Application of neural networks in evaluation of technological time

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ŠIMUNOVIĆ, Goran ;ŠARIĆ, Tomislav ;LUJIĆ, Roberto .
Application of neural networks in evaluation of technological time. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 54, n.3, p. 179-188, august 2017. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/application-of-neural-networks-in-evaluation-of-technological-time/>. Date accessed: 17 sep. 2021. 
doi:http://dx.doi.org/.
Šimunović, G., Šarić, T., & Lujić, R.
(2008).
Application of neural networks in evaluation of technological time.
Strojniški vestnik - Journal of Mechanical Engineering, 54(3), 179-188.
doi:http://dx.doi.org/
@article{.,
	author = {Goran  Šimunović and Tomislav  Šarić and Roberto  Lujić},
	title = {Application of neural networks in evaluation of technological time},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {54},
	number = {3},
	year = {2008},
	keywords = {process planning; artificial intelligence; neural networks; },
	abstract = {The traditional approach to the process planning mostly based on experience of technologists, requires a lot of accumulated knowledge, is inflexible and time consuming. The application of artificial intelligence methods can supportand greatly improve this approach. This paper describes the results obtained by investigating the application of neural networks in evaluating the manufacturing parameters and, indirectly, technological time of the seam tube polishing. Various structures of a back-propagation neural network have been analysed and the optimum one with the minimum RMS (Root Mean Square) error selected. The obtained model was integrated into the ERP system (Enterprise Resource Planning system) of a manufacturing company. The more precise evaluations of technological time obtained by the ERP system model complete the previously defined manufacturing operations and form the basis for production planning and times of delivery control. The work of technologists is thus made easier and the production preparation technological time made shorter.},
	issn = {0039-2480},	pages = {179-188},	doi = {},
	url = {https://www.sv-jme.eu/sl/article/application-of-neural-networks-in-evaluation-of-technological-time/}
}
Šimunović, G.,Šarić, T.,Lujić, R.
2008 August 54. Application of neural networks in evaluation of technological time. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 54:3
%A Šimunović, Goran 
%A Šarić, Tomislav 
%A Lujić, Roberto 
%D 2008
%T Application of neural networks in evaluation of technological time
%B 2008
%9 process planning; artificial intelligence; neural networks; 
%! Application of neural networks in evaluation of technological time
%K process planning; artificial intelligence; neural networks; 
%X The traditional approach to the process planning mostly based on experience of technologists, requires a lot of accumulated knowledge, is inflexible and time consuming. The application of artificial intelligence methods can supportand greatly improve this approach. This paper describes the results obtained by investigating the application of neural networks in evaluating the manufacturing parameters and, indirectly, technological time of the seam tube polishing. Various structures of a back-propagation neural network have been analysed and the optimum one with the minimum RMS (Root Mean Square) error selected. The obtained model was integrated into the ERP system (Enterprise Resource Planning system) of a manufacturing company. The more precise evaluations of technological time obtained by the ERP system model complete the previously defined manufacturing operations and form the basis for production planning and times of delivery control. The work of technologists is thus made easier and the production preparation technological time made shorter.
%U https://www.sv-jme.eu/sl/article/application-of-neural-networks-in-evaluation-of-technological-time/
%0 Journal Article
%R 
%& 179
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%J Strojniški vestnik - Journal of Mechanical Engineering
%V 54
%N 3
%@ 0039-2480
%8 2017-08-21
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Šimunović, Goran, Tomislav  Šarić, & Roberto  Lujić.
"Application of neural networks in evaluation of technological time." Strojniški vestnik - Journal of Mechanical Engineering [Online], 54.3 (2008): 179-188. Web.  17 Sep. 2021
TY  - JOUR
AU  - Šimunović, Goran 
AU  - Šarić, Tomislav 
AU  - Lujić, Roberto 
PY  - 2008
TI  - Application of neural networks in evaluation of technological time
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - process planning; artificial intelligence; neural networks; 
N2  - The traditional approach to the process planning mostly based on experience of technologists, requires a lot of accumulated knowledge, is inflexible and time consuming. The application of artificial intelligence methods can supportand greatly improve this approach. This paper describes the results obtained by investigating the application of neural networks in evaluating the manufacturing parameters and, indirectly, technological time of the seam tube polishing. Various structures of a back-propagation neural network have been analysed and the optimum one with the minimum RMS (Root Mean Square) error selected. The obtained model was integrated into the ERP system (Enterprise Resource Planning system) of a manufacturing company. The more precise evaluations of technological time obtained by the ERP system model complete the previously defined manufacturing operations and form the basis for production planning and times of delivery control. The work of technologists is thus made easier and the production preparation technological time made shorter.
UR  - https://www.sv-jme.eu/sl/article/application-of-neural-networks-in-evaluation-of-technological-time/
@article{{}{.},
	author = {Šimunović, G., Šarić, T., Lujić, R.},
	title = {Application of neural networks in evaluation of technological time},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {54},
	number = {3},
	year = {2008},
	doi = {},
	url = {https://www.sv-jme.eu/sl/article/application-of-neural-networks-in-evaluation-of-technological-time/}
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TY  - JOUR
AU  - Šimunović, Goran 
AU  - Šarić, Tomislav 
AU  - Lujić, Roberto 
PY  - 2017/08/21
TI  - Application of neural networks in evaluation of technological time
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 54, No 3 (2008): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - process planning, artificial intelligence, neural networks, 
N2  - The traditional approach to the process planning mostly based on experience of technologists, requires a lot of accumulated knowledge, is inflexible and time consuming. The application of artificial intelligence methods can supportand greatly improve this approach. This paper describes the results obtained by investigating the application of neural networks in evaluating the manufacturing parameters and, indirectly, technological time of the seam tube polishing. Various structures of a back-propagation neural network have been analysed and the optimum one with the minimum RMS (Root Mean Square) error selected. The obtained model was integrated into the ERP system (Enterprise Resource Planning system) of a manufacturing company. The more precise evaluations of technological time obtained by the ERP system model complete the previously defined manufacturing operations and form the basis for production planning and times of delivery control. The work of technologists is thus made easier and the production preparation technological time made shorter.
UR  - https://www.sv-jme.eu/sl/article/application-of-neural-networks-in-evaluation-of-technological-time/
Šimunović, Goran, Šarić, Tomislav, AND Lujić, Roberto.
"Application of neural networks in evaluation of technological time" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 54 Number 3 (21 August 2017)

Avtorji

Inštitucije

  • University of Osijek, Faculty of Mechanical Engineering, Croatia
  • University of Osijek, Faculty of Mechanical Engineering, Croatia
  • University of Osijek, Faculty of Mechanical Engineering, Croatia

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 54(2008)3, 179-188

The traditional approach to the process planning mostly based on experience of technologists, requires a lot of accumulated knowledge, is inflexible and time consuming. The application of artificial intelligence methods can supportand greatly improve this approach. This paper describes the results obtained by investigating the application of neural networks in evaluating the manufacturing parameters and, indirectly, technological time of the seam tube polishing. Various structures of a back-propagation neural network have been analysed and the optimum one with the minimum RMS (Root Mean Square) error selected. The obtained model was integrated into the ERP system (Enterprise Resource Planning system) of a manufacturing company. The more precise evaluations of technological time obtained by the ERP system model complete the previously defined manufacturing operations and form the basis for production planning and times of delivery control. The work of technologists is thus made easier and the production preparation technological time made shorter.

process planning; artificial intelligence; neural networks;