February 2012): 375–78. http://dx.doi.org/10.4028/www.scientific.net/amr.476-478.375.

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In electrochemical machining (ECM) machining accuracy of workpieces is greatly influenced by many machining parameters. In this paper the BP neural network model is employed to optimize machining parameters in ECM. Taking a three dimensional complicated surface as the research object the experimental results have shown that the optimization process can be easily operated and the result is of high precision.
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12

Rahul, Rahul, Chandramani Upadhyay, Saurav Datta, Bibhuti Bhusan Biswal, and Siba Sankar Mahapatra. "Machining Performance Optimization for Electro Discharge Machining of Inconel 625: A Case Experimental Study." International Journal of Materials, Mechanics and Manufacturing 5, no. 4 (2017): 228–30. http://dx.doi.org/10.18178/ijmmm.2017.5.4.324.

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13

Banh, Long Tien, Phan Huu Nguyen, and Cuong Ngo. "Tool wear rate optimization in PMEDM using titanium powder by Taguchi method for die steels." Science and Technology Development Journal 19, no. 2 (2016): 88–97. http://dx.doi.org/10.32508/stdj.v19i2.656.

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Powder mixed electrical discharge maching (PMEDM) is a complex machining process which is controlled by a number of machining parameters. Each machining parameter has its own influence on performance of the process. For achieving the best performance of the electrical discharge machining (EDM) process, it is crucial to carry out parametric design responses such as Metal Removal Rate (MRR), Tool Wear Rate (TWR) and Surface Roughness(SR). The objective of this paper is to optimization of input parameters for the TWR in PMEDM using powder titanium are presented. The Taguchi method was applied to
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14

Sim, Beomsik, and Wonkyun Lee. "Digital Twin Based Machining Condition Optimization for CNC Machining Center." International Journal of Precision Engineering and Manufacturing-Smart Technology 1, no. 2 (2023): 115–23. http://dx.doi.org/10.57062/ijpem-st.2023.0010.

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Optimization of machining conditions is important in determining productivity and machining quality. This study proposes a method for optimizing the machining conditions of a machine tool using a digital twin of a commercial machine tool comprising physical models of a controller, feed drive systems, and cutting load. The digital twin is constructed and evaluated based on machining experiments, and a genetic algorithm is adopted to determine the machining conditions to minimize the machining time and production cost. The optimal feed rate and spindle speed are obtained for each line of the par
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15

Panjabrao Raut, Mr Pritesh. "Optimization of Tool steel." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47693.

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Abstract Electro Discharge Machining (EDM) is a widely adopted non-traditional machining process used for shaping hard and electrically conductive materials, particularly tool steels. The present study focuses on optimizing the EDM process parameters for tool steel (D3) using a Grey-based Taguchi method to achieve improved machining performance. The primary objectives are to maximize the Material Removal Rate (MRR) while minimizing the surface roughness (Ra). Experiments were conducted on an ELECTRAPULS PS 35 EDM machine, utilizing copper electrodes with varying process parameters: voltage, cu
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16

Yu, Ming Rang, Ying Jie Zhang, and Ding Zhang. "Optimization of 3D Pocket Machining Using Multiple Tools." Advanced Materials Research 503-504 (April 2012): 7–10. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.7.

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In numerical control machining, the number and the size of the cutting tools in use have a significant effect on machining efficiency. This paper puts forward a method to select the most appropriate group of cutters for 3D pocket machining using NC machine tools, which aim to minimize the total machining time. Considering the material is removed layer by layer in roughing, three scan-line filling algorithm is proposed to calculate the cutting area of every layer, which is necessary to calculate the machining time. After the total machining time of each group of cutters is calculated, the optim
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17

Li, Jian Guang, Ying Xue Yao, Dong Gao, Chang Qing Liu, and Zhe Jun Yuan. "Cutting Parameters Optimization by Using Particle Swarm Optimization (PSO)." Applied Mechanics and Materials 10-12 (December 2007): 879–83. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.879.

