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Journal articles on the topic 'Machining - Processes'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

MATSUMURA, Takashi, Motohiro SHIMADA, and Kazunari TERAMOTO. "Analysis of Cutting Processes on Machining Centers(Analytical advancement of machining process)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.3 (2005): 1093–98. http://dx.doi.org/10.1299/jsmelem.2005.3.1093.

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2

Crookall, J. R. "Nontraditional Machining Processes." Precision Engineering 7, no. 1 (1985): 14. http://dx.doi.org/10.1016/0141-6359(85)90073-x.

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3

Ulsoy, A. Galip, and Y. Koren. "Control of Machining Processes." Journal of Dynamic Systems, Measurement, and Control 115, no. 2B (1993): 301–8. http://dx.doi.org/10.1115/1.2899070.

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This paper reviews the important recent research contributions for control of machining processes (e.g., turning, milling, drilling, and grinding). The major research accomplishments are reviewed from the perspective of a hierarchical control system structure which considers servo, process, and supervisory control levels. The use and benefits of advanced control methods (e.g., optimal control, adaptive control) are highlighted and illustrated with examples from research work conducted by the authors. Also included are observations on how significant the research to date has been in terms of in

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4

Grzesik, Wit. "Media-assisted machining processes." Mechanik 91, no. 12 (2018): 1050–56. http://dx.doi.org/10.17814/mechanik.2018.12.186.

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A special group of hybrid assisted processes termed media-assisted processes which various liquid and gaseous media supplied to the cutting zone is highlighted. Special attention is paid on such cooling techniques as high-pressure machining (HPC), high-pressure jet assisted machining (HPJAM), minimum quantity cooling/lubrication (MQC/MQL) and a group of cryogenically cooled machining including such cryogenic media as CO2 snow and liquid nitrogen (LN2). Some important effects resulting from the various cooling strategies are outlined and compared. In particular, quantitative effects concerning

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5

Inasaki, Ichiro. "Towards symbiotic machining processes." International Journal of Precision Engineering and Manufacturing 13, no. 7 (2012): 1053–57. http://dx.doi.org/10.1007/s12541-012-0137-9.

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6

Shvartsburg, L. E., N. A. Ivanova, S. A. Ryabov, et al. "Safety of Machining Processes." Russian Engineering Research 40, no. 12 (2020): 1055–57. http://dx.doi.org/10.3103/s1068798x20120175.

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7

Qin, Yongtao, Liping Zhao, Yiyong Yao, and Damin Xu. "Multistage machining processes variation propagation analysis based on machining processes weighted network performance." International Journal of Advanced Manufacturing Technology 55, no. 5-8 (2010): 487–99. http://dx.doi.org/10.1007/s00170-010-3113-5.

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8

Dondi, Valerio. "Acoustic sensor for monitoring machining processes in machining tools." Journal of the Acoustical Society of America 122, no. 5 (2007): 2502. http://dx.doi.org/10.1121/1.2801788.

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9

Shrivastava, Pankaj K., and Avanish K. Dubey. "Electrical discharge machining–based hybrid machining processes: A review." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 228, no. 6 (2013): 799–825. http://dx.doi.org/10.1177/0954405413508939.

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10

Childs, T. H. C. "Materials Issues in machining and physics and machining processes." Materials & Design 15, no. 1 (1994): 53. http://dx.doi.org/10.1016/0261-3069(94)90062-0.

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11

Rieck, Iris, and Eckhart Uhlmann. "Advanced Machining Processes for CFRP." Advanced Materials Research 1018 (September 2014): 67–74. http://dx.doi.org/10.4028/www.scientific.net/amr.1018.67.

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The processing of fiber reinforced plastics is one of the main research areas at the Institute for Machine Tool and Factory Management of the Technical University of Berlin. In this process new tool concepts and innovative process strategies are developed, tested and prepared for the industrial application. This report presents the latest research results in the field of High-Speed-Cutting of fiber-reinforced plastics.

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12

Shokrani, Alborz, and Dirk Biermann. "Advanced Manufacturing and Machining Processes." Journal of Manufacturing and Materials Processing 4, no. 4 (2020): 102. http://dx.doi.org/10.3390/jmmp4040102.

