Skip to main content
SpringerLink
Log in

Case of Study

  • Chapter
  • First Online:
Hybrid Modeling and Optimization of Manufacturing

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSCOMPUTAT))

  • 1076 Accesses

Abstract

This chapter presents a case of study exemplifying the combined application of the finite element method (FEM) and artificial intelligence (AI) based tool in modeling and optimization of manufacturing process. In the study, modeling of an orthogonal cutting process of AISI 1045 steel is carry out by using the FEM. Outcomes of the model, in terms of cutting forces and tool wear are related to the experimental factors (feed, velocity and rake angle) through neural networks models. Finally, a multi-objective optimization process is defined and executed in order to obtain the most convenient factors for this specific process, on different workshop conditions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • S.A. Iqbal, P.T. Mativenga, M.A. Sheikh, Characterization of machining of AISI 1045 steel over a wide range of cutting speeds. Part 2: evaluation of flow stress models and interface friction distribution schemes. Proc. Inst. Mech. Eng. B-J Eng. 221, 917–926 (2007). doi:10.1243/09544054JEM797

    Article  Google Scholar 

  • S.P.F.C. Jasper, J.H. Dautzenberg, Material behaviour in conditions similar to metal cutting: flow stress in the primary shear zone. J. Mater. Process. Tech. 122, 322–330 (2002). doi:10.1016/S0924-0136(01)01228-6

    Article  Google Scholar 

  • R. Quiza, M. Rivas, E. Alfonso, Genetic algorithm-based multi-objective optimization of cutting parameters in turning processes. Eng. Appl. Artif. Intell. 19, 127–133 (2006)

    Article  Google Scholar 

  • Y.-C. Yen, J. Söhner, B. Lilly, T. Altan, Estimation of tool wear in orthogonal cutting using the finite element analysis. J. Mater. Process. Tech. 146, 82–91 (2004). doi:10.1016/S0924-0136(03)00847-1

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Matanzas, Autopista a Varadero, 44740, Matanzas, Cuba

    Ramón Quiza

  2. Department of Mechanical Engineering, University of Matanzas, Autopista a Varadero, km 3½, 44740, Matanzas, Cuba

    Omar López-Armas

  3. Department of Mechanical Engineering, University of Aveiro, Campus Santiago, 3810-193, Aveiro, Portugal

    J. Paulo Davim

Authors
  1. Ramón Quiza
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Omar López-Armas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. Paulo Davim
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2012 The Author(s)

About this chapter

Cite this chapter

Quiza, R., López-Armas, O., Davim, J.P. (2012). Case of Study. In: Hybrid Modeling and Optimization of Manufacturing. SpringerBriefs in Applied Sciences and Technology(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28085-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28085-6_4

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28084-9

  • Online ISBN: 978-3-642-28085-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation