Analysis of Production Process composed of Two Machines and Two Robots using Petri nets

2016 ◽  
Vol 2016.52 (0) ◽  
pp. 314
Author(s):  
Mitsuo YAMASHIRO ◽  
Mamoru KATOH ◽  
Wodaje HELETWORK Bekele
2011 ◽  
Vol 143-144 ◽  
pp. 894-900
Author(s):  
Bin Peng ◽  
Bo Zhu ◽  
Fei Liu

Most of the pre-existing modeling approaches for Automatic machining line (AML) concentrate on the equipment failure, but ignore some factors greatly influencing the performance of AML in production process, like the tool life, quality abnormality etc. Considering the above complex factors, a GSPN-based modeling approach is proposed to model the AML based on the fundamental principle of generalized stochastic petri nets (GSPN), which contributes to quantitatively analyze the relations between those factors and productivity of AML. The proposed modeling approach is applied in the automatic gear hobbing and shaving line in a gearbox factory. Some factors including equipment failure, cutting tool and quality abnormality are simulated to analyze the affections on the productivity, and the results show the validity of the approach.


Jurnal Tekno ◽  
2019 ◽  
Vol 16 (2) ◽  
pp. 49-55
Author(s):  
R Ismed Rohimat

Recently, the usage of animal horn in Indonesia as a hand craft has a great attention especially for a dirk handycrafter. The shortage of such horn as raw material becomes a problem for the horn and dirk handycrafter. Implication of that is a gap between demand and supply in the market. To over come this condition, we design two machines-milling machine and pressing machine- that changing the scrap of horn processing into a useable raw material. The idea is converted the waste by using milling and pressing process.The result not only profitable for the horn handy-crafter, it also gives benefition solution for the green production process by making a better environment


2008 ◽  
Vol 41 (2) ◽  
pp. 1863-1868 ◽  
Author(s):  
Nilson Bastos ◽  
Eduardo R. Loures ◽  
Eduardo A.P. Santos ◽  
Marco A.B. de Paula

Author(s):  
Victor E. Stepanenko ◽  
◽  
Dmitry N. Frolov ◽  
Boris N. Maryin ◽  
◽  
...  

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