Technical Journal, Vol. 14 No. 2, 2020.
Original scientific paper
https://doi.org/10.31803/tg-20200523200341
CAD Based Electric Transporter Path Planning and Production Storage Optimization Using Genetic Algorithm – Industrial Case Study
Miha Kovačič
; Štore Steel d.o.o. Železarska cesta 3, 3220 Štore, Slovenia / Faculty of Mechanical Engineering, University of Ljubljana, Aškerčeva cesta 6, 1000 Ljubljana, Slovenia
Goran Đukić
orcid.org/0000-0001-8898-6756
; Fakultet strojarstva i brodogradnje, Sveučilište u Zagrebu, Ivana Lučića 5, 10002 Zagreb, Croatia
Brigita Gajšek
; Faculty of Logistics, University of Maribor, Mariborska cesta 7, 3000 Celje, Slovenia
Klemen Stopar
; Štore Steel d.o.o. Železarska cesta 3, 3220 Štore, Slovenia
Abstract
Štore Steel Ltd. is one of the largest flat spring steel producers in Europe. There are two production lines after rolling – one for flat bars and the other for round bars. The flat bars production generally consists of visual examination, straightening and cutting operation. In addition, heat treatment or magnetic particle testing could be conducted. On the other hand, the round bars production consists generally of straightening, automatic control line control, chamfering and cutting. In addition, heat treatment is possible. For manipulation of the material in the rolling plant, the electric transporter and several cassettes are used. In the paper path planning and production storage optimization (i.e. storage spaces for cassettes) were conducted using genetic algorithm. The production storage is actually the space between main transport passage and individual operations. In the research the universal system using CAD geometry is presented where AutoCAD environment and in-house developed AutoLISP system were used. The production storage – storage spaces for cassettes (location and orientation) with corresponding electric transporter trajectories are represented as CAD objects and thus form individual solution/organism. The organisms undergo simulated evolution. The results of the evolution are compared with actual production storage in the steel plant.
Keywords
genetic algorithm; optimization; path planning; production storage; steel industry
Hrčak ID:
239005
URI
Publication date:
11.6.2020.
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