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Cutting parameters play an essential role in the economics of machining. In this paper, particle swarm optimization (PSO), a novel optimization algorithm for cutting parameters optimization (CPO), was discussed comprehensively. First, the fundamental principle of PSO was introduced; then, the algorithm for PSO application in cutting parameters optimization was developed; thirdly, cutting experiments without and with optimized cutting parameters were conducted to demonstrate the effectiveness of optimization, respectively. The results show that the machining process was improved obviously.
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18

Qiao, Li Hong, Quan Wei Hu, and Hong Wei Zhang. "Machining Sequencing Optimization Based on Simulated Annealing Algorithm." Advanced Materials Research 472-475 (February 2012): 1632–36. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.1632.

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Distributed geometric features such as adjacent auxiliary holes with certain tolerance requirements are common geometry to be machined in many complex structural components. The machining sequencing decision of such features has high impact on the machining efficiency of the part. This paper conducted an algorithm to generate optimal machining sequence of the distributed holes in a machined part by using simulated annealing. The procedures of the algorithm were introduced. Distributed holes machining of an example part has been considered in the paper to exam the algorithm to find an optimal m
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19

Park, Hong-seok, Bowen Qi, Duck-Viet Dang, and Dae Yu Park. "Development of smart machining system for optimizing feedrates to minimize machining time." Journal of Computational Design and Engineering 5, no. 3 (2017): 299–304. http://dx.doi.org/10.1016/j.jcde.2017.12.004.

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Abstract Feedrate optimization is an important aspect of getting shorter machining time and increase the potential of efficient machining. This paper presents an autonomous machining system and optimization strategies to predict and improve the performance of milling operations. The machining process was simulated and analyzed in virtual machining framework to extract cutter-workpiece engagement conditions. Cutting force along the cutting segmentation is evaluated based on the laws of mechanics of milling. In simulation, constraint-based optimization scheme was used to maximize the cutting for
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20

Rajesh, A. S., and M. S. Prabuswamy Dr. "An Overview of PSO in Optimization of Machining Parameters." International Journal of Trend in Scientific Research and Development 2, no. 2 (2018): 150–57. https://doi.org/10.31142/ijtsrd8383.

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In the current trends of optimizing machining process parameters, various evolutionary techniques such as Particle Swarm Optimization PSO , Genetic Algorithm GA , Simulated Annealing SA , Ant Colony Optimization ACO and Artificial Bee Colony algorithm ABC have been used. This paper gives an overview of PSO techniques to optimize machining process parameter of both traditional and modern machining. Machining process parameters such as cutting speed, depth of cut and radial rake angle are mostly considered by researchers in order to minimize or maximize machining performances. From the review, t
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21

Szablewski, Piotr, Tomasz Dobrowolski, and Tadeusz Chwalczuk. "Optimization of Inconel 718 milling strategies." Mechanik 92, no. 12 (2019): 824–26. http://dx.doi.org/10.17814/mechanik.2019.12.112.

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This paper applies to the tests of the machining of a part made of supper alloy – nickel alloy – Inconel 718, using a monolithic carbide cutter. The paper includes a different versions of cutting methods with variable cutting parameters and machining strategies. The used sustainable machining process allowed to obtain control over the tool wear.
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22

Pateloup, V., E. Duc, and P. Ray. "Corner optimization for pocket machining." International Journal of Machine Tools and Manufacture 44, no. 12-13 (2004): 1343–53. http://dx.doi.org/10.1016/j.ijmachtools.2004.04.011.

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23

Zhang, JingYing, Steven Y. Liang, Jun Yao, Jia Ming Chen, and Jing Li Huang. "Evolutionary Optimization of Machining Processes." Journal of Intelligent Manufacturing 17, no. 2 (2006): 203–15. http://dx.doi.org/10.1007/s10845-005-6637-z.

