Using an Adaptive Network-based Fuzzy Inference System to Estimate the Vertical Force in Single Point Incremental Forming

Sever Gabriel Racz, Radu Eugen Breaz, Octavian Bologa, Melania Tera, Valentin Stefan Oleksik

Abstract


Manufacturing processes are usually complex ones, involving a significant number of parameters. Unconventional manufacturing processes, such as incremental forming is even more complex, and the establishment of some analytical relationships between parameters is difficult, largely due to the nonlinearities in the process. To overcome this drawback, artificial intelligence techniques were used to build empirical models from experimental data sets acquired from the manufacturing processes. The approach proposed in this work used an adaptive network-based fuzzy inference system to extract the value of technological force on Z-axis, which appears during incremental forming, considering a set of technological parameters (diameter of the tool, feed and incremental step) as inputs. Sets of experimental data were generated and processed by means of the proposed system, to make use of the learning ability of it to extract the empirical values of the technological force from rough data.

Keywords


adaptive network-based fuzzy inference system, CNC milling machines, incremental forming, technological force

Full Text:

PDF

References


Aerens, R.; Eyckens, P.; Van Bael, A.; Duflou, J. R. (2010); Force prediction for single point incremental forming deduced from experimental and FEM observations, International Journal of Advanced Manufacturing Technology, 46(9-12), 969–982, 2010.
https://doi.org/10.1007/s00170-009-2160-2

Behera, A.K.; De Sousa R.A.; Ingarao, G.; Oleksik, V. (2017); Single point incremental forming: An assessment of the progress and technology trends from 2005 to 2015, Journal of Manufacturing Processes, 27, 37–62, 2017.
https://doi.org/10.1016/j.jmapro.2017.03.014

Breaz, R.; Bologa, O.; Tera, M.; Racz, G. (2013); Determination of Technological Forces in the Incremental Forming Process, Applied Mechanics and Materials, 371, 133–137, 2013.

Caydas, U.; Hascalik, A.; Ekici, S. (2009); An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM, Expert Systems with Applications, 36, 6135-6139, 2009.
https://doi.org/10.1016/j.eswa.2008.07.019

Ceretti, E.; Giardini, C.; Attanasio, A. (2004); Experimental and simulative results in sheet incremental forming on CNC machines, Journal of Materials Processing Technology, 152(2), 176–184, 2004.
https://doi.org/10.1016/j.jmatprotec.2004.03.024

Ciupan, E.; Lungu, F.; Ciupan, C. (2015); ANN Training Method with a Small Number of Examples Used for Robots Control, International Journal of Computers Communications & Control, 10(5), 643–653, 2015.
https://doi.org/10.15837/ijccc.2015.5.2027

Duflou, J. R.; Szekeres, A.; Vanherck, P. (2005); Force Measurements for Single Point Incremental Forming: An Experimental Study, Advanced Materials Research, 6-8, 441–448, 2005.

Dzitac, I.; Filip, F.G.; Manolescu, M.J. (2017); Fuzzy logic is not fuzzy: World-renowned computer scientist Lotfi A. Zadeh, International Journal of Computers Communications & Control, 12(6), 748–789, 2017.
https://doi.org/10.15837/ijccc.2017.6.3111

Dzitac, I. (2015); The fuzzification of classical structures: A general view, International Journal of Computers Communications & Control, 10(6), 772–788, 2015.
https://doi.org/10.15837/ijccc.2015.6.2069

Gatea, S.; Ou, H.; Mccartney, G. (2016); Review on the influence of process parameters in incremental sheet forming, International Journal of Advanced Manufacturing Technology, 87, 479–499, 2016.
https://doi.org/10.1007/s00170-016-8426-6

Haidegger, T.; Kovacs, L.; Precup, R.-E.; Benyo, B.; Benyo, Z.; Preitl, S. (2012); Simulation and control for telerobots in space medicine, Acta Astronautica, 181(1), 390–402, 2012.

Herrera-Viedma, E.; Lopez-Herrera, A.G. (2010); A review on information accessing systems based on fuzzy linguistic modelling, International Journal of Computational Intelligence Systems, 3(4), 420–437, 2010.
https://doi.org/10.1080/18756891.2010.9727711

Hyacinth Suganthi, X.; Natarajan, U.; Sathiyamurthy, S.; Chidambaram, K. (2013); Prediction of quality responses in micro-EDM process using an adaptive neuro-fuzzy inference system (ANFIS) model, International Journal of Advanced Manufacturing Technology, 68, 339-347, 2013.
https://doi.org/10.1007/s00170-013-4731-5

Jeswiet, J.; Micari, F.; Hirt, G.; Bramley A.; Duflou, J.; Allwood, J.(2005); Asymmetric Single Point Incremental Forming of Sheet Metal, Annals of CIRP, 54, 623–650, 2005.

Jiao, Y.; Lei, S.; Pei, Z.J.; Lee, E.S. (2004); Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations, International Journal of Machine Tools and Manufacture, 44(15), 1643–1651, 2004.
https://doi.org/10.1016/j.ijmachtools.2004.06.004

Kumanan, S.; Jesuthanam, C. P. (2008); Ashok Kumar, R.; Application of multiple regression and adaptive neuro fuzzy inference system for the prediction of surface roughness, International Journal of Advanced Manufacturing Technology, 35, 778-788, 2008.
https://doi.org/10.1007/s00170-006-0755-4

Li, Y.; Liu, Z.; Lu, H.; Daniel, W. J. T.; Liu, S.; Meehan, P. A. (2014); Efficient force prediction for incremental sheet forming and experimental validation, International Journal of Advanced Manufacturing Technology, 73, 571-587, 2014.
https://doi.org/10.1007/s00170-014-5665-2

