Lean Production Planning for 5 Axes CNC Driven Milling Machine

Sandor Bodzas; Bela Krakko

doi:doi:10.11648/j.mlr.20170202.14

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Lean Production Planning for 5 Axes CNC Driven Milling Machine

Sandor Bodzas, Bela Krakko

Published in Machine Learning Research (Volume 2, Issue 2)

Received: 29 January 2017 Accepted: 3 March 2017 Published: 15 March 2017

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Abstract

The aim of this publication is to determine the OEE (Overall Equipment Efficiency) indicator for a 5 axes milling machine found at Diehl Aircabin Hungary Ltd. for the present and future state. Based on this value, the utilization of the machine for the given production amount can be calculated. With the optimal choice of the right production parameters (the number of cuts, feeding, depth of cut, etc.) greater productivity can be achieved i.e the machine main time (time of cutting) will be less. The possibilities of the reduction of the machine time will be analyzed and calculated.

Published in	Machine Learning Research (Volume 2, Issue 2)
DOI	10.11648/j.mlr.20170202.14
Page(s)	66-72
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

OEE Value, Production Planning, Lean, Milling Machine

References

[1]	BODZÁS S: Gyártástervezés MAKA típusú CNC vezérlésű 5 tengelyes marógépre, thesis, LEAN profession, University of Debrecen, Debrecen, 2016, p. 67.
[2]	BERTA M.: CNC szerszámgépek szerszámrendszerei, Collage of Nyíregyháza Publisher, Nyíregyháza, p. 155, ISBN 978 615 5545 03 0
[3]	DUDÁS I.: Gépgyártástechnológia I., A gyártástechnológia alapjai, 2. edition, Műszaki Könyvkiadó Ltd., 2011, Budapest, p. 584, ISBN 963-16-4030-2
[4]	MÁTRAI N.: Lean Menedzsment presentations, University of Debrecen, Debrecen, 2016
[5]	PÉCZELY GY., PÉCZELY CS., PÉCZELI GY.: Lean 3, Termelékenységfejlesztés egységes rendszerben, A. A. Stádium Diagnosztikai és Menedzsment Ltd., Budapest, 2009, p. 690, ISBN 978-963-08-3163-5
[6]	WILSON, L.: How to implement Lean Manufacturing, Second Edition, 2015, p. 419, ISBN 978-0-07-183573-2
[7]	BÁLINT L.: A forgácsoló megmunkálás tervezése, 2. kiadás, Műszaki Könyvkiadó Kft., 1961, Budapest, p. 883
[8]	KLOCKE, F.: Manufacturing Processes I, Cutting, RWTH Edition, RWTH Aachen University, p. 524, ISBN 978-3-642-11978-1
[9]	SCHEY, J. A.: Introduction to Manufacturing Processes, McGraw – Hill Book Company, 1977., p. 392., ISBN 0-07-055274-6
[10]	BRALLA, J. G.: Handbook of Manufacturing Processes, First Edition, Industrial Press Inc., New York, 2007, ISBN 0-831 1-3179-9
[11]	YOUSSEF, H. A., EL HOFY, H.: Machining Technology, Machine tools and operations, CRC Press, United States of Amerika, p. 672, ISBN 978-1-4200-4339-6

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APA Style

Sandor Bodzas, Bela Krakko. (2017). Lean Production Planning for 5 Axes CNC Driven Milling Machine. Machine Learning Research, 2(2), 66-72. https://doi.org/10.11648/j.mlr.20170202.14

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ACS Style

Sandor Bodzas; Bela Krakko. Lean Production Planning for 5 Axes CNC Driven Milling Machine. Mach. Learn. Res. 2017, 2(2), 66-72. doi: 10.11648/j.mlr.20170202.14

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AMA Style

Sandor Bodzas, Bela Krakko. Lean Production Planning for 5 Axes CNC Driven Milling Machine. Mach Learn Res. 2017;2(2):66-72. doi: 10.11648/j.mlr.20170202.14