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24

Belmokhtar, Sana. "Optimization of modular machining lines." 4OR 6, no. 3 (2007): 315–18. http://dx.doi.org/10.1007/s10288-007-0059-z.

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25

Shandilya, Pragya, Arun Kumar Rouniyar, and D. Saikiran. "Multi-objective parametric optimization on machining of Inconel-825 using wire electrical discharge machining." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 234, no. 20 (2020): 4056–68. http://dx.doi.org/10.1177/0954406220917706.

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Wire electrical discharge machining is a thermal energy-based non-conventional machining process which can machine conductive materials with high precision. In this present work, machining of Inconel-825 was performed using wire electrical discharge machining. Multi-objective parametric optimization was performed for maximum cutting rate and minimum surface roughness using teaching–learning-based optimization, grey relational analysis, and genetic algorithm. Four wire electrical discharge machining parameters, namely spark off time (SOFF), spark on time (SON), peak current (IP), and angle of c
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26

Dhiraj, S. Pachpor*1 &. Dr. P. M. Ardhapurkar2. "OPTIMIZATION OF MACHINING COST FOR TURNING OPERATION USING GENETIC ALGORITHM." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES [NC-Rase 18] (November 22, 2018): 172–78. https://doi.org/10.5281/zenodo.1494032.

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Determining the optimal cutting parameters is having vital importance in any machining process considering the economy of machining operation. In the optimization process, any possible variables will be evaluated based on requirements. In turning operation predicting the proper cutting speed and feed during turning is of great importance as it helps in setting the appropriate cutting parameters before machining starts in order to optimize the machining cost. The Genetic Algorithm (GA) is used for optimization of complex problems in many applications. The paper deals with the optimization of ma
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27

S Chougale, Sagar, and A. N Chapgaon. "Optimization of Machining Parameter on Vertical Machining Center of FG 250 Casting for Surface Roughness." International Journal of Scientific Engineering and Research 8, no. 1 (2020): 11–13. https://doi.org/10.70729/20012001.

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28

Ma, Zi Qin, Peng Zhang, Meng Gu, et al. "Process Route Optimization for Machining Center NC Milling Manufacturing." Applied Mechanics and Materials 455 (November 2013): 561–67. http://dx.doi.org/10.4028/www.scientific.net/amm.455.561.

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There are some characteristics about CNC milling machining centers, such as the procedures are concentrated, the procedure steps are complex, the machining cost is expensive and so on. A mathematical model was established to optimize the process route for machining center NC milling manufacturing. It wants to make the time of machining a single part is shorter or the cost of machining a single part is lower. A using example was given.
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29

Kurita, Hirokazu, and Toshiyuki KIYOTO. "Optimization of machining condition with quality engineering for MQL machining." Proceedings of Conference of Hokuriku-Shinetsu Branch 2004.41 (2004): 137–38. http://dx.doi.org/10.1299/jsmehs.2004.41.137.

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30

Kaladhar, M. "Optimization of machining parameters when machining beyond recommended cutting speed." World Journal of Engineering 17, no. 5 (2020): 739–49. http://dx.doi.org/10.1108/wje-01-2020-0018.

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Purpose Even though austenitic stainless steels have been extensively used in industries, owing to some of the characteristics of the material, its performance in machining is difficult to understand, in particular at high cutting speeds. There is no availability of dependable and in-depth studies pertinent to this matter. In this work, performance of AISI 304 austenitic stainless steel was studied in terms of surface roughness (Ra) and material removal rate (MRR) at high cutting speeds. Subsequently, parametric optimization and prediction for responses were carried out. Design/methodology/app
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31

Varghese, Vinay, M. R. Ramesh, and D. Chakradhar. "Experimental investigation and optimization of machining parameters for sustainable machining." Materials and Manufacturing Processes 33, no. 16 (2018): 1782–92. http://dx.doi.org/10.1080/10426914.2018.1476760.

