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Software analyses of optimum toolpath strategies from computer numerical control (CNC) codes

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Abstract

This study presents an approach for determining energy efficient toolpaths using numerical control (NC)-based energy demand software. To achieve this, NC programmes were generated for the true spiral, rectangular spiral, and square contour toolpaths from HyperMill, a commercially available Computer-Aided Manufacturing (CAM) software for performing pocket milling of AISI 1018 steel on a 3-axis CNC milling machine. These programmes were uploaded as input on the graphical user interface (GUI) of the NC code-based energy demand software. The result obtained from NC code-based energy software was validated against the theoretical total energy and processing time, and the pocket milling of AISI 1018 steel on a 3-axis CNC milling machine. The theoretical, software, and experimental analyses show that the true spiral toolpath had the lowest total electrical energy demand and processing time. The result also shows that the energy demand software could be adopted to accurately predict the total electrical energy and processing time pre-machining. This could save setting up and trial by error practices and costs. Further studies included surface roughness analyses of the machined pockets after milling, and an improved surface finish of the pocket was obtained with the true spiral toolpath when compared with the other considered toolpaths. Therefore, for energy efficient machining, it is recommended that NC code-based energy demand software which incorporates the weights of feed axes, vice, and workpiece, as well as the power required by the feed drive during cutting should be adopted for the accurate prediction of total electrical energy demand and total processing time of a machining process.

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Authors and Affiliations

  1. Faculty of Engineering, Department of Mechanical Engineering, Akwa Ibom State University, Ikot Akpaden, Mkpat Enin, Akwa Ibom State, Nigeria

    Isuamfon F. Edem & Bassey D. Nkanang

  2. Faculty of Engineering, Department of Mechanical Engineering, Edo University Iyamho, Iyamho, Edo State, Nigeria

    Vincent A. Balogun

  3. School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, M13 9PL, Manchester, UK

    Paul T. Mativenga

Authors
  1. Isuamfon F. Edem
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  2. Vincent A. Balogun
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  3. Bassey D. Nkanang
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  4. Paul T. Mativenga
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Correspondence to Isuamfon F. Edem.

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Edem, I.F., Balogun, V.A., Nkanang, B.D. et al. Software analyses of optimum toolpath strategies from computer numerical control (CNC) codes. Int J Adv Manuf Technol 103, 997–1007 (2019). https://doi.org/10.1007/s00170-019-03604-6

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  • DOI: https://doi.org/10.1007/s00170-019-03604-6

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