SIMULATING A FACTORY PRODUCTION PROCESS WITH AUTOMATED GUIDED VEHICLES

Author(s):  
G. Petkovska ◽  
V. Nedeljkovic ◽  
M. Hovanec
1990 ◽  
Vol 23 (3) ◽  
pp. 455-459
Author(s):  
G. Petkovska ◽  
V. Nedeljkovic ◽  
M. Hovanec

Author(s):  
Konstantin Vyatcheslavovitch Belyj

The article's research is centered on the transcripts of industrial conferences, meetings and reunions of the Moscow Automobile Plant named after I.A. Likhachev (AMO ZIL). The aim of this study is to determine the information potential of the transcripts taken during factory meetings concerning production issues and to use them as a source for studying the socio-psychological aspects of the history of industrial enterprises. The author examines in detail many aspects of the topic, including the transcripts' reflection of the views of enterprise managers, unit leaders, engineering and technical workers and workers in the production process, the features of the business culture, and the motivation of production participants. In working with transcripts, the author applied the socio-psychological and illustrative methods to a comprehensive analysis of sources. The research revealed a high saturation of information contained in the transcripts of production meetings, showing the possibilities of their use for studying the socio-psychological aspects of the history of industrial enterprises, in particular, the economic culture, the mentality of organizers and production participants, the atmosphere within the team, the views of managers and employees on the production process, their work motivation, as well as other issues. The author introduces into scientific circulation previously unexamined archival materials.


2018 ◽  
Vol 18 (3-4) ◽  
pp. 520-534 ◽  
Author(s):  
MARTIN GEBSER ◽  
PHILIPP OBERMEIER ◽  
TORSTEN SCHAUB ◽  
MICHEL RATSCH-HEITMANN ◽  
MARIO RUNGE

AbstractAutomated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such ad-hoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.


2019 ◽  
Vol 28 (9) ◽  
pp. 50-53
Author(s):  
N.N. Martynov ◽  
◽  
G.A. Sidorenko ◽  
G.B. Zinyukhin ◽  
E.Sh. Maneeva ◽  
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2018 ◽  
Vol 4 (2) ◽  
pp. 43-55
Author(s):  
Ika Yulianti ◽  
Endah Masrunik ◽  
Anam Miftakhul Huda ◽  
Diana Elvianita

This study aims to find a comparison of the calculation of the cost of goods manufactured in the CV. Mitra Setia Blitar uses the company's method and uses the Job Order Costing (JOC) method. The method used in this study is quantitative. The types of data used are quantitative and qualitative. Quantitative data is in the form of map production cost data while qualitative data is in the form of information about map production process. The result of calculating the cost of production of the map between the two methods results in a difference of Rp. 306. Calculation using the company method is more expensive than using the Job Order Costing method. Calculation of cost of goods manufactured using the company method is Rp. 2,205,000, - or Rp. 2,205, - each unit. While using the Job Order Costing (JOC) method is Rp. 1,899,000, - or Rp 1,899, - each unit. So that the right method used in calculating the cost of production is the Job Order Costing (JOC) method


Científica ◽  
2016 ◽  
Vol 44 (3) ◽  
pp. 412 ◽  
Author(s):  
Rafael Marani Barbosa ◽  
Bruno Guilherme Torres Licursi Vieira ◽  
Francisco Guilhien Gomes-Junior ◽  
Roberval Daiton Vieira

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