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13

Schulze, Volker, Frederik Zanger, Benedict Stampfer, et al. "Surface conditioning in machining processes." tm - Technisches Messen 87, no. 11 (2020): 661–73. http://dx.doi.org/10.1515/teme-2020-0044.

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14

Schulze, Volker. "Surface conditioning in machining processes." tm - Technisches Messen 87, no. 11 (2020): 659–60. http://dx.doi.org/10.1515/teme-2020-0069.

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15

Schulze, Volker. "Surface conditioning in machining processes." tm - Technisches Messen 87, no. 12 (2020): 743–44. http://dx.doi.org/10.1515/teme-2020-0071.

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16

Brinksmeier, E., D. A. Lucca, and A. Walter. "Chemical Aspects of Machining Processes." CIRP Annals 53, no. 2 (2004): 685–99. http://dx.doi.org/10.1016/s0007-8506(07)60035-3.

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17

Marinescu,, Ioan, Brian Rowe,, Boris Dimitrov, and, and Ichiro Inasaki. "Tribology of Abrasive Machining Processes." Journal of Manufacturing Science and Engineering 126, no. 4 (2004): 859. http://dx.doi.org/10.1115/1.1819313.

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18

Dornfeld, D. A., Y. Lee, and A. Chang. "Monitoring of Ultraprecision Machining Processes." International Journal of Advanced Manufacturing Technology 21, no. 8 (2003): 571–78. http://dx.doi.org/10.1007/s00170-002-1294-2.

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19

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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20

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

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21

Gökçe, Hakan, Ramazan Yeşilay, Necati Uçak, Ali Teke, and Adem Çiçek. "Improvement of Machining Processes: A Case Study." Academic Perspective Procedia 2, no. 3 (2019): 634–41. http://dx.doi.org/10.33793/acperpro.02.03.67.

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In material removal processes, determination of optimal machining strategy is a key factor to increase productivity. This situation is gaining more importance when machining components with complex geometry. The current practice in the determination of machining strategy mostly depends on the experience of the machine operator. However, poorly designed machining processes lead to time-consuming and costly solutions. Therefore, the improvement of machining processes plays a vital role in terms of machining costs. In this study, the machining process of a boom-body connector (GGG40) of a backhoe

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22

Han, Zi Xu, Li Bao An, and Hai Dong Zhao. "Progress of Traditional Ultra-Precision Machining Processes." Advanced Materials Research 753-755 (August 2013): 314–17. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.314.

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Ultra-precision machining is in the forefront of advanced manufacturing technology and also will become the basis of future manufacturing technology. Ultra-precision machining already has turned into the enabling technology to success in the international competition. Some new progresses in traditional ultra-precision machining processes including processing and measuring techniques, machining equipment, and analysis methods are introduced in this paper. Components with high form accuracy and good surface roughness are widely applied to precision apparatuses. Structured surfaces can be acquire

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23

Liu, D. Y., Ping Yu Jiang, and L. Guo. "Study on Machining Error Propagation for Multistage Processes." Applied Mechanics and Materials 10-12 (December 2007): 379–84. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.379.

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Digital action mechanism of machining error propagation has been a hot research topic in recent years. A complicated machining system usually contains multiple stages. Basing on analyzing digital behaviors of machining process flow, a methodology of machining error monitoring and control is put forward, which is based on dynamic programming. Under this framework, state of machining feature is described with vector matrices, and then differential transition matrices are used to represent the influences of error sources on machining feature quality of workpiece. Basing on this, a general error p

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24

Vallejo, Antonio J., Ruben Morales-Menendez, and Ricardo Ramírez-Mendoza. "Surface Roughness Modelling in Machining Processes." IFAC Proceedings Volumes 42, no. 4 (2009): 325–30. http://dx.doi.org/10.3182/20090603-3-ru-2001.0167.

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25

ABDEL MAHBOUD, A. "IMPROVING ACCURACY OF ELECTROCHEMICAL MACHINING PROCESSES." International Conference on Applied Mechanics and Mechanical Engineering 2, no. 2 (1986): 91–100. http://dx.doi.org/10.21608/amme.1986.57187.

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26

Kundrák, János, Athanasios Mamalis, and Viktor Molnár. "The efficiency of hard machining processes." Nanotechnology Perceptions 15, no. 2 (2019): 121–42. http://dx.doi.org/10.4024/n05ku19a.ntp.15.02.