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32

., Vipin, R. S. Mishra, and Ranganath M. S. "Optimization of Machining cost and time in Heavy Machining Operation." International Journal of Advance Research and Innovation 2, no. 3 (2014): 160–64. http://dx.doi.org/10.51976/ijari.231424.

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Investigation has been done to determine the optimal machining cost and time parameters for multi-pass operations with carbide tool (P-40) on cast steel material. The experiments were carried out on double column heavy duty turning and boring machine and were analyzed. The temperature, cutting force, surface roughness and tool life equations were obtained in terms of speed, feed and depth of cut. The expressions so developed were used to further optimize the numbers of tool passes to minimize the cost and time.
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33

Li, J. G., H. Zhao, Y. X. Yao, and C. Q. Liu. "Off-line optimization on NC machining based on virtual machining." International Journal of Advanced Manufacturing Technology 36, no. 9-10 (2007): 908–17. http://dx.doi.org/10.1007/s00170-006-0915-6.

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34

Bhatia, Anmol, Gagan Vijay Singh, Anmol Madaan, and Akansha Bhatia. "An Experimental Study to Achieve Minimum Surface Roughness While Machining P20 Tool Steel Using Wire EDM." International Journal of Advance Research and Innovation 5, no. 2 (2017): 153–59. http://dx.doi.org/10.51976/ijari.521727.

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There is a rapid increase in the usage of hard materials. The conventional machining process has been left behind by complex and intricate part machining. Such complex machining of hard materials via conventional machining methods does often lead to poor quality characteristics such as low surface roughness. Thus, to achieve the goal of better quality characteristics while machining hard materials, non-conventional machining processes come into play. Wire Electric Discharge Machining (Wire-EDM), is an example of such non-conventional machining processes. This paper highlights a research analys
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35

Buzatu, Constantin, Adela Eliza Dumitrascu, Dorin Ion Dumitrascu, and Iulian Orzan. "Contributions to Multi-Criteria Optimization of Cutting Processing." Applied Mechanics and Materials 657 (October 2014): 48–52. http://dx.doi.org/10.4028/www.scientific.net/amm.657.48.

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Based on the experimental research and of theoretical studies in the paper it is presented recommendations and possibilities for the multicriteria optimization of the machining processes. For the application, it is analyzed in this way, the case of the turning process, in special the operation of roughness. The results of the research are analyzed, in special, with the help of suggestive graphs, based on it is presented recommendations for the optimizations of the design and technological process for the machining production from energy consumption, costs and productivity point of view.
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36

Durairaj, M., A. K. S. Ansari, and M. H. Gauthamkumar. "Parametric optimization of wire cut electrical discharge machining." International Journal of Engineering & Technology 3, no. 2 (2014): 212. http://dx.doi.org/10.14419/ijet.v3i2.1807.

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Wire Electrical Discharge Machining is a manufacturing process whereby a desired shape is obtained using electrical discharges (or) by repetitive spark cycle. Precision and intricate machining are the strengths. Machining parameters tables provided by the machine tool manufacturers often do not meet the operator requirements. Selection of optimum machining and machining parameters combinations is needed for obtaining higher cutting efficiency and accuracy. In this present study, machining is done using Wire-Cut EDM and optimization of surface roughness is done using Taguchis design of experime
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37

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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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.
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38

Lan, Tian-Syung. "Dynamic MRR Function Optimization Using Calculus of Variations." Mathematical Problems in Engineering 2010 (2010): 1–12. http://dx.doi.org/10.1155/2010/671062.