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@article{10.11648/j.mlr.20170202.14,
  author = {Sandor Bodzas and Bela Krakko},
  title = {Lean Production Planning for 5 Axes CNC Driven Milling Machine},
  journal = {Machine Learning Research},
  volume = {2},
  number = {2},
  pages = {66-72},
  doi = {10.11648/j.mlr.20170202.14},
  url = {https://doi.org/10.11648/j.mlr.20170202.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20170202.14},
  abstract = {The aim of this publication is to determine the OEE (Overall Equipment Efficiency) indicator for a 5 axes milling machine found at Diehl Aircabin Hungary Ltd. for the present and future state. Based on this value, the utilization of the machine for the given production amount can be calculated. With the optimal choice of the right production parameters (the number of cuts, feeding, depth of cut, etc.) greater productivity can be achieved i.e the machine main time (time of cutting) will be less. The possibilities of the reduction of the machine time will be analyzed and calculated.},
 year = {2017}
}

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TY  - JOUR
T1  - Lean Production Planning for 5 Axes CNC Driven Milling Machine
AU  - Sandor Bodzas
AU  - Bela Krakko
Y1  - 2017/03/15
PY  - 2017
N1  - https://doi.org/10.11648/j.mlr.20170202.14
DO  - 10.11648/j.mlr.20170202.14
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 66
EP  - 72
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20170202.14
AB  - The aim of this publication is to determine the OEE (Overall Equipment Efficiency) indicator for a 5 axes milling machine found at Diehl Aircabin Hungary Ltd. for the present and future state. Based on this value, the utilization of the machine for the given production amount can be calculated. With the optimal choice of the right production parameters (the number of cuts, feeding, depth of cut, etc.) greater productivity can be achieved i.e the machine main time (time of cutting) will be less. The possibilities of the reduction of the machine time will be analyzed and calculated.
VL  - 2
IS  - 2
ER  -

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Author Information

Sandor Bodzas

Department of Mechanical Engineering, University of Debrecen, Debrecen, Hungary
Bela Krakko

Diehl Aircabin Hungary Ltd., Nyirbator, Hungary

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APA Style

Sandor Bodzas, Bela Krakko. (2017). Lean Production Planning for 5 Axes CNC Driven Milling Machine. Machine Learning Research, 2(2), 66-72. https://doi.org/10.11648/j.mlr.20170202.14

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ACS Style

Sandor Bodzas; Bela Krakko. Lean Production Planning for 5 Axes CNC Driven Milling Machine. Mach. Learn. Res. 2017, 2(2), 66-72. doi: 10.11648/j.mlr.20170202.14

Copy | Download

AMA Style

Sandor Bodzas, Bela Krakko. Lean Production Planning for 5 Axes CNC Driven Milling Machine. Mach Learn Res. 2017;2(2):66-72. doi: 10.11648/j.mlr.20170202.14

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@article{10.11648/j.mlr.20170202.14,
  author = {Sandor Bodzas and Bela Krakko},
  title = {Lean Production Planning for 5 Axes CNC Driven Milling Machine},
  journal = {Machine Learning Research},
  volume = {2},
  number = {2},
  pages = {66-72},
  doi = {10.11648/j.mlr.20170202.14},
  url = {https://doi.org/10.11648/j.mlr.20170202.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20170202.14},
  abstract = {The aim of this publication is to determine the OEE (Overall Equipment Efficiency) indicator for a 5 axes milling machine found at Diehl Aircabin Hungary Ltd. for the present and future state. Based on this value, the utilization of the machine for the given production amount can be calculated. With the optimal choice of the right production parameters (the number of cuts, feeding, depth of cut, etc.) greater productivity can be achieved i.e the machine main time (time of cutting) will be less. The possibilities of the reduction of the machine time will be analyzed and calculated.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Lean Production Planning for 5 Axes CNC Driven Milling Machine
AU  - Sandor Bodzas
AU  - Bela Krakko
Y1  - 2017/03/15
PY  - 2017
N1  - https://doi.org/10.11648/j.mlr.20170202.14
DO  - 10.11648/j.mlr.20170202.14
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 66
EP  - 72
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20170202.14
AB  - The aim of this publication is to determine the OEE (Overall Equipment Efficiency) indicator for a 5 axes milling machine found at Diehl Aircabin Hungary Ltd. for the present and future state. Based on this value, the utilization of the machine for the given production amount can be calculated. With the optimal choice of the right production parameters (the number of cuts, feeding, depth of cut, etc.) greater productivity can be achieved i.e the machine main time (time of cutting) will be less. The possibilities of the reduction of the machine time will be analyzed and calculated.
VL  - 2
IS  - 2
ER  -

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