IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v158y2014icp345-358.html
   My bibliography  Save this article

Comparative study of 3- and 5-axis CNC centers for free-form machining of difficult-to-cut material

Author

Listed:
  • Zębala, Wojciech
  • Plaza, Malgorzata

Abstract

This paper examines the cost effectiveness of 3- versus 5-axis machines for the machining of a turbine blade made of alloy steel EN 34CrNiMo6. The acceptable surface finish cannot be achieved when a free surface is machined on a 3-axis CNC center due to the variation of the tool׳s position in relation to the part׳s surface. A feed-rate adjustment algorithm is proposed in this paper as a way to compensate for that limitation. To that end, the following two research questions are addressed: (1) if the algorithm is used, can the required surface finish be achieved on a 3-axis CNC center, and (2) which of two alternatives: a 3-axis (assuming the algorithm is executed) or 5-axis CNC center (without the algorithm) will be more cost effective?

Suggested Citation

  • Zębala, Wojciech & Plaza, Malgorzata, 2014. "Comparative study of 3- and 5-axis CNC centers for free-form machining of difficult-to-cut material," International Journal of Production Economics, Elsevier, vol. 158(C), pages 345-358.
    • Handle: RePEc:eee:proeco:v:158:y:2014:i:c:p:345-358
    DOI: 10.1016/j.ijpe.2014.08.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527314002643
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2014.08.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Plaza, Malgorzata & Ngwenyama, Ojelanki K. & Rohlf, Katrin, 2010. "A comparative analysis of learning curves: Implications for new technology implementation management," European Journal of Operational Research, Elsevier, vol. 200(2), pages 518-528, January.
    2. Folgado, R. & Peças, P. & Henriques, E., 2010. "Life cycle cost for technology selection: A Case study in the manufacturing of injection moulds," International Journal of Production Economics, Elsevier, vol. 128(1), pages 368-378, November.
    3. Langmaak, Stephan & Wiseall, Stephen & Bru, Christophe & Adkins, Russell & Scanlan, James & Sóbester, András, 2013. "An activity-based-parametric hybrid cost model to estimate the unit cost of a novel gas turbine component," International Journal of Production Economics, Elsevier, vol. 142(1), pages 74-88.
    4. Quintana, Guillem & Ciurana, Joaquim, 2011. "Cost estimation support tool for vertical high speed machines based on product characteristics and productivity requirements," International Journal of Production Economics, Elsevier, vol. 134(1), pages 188-195, November.
    5. Qian, Li & Ben-Arieh, David, 2008. "Parametric cost estimation based on activity-based costing: A case study for design and development of rotational parts," International Journal of Production Economics, Elsevier, vol. 113(2), pages 805-818, June.
    6. Kovac, Pavel & Sidjanin, Leposava, 1997. "Investigation of chip formation during milling," International Journal of Production Economics, Elsevier, vol. 51(1-2), pages 149-153, August.
    7. Abdel-Malek, Layek & Asadathorn, Nutthapol, 1996. "An analytical approach to process planning with rework option," International Journal of Production Economics, Elsevier, vol. 46(1), pages 511-520, December.
    8. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2004. "Learning curves for processes generating defects requiring reworks," European Journal of Operational Research, Elsevier, vol. 159(3), pages 663-672, December.
    9. Jaber, Mohamad Y. & Khan, Mehmood, 2010. "Managing yield by lot splitting in a serial production line with learning, rework and scrap," International Journal of Production Economics, Elsevier, vol. 124(1), pages 32-39, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Plaza, Malgorzata, 2016. "Balancing the costs of human resources on an ERP project," Omega, Elsevier, vol. 59(PB), pages 171-183.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yamane, Yasuo & Takahashi, Katsuhiko & Hamada, Kunihiro & Morikawa, Katsumi & Nur Bahagia, Senator & Diawati, Lucia & Cakravastia, Andi, 2015. "Developing a plant system prediction model for technology transfer," International Journal of Production Economics, Elsevier, vol. 166(C), pages 119-128.
    2. M. Jaber & Z. Givi, 2015. "Imperfect production process with learning and forgetting effects," Computational Management Science, Springer, vol. 12(1), pages 129-152, January.