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A dynamic machining model to optimize the control of material removal rate (MRR) for a cutting tool undergoing the considerations of fixed tool life and maximum machining rate is established in this paper. This study not only applies material removal rate mathematically into the objective function, but also implements Calculus of Variations to comprehensively optimize the control of material removal rate. In addition, the optimal solution for the dynamic machining model to gain the maximum profit is provided, and the decision criteria for selecting the optimal solution of the dynamic machining
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39

Wang, Shih-Ming, Chun-Yi Lee, Hariyanto Gunawan, and Chin-Cheng Yeh. "An Accuracy-Efficiency-Power Consumption Hybrid Optimization Method for CNC Milling Process." Applied Sciences 9, no. 7 (2019): 1495. http://dx.doi.org/10.3390/app9071495.

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This study proposes a hybrid optimization method which can help users to find optimal cutting parameters which will provide better efficiency and lower power consumption for a milling process. Empirical models including performance-power consumption characteristic curves of servo motors were built, and an optimization algorithm adopting the empirical models with procedure guiding function was developed. The empirical models were built based on the measurements from planned machining experiments with different combination of machining parameters including spindle speed, feedrate, and chip load,
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40

S, Rajesh A., and Dr M. S. Prabuswamy. "An Overview of PSO in Optimization of Machining Parameters." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (2018): 150–57. http://dx.doi.org/10.31142/ijtsrd8383.

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41

Zhu, Li Feng, and Yan Zhang. "Application of Genetic Algorithm in Cutting Parameter Optimization." Advanced Materials Research 1082 (December 2014): 138–42. http://dx.doi.org/10.4028/www.scientific.net/amr.1082.138.

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Process parameters optimization is an important problem in numerical control machining, through the analysis of various factors affecting the cutting effect in cutting process, a mathematical model of cutting parameter optimization in NC machining is established and the constraint conditions are also determined in the paper. The article puts forward using genetic algorithm to realize the optimization of mathematical model, and the optimization analysis results are verified in practical processing. The experimental results show that the optimized cutting parameters can satisfy machining request
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42

Sumesh, C. S., and Ajith Ramesh. "Optimization and finite element modeling of orthogonal turning of Ti6Al4V alloys: A comparative study of different optimization techniques." Engineering Solid Mechanics 11, no. 1 (2023): 11–22. http://dx.doi.org/10.5267/j.esm.2022.11.002.

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The main goal of this research is to compare the various optimization strategies (Response Surface Methodology, Taguchi, and Teaching Learning Based Optimization) for orthogonal turning of Hard to Machine materials. The workpiece material in this work is Ti6Al4V alloys. After selecting cutting speeds in the High-Speed Machining range, orthogonal turning tests are performed on the material for a specific combination of machining parameters – Depth of Cut, Cutting Speed, and, Feed Rate. A Lathe Tool Dynamometer is used to record the cutting forces from the trials. After combining Johnson Cook Ma
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43

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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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 applica
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Zhang, Xing, Zhao Zhao, Zhuocheng Guo, and Wanhua Zhao. "Research on machining parameter optimization in finishing milling with multiple constraints." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 236, no. 6-7 (2021): 968–80. http://dx.doi.org/10.1177/09544054211057989.

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High efficiency and high precision milling, as the eternal goal of CNC machining, needs to balance many constraints for selecting the most reasonable processing parameters. This paper presents an efficient machining parameter optimization method for finishing milling operation with multiple constraints. Firstly, under the multiple constraints of parameter feasible region, milling force, milling stability, roughness, and machining contour accuracy, a multi-variable parameter optimization model with machining efficiency as the objective is established. A four level cycle optimization strategy ha
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45

Wang, Ming Hai, Zhong Hai Liu, and Wei Wang. "Study on Precision Machining Titanium Alloy Thin-Walled Parts." Advanced Materials Research 314-316 (August 2011): 1778–82. http://dx.doi.org/10.4028/www.scientific.net/amr.314-316.1778.