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27

Chavoshi, Saeed Zare, and Xichun Luo. "Hybrid micro-machining processes: A review." Precision Engineering 41 (July 2015): 1–23. http://dx.doi.org/10.1016/j.precisioneng.2015.03.001.

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28

Fergani, Omar, Zhipeng Pan, Steven Y. Liang, Zoubir Atmani, and Torgeir Welo. "Microstructure Texture Prediction in Machining Processes." Procedia CIRP 46 (2016): 595–98. http://dx.doi.org/10.1016/j.procir.2016.05.012.

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29

Lauwers, B. "Surface Integrity in Hybrid Machining Processes." Procedia Engineering 19 (2011): 241–51. http://dx.doi.org/10.1016/j.proeng.2011.11.107.

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30

Reverberi, A. P., D. M. D’Addona, A. A. G. Bruzzone, R. Teti, and B. Fabiano. "Nanotechnology in machining processes: recent advances." Procedia CIRP 79 (2019): 3–8. http://dx.doi.org/10.1016/j.procir.2019.02.002.

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31

Gieras, Jacek F. "Linear Electric Motors in Machining Processes." Journal of international Conference on Electrical Machines and Systems 2, no. 4 (2013): 380–89. http://dx.doi.org/10.11142/jicems.2013.2.4.380.

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32

Fetsak, S. I., Yu V. Idrisova, R. G. Kudoyarov, R. R. Latypov, and A. G. Omel’chak. "Dynamic processes in high-speed machining." Russian Engineering Research 37, no. 5 (2017): 438–39. http://dx.doi.org/10.3103/s1068798x17050100.

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33

Kandráč, Ladislav, Ildikó Maňková, and Marek Vrabeľ. "Cutting edge preparation in machining processes." Scientific Letters of Rzeszow University of Technology - Mechanics 30, no. 85(2/2013) (2013): 149–59. http://dx.doi.org/10.7862/rm.2013.14.

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34

Wolff, Valéry, Arnaud Lefebvre, and Jean Renaud. "Maps of Dispersions for Machining Processes." Concurrent Engineering 14, no. 2 (2006): 129–39. http://dx.doi.org/10.1177/1063293x06066196.

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35

Verma, Girish Chandra, Pulak Mohan Pandey, and Uday Shanker Dixit. "Ultrasonic-assisted machining processes: a review." International Journal of Mechatronics and Manufacturing Systems 12, no. 3/4 (2019): 227. http://dx.doi.org/10.1504/ijmms.2019.10025069.

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36

Dixit, Uday Shanker, Pulak Mohan Pandey, and Girish Chandra Verma. "Ultrasonic-assisted machining processes: a review." International Journal of Mechatronics and Manufacturing Systems 12, no. 3/4 (2019): 227. http://dx.doi.org/10.1504/ijmms.2019.103479.

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37

Miguélez, H., C. Santiuste, José Díaz, X. Soldani, and J. L. Cantero. "Three-Dimensional Modeling of Machining Processes." Advanced Materials Research 498 (April 2012): 255–60. http://dx.doi.org/10.4028/www.scientific.net/amr.498.255.

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Despite of the efforts focused on the improvement of simulation of machining processes, this problem remains still open. In the case of metal cutting, 2D (two dimensional) modeling has been extensively used for decades in the prediction of difficult to measure variables in metal cutting. Although more complex 3D (three dimensional) approaches have been carried out they have still high computational cost. On the other hand long fiber reinforced composites are extensively used in industry; however the numerical modeling of composite cutting is still poorly developed, and mainly focused on 2D app

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38

Liu, Y., T. Cheng, and L. Zuo. "Adaptive Control Constraint of Machining Processes." International Journal of Advanced Manufacturing Technology 17, no. 10 (2001): 720–26. http://dx.doi.org/10.1007/s001700170117.

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39

Vaz, M., D. R. J. Owen, V. Kalhori, M. Lundblad, and L. E. Lindgren. "Modelling and Simulation of Machining Processes." Archives of Computational Methods in Engineering 14, no. 2 (2007): 173–204. http://dx.doi.org/10.1007/s11831-007-9005-7.

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40

Hegab, H. A., B. Darras, and H. A. Kishawy. "Towards sustainability assessment of machining processes." Journal of Cleaner Production 170 (January 2018): 694–703. http://dx.doi.org/10.1016/j.jclepro.2017.09.197.

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41

Quintana, Guillem, and Joaquim Ciurana. "Chatter in machining processes: A review." International Journal of Machine Tools and Manufacture 51, no. 5 (2011): 363–76. http://dx.doi.org/10.1016/j.ijmachtools.2011.01.001.

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42

Denkena, B., H. W. Hoffmeister, M. Reichstein, S. Illenseer, and M. Hlavac. "Micro-machining processes for microsystem technology." Microsystem Technologies 12, no. 7 (2006): 659–64. http://dx.doi.org/10.1007/s00542-006-0089-z.

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43

GUIOTOKO, Eric H., Hideki AOYAMA, and Noriaki SANO. "Optimization of hole making processes considering machining time and machining accuracy." Journal of Advanced Mechanical Design, Systems, and Manufacturing 11, no. 4 (2017): JAMDSM0048. http://dx.doi.org/10.1299/jamdsm.2017jamdsm0048.

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44

Yadav, Ravindra Nath. "Electro-chemical spark machining–based hybrid machining processes: Research trends and opportunities." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 233, no. 4 (2018): 1037–61. http://dx.doi.org/10.1177/0954405418755825.

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Shaping of the difficult-to-machine non-conductive materials such as glass, quartz and ceramic is much difficult and uneconomical by existing machining processes. As a result, wide applicabilities of these materials are still limited. Even though these materials are highly required in the field of the modern industries. To overcome the problem, a new machining method has been proposed by researchers by combining the features of electro-chemical machining and electro-discharge machining. Such combined machining process is called as electro-chemical spark machining process. Such developed machin

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45

Singh, Palwinder. "Modern Developments in Magnetic Field Assisted Abrasive Flow Machining Processes." Journal of Advanced Research in Production and Industrial Engineering 06, no. 01 (2019): 1–7. http://dx.doi.org/10.24321/2456.429x.201901.

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46

Ruszaj, Adam, Sebastian Skoczypiec, and Dominik Wyszyński. "Recent Developments in Abrasive Hybrid Manufacturing Processes." Management and Production Engineering Review 8, no. 2 (2017): 81–90. http://dx.doi.org/10.1515/mper-2017-0020.

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AbstractRecent dynamic development of abrasive hybrid manufacturing processes results from application of a new difficult for machining materials and improvement of technological indicators of manufacturing processes already applied in practice. This tendency also occurs in abrasive machining processes which are often supported by ultrasonic vibrations, electrochemical dissolution or by electrical discharges. In the paper we present the review of new results of investigations and new practical applications of Abrasive Electrodischarge (AEDM) and Electrochemical (AECM) Machining.

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47

Ling, Tsz Yan, and David Y. H. Pui. "Characterization of Nanoparticles from Abrasive Waterjet Machining and Electrical Discharge Machining Processes." Environmental Science & Technology 47, no. 22 (2013): 12721–27. http://dx.doi.org/10.1021/es402593y.

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48

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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49

Khan, Aqib Mashood, Saqib Anwar, Munish Kumar Gupta, et al. "Energy-Based Novel Quantifiable Sustainability Value Assessment Method for Machining Processes." Energies 13, no. 22 (2020): 6144. http://dx.doi.org/10.3390/en13226144.

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Sustainability assessments of cooling/lubrication-assisted advanced machining processes has been demanded by environment control agencies because it is an effective management tool for improving process sustainability. To achieve an effective and efficient sustainability evolution of machining processes, there is a need to develop a new method that can incorporate qualitative indicators to create a quantifiable value. In the present research work, a novel quantifiable sustainability value assessment method was proposed to provide performance quantification of the existing sustainability assess

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50

Rahman, Mustafizur. "Special Issue on Micro/Nano Machining – Processes, Systems and Control." International Journal of Automation Technology 5, no. 1 (2011): 3. http://dx.doi.org/10.20965/ijat.2011.p0003.

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In recent years, the trend in miniaturization of products is pervasive in areas such as information technology, biotechnology, environmental and medical industries. Micro-machining is the key supporting technology that has to be developed to meet the challenges posed by the requirements of product miniaturization and industrial realization of nanotechnology. Micro-machining techniques can be carried out by techniques based on energy beams (beam-based micro-machining) or solid cutting tools (tool-based micro-machining). Beambased micro-machining have some limitations due to poor control of 3D s

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