    3. Mahesh Kumar Jayaswal & Mandeep Mittal & Isha Sangal, 2021. "Ordering policies for deteriorating imperfect quality items with trade-credit financing under learning effect," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(1), pages 112-125, February.
    4. Jaber, M.Y. & Peltokorpi, J. & Glock, C.H. & Grosse, E.H. & Pusic, M., 2021. "Adjustment for cognitive interference enhances the predictability of the power learning curve," International Journal of Production Economics, Elsevier, vol. 234(C).
    5. Tsionas, Mike G., 2023. "Bayesian learning in performance. Is there any?," European Journal of Operational Research, Elsevier, vol. 311(1), pages 263-282.
    6. Nasser Amaitik & Ming Zhang & Zezhong Wang & Yuchun Xu & Gareth Thomson & Yiyong Xiao & Nikolaos Kolokas & Alexander Maisuradze & Oscar Garcia & Michael Peschl & Dimitrios Tzovaras, 2022. "Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing," Circular Economy and Sustainability, Springer, vol. 2(4), pages 1425-1444, December.
    7. Muhammad Babar Ramzan & Shehreyar Mohsin Qureshi & Sonia Irshad Mari & Muhammad Saad Memon & Mandeep Mittal & Muhammad Imran & Muhammad Waqas Iqbal, 2019. "Effect of Time-Varying Factors on Optimal Combination of Quality Inspectors for Offline Inspection Station," Mathematics, MDPI, vol. 7(1), pages 1-18, January.
    8. Anzanello, Michel J. & Fogliatto, Flavio S. & Santos, Luana, 2014. "Learning dependent job scheduling in mass customized scenarios considering ergonomic factors," International Journal of Production Economics, Elsevier, vol. 154(C), pages 136-145.
    9. Johnson, Michael D. & Kirchain, Randolph E., 2009. "Quantifying the effects of product family decisions on material selection: A process-based costing approach," International Journal of Production Economics, Elsevier, vol. 120(2), pages 653-668, August.
    10. Bai, Danyu & Tang, Mengqian & Zhang, Zhi-Hai & Santibanez-Gonzalez, Ernesto DR, 2018. "Flow shop learning effect scheduling problem with release dates," Omega, Elsevier, vol. 78(C), pages 21-38.
    11. Mahesh Kumar Jayaswal & Mandeep Mittal, 2022. "Impact of Inflation and Credit Financing Policy on the Supply Chain With Learning," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-25, January.
    12. Askarany, Davood & Yazdifar, Hassan, 2012. "An investigation into the mixed reported adoption rates for ABC: Evidence from Australia, New Zealand and the UK," International Journal of Production Economics, Elsevier, vol. 135(1), pages 430-439.
    13. K. Reddy & H. S. Venter & M. S. Olivier, 2012. "Using time-driven activity-based costing to manage digital forensic readiness in large organisations," Information Systems Frontiers, Springer, vol. 14(5), pages 1061-1077, December.
    14. Antonio Armillotta, 2021. "On the role of complexity in machining time estimation," Journal of Intelligent Manufacturing, Springer, vol. 32(8), pages 2281-2299, December.
    15. Korytkowski, Przemyslaw & Malachowski, Bartlomiej, 2019. "Competence-based estimation of activity duration in IT projects," European Journal of Operational Research, Elsevier, vol. 275(2), pages 708-720.
    16. Mitali Sarkar & Li Pan & Bikash Koli Dey & Biswajit Sarkar, 2020. "Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production?," Mathematics, MDPI, vol. 8(7), pages 1-21, July.
    17. Duffner, Fabian & Mauler, Lukas & Wentker, Marc & Leker, Jens & Winter, Martin, 2021. "Large-scale automotive battery cell manufacturing: Analyzing strategic and operational effects on manufacturing costs," International Journal of Production Economics, Elsevier, vol. 232(C).
    18. Sonntag, Danja & Kiesmüller, Gudrun P., 2018. "Disposal versus rework – Inventory control in a production system with random yield," European Journal of Operational Research, Elsevier, vol. 267(1), pages 138-149.
    19. Gour Chandra Mahata, 2017. "A production-inventory model with imperfect production process and partial backlogging under learning considerations in fuzzy random environments," Journal of Intelligent Manufacturing, Springer, vol. 28(4), pages 883-897, April.
    20. Morgan, Horatio M. & Ngwenyama, Ojelanki, 2015. "Real options, learning cost and timing software upgrades: Towards an integrative model for enterprise software upgrade decision analysis," International Journal of Production Economics, Elsevier, vol. 168(C), pages 211-223.

    More about this item

    Keywords

    Free-form machining; Cost modeling;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:158:y:2014:i:c:p:345-358. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.