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In order to obtain the aims of weight reduction, efficiency increase and quality assurance of thin-walled parts of aircraft engine, the titanium alloy thin-walled parts are machined by precision machining method in the experiment. In this paper the precision machining method is used to cut titanium alloy thin-walled parts. The data of surface roughness is chosen as constraint conditions, and machining parameters will be optimized. The optimization parameters is feasible in this experiment, the optimization method is helpful to improve machining parameters and machining technology of titanium a
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Mehrvar, Ali, Ali Basti, and Ali Jamali. "Optimization of electrochemical machining process parameters: Combining response surface methodology and differential evolution algorithm." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 231, no. 6 (2016): 1114–26. http://dx.doi.org/10.1177/0954408916656387.

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Electrochemical machining is a unique prevalent nonconventional manufacturing process used in different industries involving various process parameters, which greatly influence machining performance. Therefore, selection of proper and optimal parameters setting is a challenging issue. In this paper, differential evolution algorithm is applied to look for the optimum solution to this problem. Four parameters, i.e. voltage, tool feed rate, electrolyte flow rate, and electrolyte concentration; and two machining criteria, i.e. material removal rate and surface roughness (Ra) are considered as inpu
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47

Saedon, J. B., Norkamal Jaafar, Roseleena Jaafar, Nor Hayati Saad, and Mohd Shahir Kasim. "Modeling and Multi-Response Optimization on WEDM Ti6Al4V." Applied Mechanics and Materials 510 (February 2014): 123–29. http://dx.doi.org/10.4028/www.scientific.net/amm.510.123.

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Wire electrical discharge machining (WEDM) is a material removal process of electrically conductive materials by the thermo-electric source of energy which is extensively used in machining of materials for a highly precision productivity. This work presents the machining of titanium alloy (TI-6AL-4V) using WEDM with a brass wire diameter of 0.25mm.The objective of this work is to study the influence of three machining parameters, namely peak current (IP), feed rate (FC) and wire tension (WT) to cutting speed and surface roughness. Response Surface Methodology was used to develop second order m
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Zhang, Chen. "Off-Line Feedrate Optimization Based on Simulation of Cutting Forces." Key Engineering Materials 407-408 (February 2009): 408–11. http://dx.doi.org/10.4028/www.scientific.net/kem.407-408.408.

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The strategies of selection of feedrate are studied in the ball-end machining process. The optimization algorithm utilizes the objective requirements of a line of NC program to set constraints relation between cutting force and feedrate and optimizes feedrate by controlling the variety ranges of the instantaneous cutting force specified in the cutting forces simulation. Off-line feedrate optimization software for complex sculptured is developed. For a line of NC program, the developed software calculates instantaneous cutting force and an optimization algorithm is used to acquire desired feedr
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Chirita, Bogdan, Catalin Tampu, Eugen Herghelegiu, and Cosmin Grigoras. "Modelling and optimization of magnesium alloy milling parameters." International Journal of Modern Manufacturing Technologies 13, no. 3 (2021): 29–36. http://dx.doi.org/10.54684/ijmmt.2021.13.3.29.

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In the pursuit to lighter, less consuming products, manufacturers, especially in aviation and automotive industries, are turning more and more to using lightweight alloys such as the ones based on magnesium. Higher requirements for increased productivity have led to concepts like high-speed machining (HSM), high feed machining (HFM) or high-efficiency machining. Tighter regulations concerning requiring for more environmentally friendly industrial processes led to limitations in the use of cooling liquids and a search for cooling methods with less impact (dry cutting, cryogenic cooling, near dr
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Hashish, M. "Optimization Factors in Abrasive-Waterjet Machining." Journal of Engineering for Industry 113, no. 1 (1991): 29–37. http://dx.doi.org/10.1115/1.2899619.

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This paper discusses the factors that need to be considered when selecting the operational parameters for abrasive-waterjet (AWJ) machining. Machining applications such as cutting, milling, and turning are considered along with sample data. The effects of different AWJ parameters on both the functional performance of the AWJ system components and the material removal process are discussed. Factors for optimizing these parameters include hardware limitations, high-pressure-related phenomena, and the performance interaction among the different nozzle components. Due to the large number of parame
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