Micari, F.; Ambrogio, G.; Filice, L. (2007); Shape and dimensional accuracy in single point incremental forming: State of the art and future trends, Journal of Materials Processing Technology, 191(1-3), 390-395, 2007.
https://doi.org/10.1016/j.jmatprotec.2007.03.066

Oprea, M.; Mihalache, S. F.; Popescu, M. (2017); Computational Intelligence-based PM2.5 Air Pollution Forecasting, International Journal of Computers Communications & Control, 12(3), 365–380, 2017.
https://doi.org/10.15837/ijccc.2017.3.2907

Perez-Santiago, R.; Bagudanch FrigolA and I.; Garcia-Romeu de Luna, M.L. (2011); Force Modeling in Single Point Incremental Forming of Variable Wall Angle Components, Key Engineering Materials, 473, 833-840, 2011.
https://doi.org/10.4028/www.scientific.net/KEM.473.833

Precup, R.-E.; Hellendoorn, H. (2011); A survey on industrial applications of fuzzy control, Computers in Industry, 62, 213-226, 2011.
https://doi.org/10.1016/j.compind.2010.10.001

Salahshoor, K.; Kordestani, M.; Khoshro, M.S. (2010); XFault detection and diagnosis of an industrial steam turbine using fusion of SVM (support vector machine) and ANFIS (adaptive neuro-fuzzy inference system) classifiers, Energy, 35, 5472–5482, 2010.
https://doi.org/10.1016/j.energy.2010.06.001

Schafer, T.; Schraft, R.D. (2005); Incremental sheet metal forming by industrial robots, Rapid Prototyping Journal, 11(5), 278–286, 2005.
https://doi.org/10.1108/13552540510623585

Tera, M.; Breaz, R.E.; Bologa, O.; Racz, S.G.(2015); Developing a Knowledge Base about the Technological Forces within the Asymmetric Incremental Forming Process, Key Engineering Materials, 651, 1115-1121, 2015.

Tseng, T.-L.; Konada, U.; Kwon, Y. (2016); A novel approach to predict surface roughness in machining operations using fuzzy set theory, Journal of Computational Design and Engineering, 3, 1-13, 2016.
https://doi.org/10.1016/j.jcde.2015.04.002

Velosa De Sena, J.I. (2015); Advanced numerical framework to simulate Incremental Forming Processes, Ph.D. Thesis, University of Aveiro, Portugal, 2015.




DOI: https://doi.org/10.15837/ijccc.2019.1.3489



Copyright (c) 2019 Sever Gabriel Racz, Radu Eugen Breaz, Octavian Bologa, Melania Tera, Valentin Stefan Oleksik

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

CC-BY-NC  License for Website User

Articles published in IJCCC user license are protected by copyright.

Users can access, download, copy, translate the IJCCC articles for non-commercial purposes provided that users, but cannot redistribute, display or adapt:

  • Cite the article using an appropriate bibliographic citation: author(s), article title, journal, volume, issue, page numbers, year of publication, DOI, and the link to the definitive published version on IJCCC website;
  • Maintain the integrity of the IJCCC article;
  • Retain the copyright notices and links to these terms and conditions so it is clear to other users what can and what cannot be done with the  article;
  • Ensure that, for any content in the IJCCC article that is identified as belonging to a third party, any re-use complies with the copyright policies of that third party;
  • Any translations must prominently display the statement: "This is an unofficial translation of an article that appeared in IJCCC. Agora University  has not endorsed this translation."

This is a non commercial license where the use of published articles for commercial purposes is forbiden. 

Commercial purposes include: 

  • Copying or downloading IJCCC articles, or linking to such postings, for further redistribution, sale or licensing, for a fee;
  • Copying, downloading or posting by a site or service that incorporates advertising with such content;
  • The inclusion or incorporation of article content in other works or services (other than normal quotations with an appropriate citation) that is then available for sale or licensing, for a fee;
  • Use of IJCCC articles or article content (other than normal quotations with appropriate citation) by for-profit organizations for promotional purposes, whether for a fee or otherwise;
  • Use for the purposes of monetary reward by means of sale, resale, license, loan, transfer or other form of commercial exploitation;

    The licensor cannot revoke these freedoms as long as you follow the license terms.

[End of CC-BY-NC  License for Website User]


INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL (IJCCC), With Emphasis on the Integration of Three Technologies (C & C & C),  ISSN 1841-9836.

IJCCC was founded in 2006,  at Agora University, by  Ioan DZITAC (Editor-in-Chief),  Florin Gheorghe FILIP (Editor-in-Chief), and  Misu-Jan MANOLESCU (Managing Editor).

Ethics: This journal is a member of, and subscribes to the principles of, the Committee on Publication Ethics (COPE).

Ioan  DZITAC (Editor-in-Chief) at COPE European Seminar, Bruxelles, 2015:

IJCCC is covered/indexed/abstracted in Science Citation Index Expanded (since vol.1(S),  2006); JCR2018: IF=1.585..

IJCCC is indexed in Scopus from 2008 (CiteScore2018 = 1.56):

Nomination by Elsevier for Journal Excellence Award Romania 2015 (SNIP2014 = 1.029): Elsevier/ Scopus

IJCCC was nominated by Elsevier for Journal Excellence Award - "Scopus Awards Romania 2015" (SNIP2014 = 1.029).

IJCCC is in Top 3 of 157 Romanian journals indexed by Scopus (in all fields) and No.1 in Computer Science field by Elsevier/ Scopus.

 

 Impact Factor in JCR2018 (Clarivate Analytics/SCI Expanded/ISI Web of Science): IF=1.585 (Q3). Scopus: CiteScore2018=1.56 (Q2);

SCImago Journal & Country Rank

Editors-in-Chief: Ioan DZITAC & Florin Gheorghe FILIP.