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Title:OPTIMIZACIJA RAZMESTITVE STROJEV V VALJARNI S POMOČJO GENETSKEGA ALGORITMA
Authors:Rožej, Urban (Author)
Brezočnik, Miran (Mentor) More about this mentor... New window
Kovačič, Miha (Co-mentor)
Files:.pdf VS_Rozej_Urban_2011.pdf (1,87 MB)
 
Language:Slovenian
Work type:Undergraduate thesis (m5)
Organization:FS - Faculty of Mechanical Engineering
Abstract:Štore Steel d.o.o. je fleksibilna mini jeklarna, specializirana za dobavo jekel v manjših serijah. V letu 2010 je predviden zagon nove konti proge s tehnično letno kapaciteto 250.000 ton. Nova konti valjarska proga bo poleg povišane produktivnosti omogočala bistveno višji nivo kvalitete valjancev (tolerance, ravnost, površina, trdote), obenem pa s sodobnejšo avtomatizacijo tudi bistveno višji nivo zbiranja in prenosa informacij o izvršeni proizvodnji. Konfiguracija proge bo omogočala temeljitejšo on-line vzorčno kontrolo valjancev in posledično hitrejše ukrepanje, če bi prišlo do neskladnosti. Zgoraj navedene spremembe bodo bistveno vplivale tudi na bodoče izvajanje dodatnih opravil na valjancih (obrat adjustaže), obenem pa bo obstajala možnost premestitve strojev obrata adjustaže na nove lokacije. Cilj naloge je poiskati najprimernejšo razporeditev strojne opreme v obratu adjustaže in posledično transportnih poti glede na obstoječ proizvodni program in prostorske zmožnosti. Za reševanje problema razvrščanja strojev je bil uporabljen genetski algoritem, ki posnema evolucijo živih bitij. Dosežena je bila optimalna razmestitev strojev in s tem krajše transportne poti glede na dosedanje stanje.
Keywords:valjarna, optimizacija razmestitve strojev, optimizacija, evolucijsko računanje, genetski algoritmi;
Year of publishing:2011
Source:Maribor
NUK URN:URN:SI:UM:DK:9JL8XKJF
Views:2218
Downloads:168
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FS
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Secondary language

Language:English
Title:OPTIMIZATION OF MACHINES ARRANGEMENT IN ROLLING MILL BY GENETIC ALGORITHM
Abstract:Štore Steel d.o.o. is a flexible mini steel factory that specializes in supply of steel in smaller series. In 2010 a starting of a new konti line, having a technical capacity of 250.000 tons a year is planned. A new konti fulling mill lane will, beside the enhanced productivity, enable a higher level of cylinder quality (tolerance, evenness, surface, hardness) and with Level 2 automation significantly higher level of gathering and transferring of data on executed production. Configuration of the lane will enable a more thorough on-line cylinder sample control and consequently faster responsiveness in a sense of eliminating inconsistencies. The above mentioned changes will have a significant influence on future execution of additional actions on cylinders (finishing plant), and will also open a possibility for relocation of machines in the finishing plant to a new location. The goal of this research is finding the most appropriate arrangement of the machinery equipment in the finishing plant as well as finding the most appropriate transport route, according to the current production programme and spatial ability. To solve the problem of arranging machines, a genetic algorithm imitating the evolution of living creatures has been used. We reached the optimal layout of machinery and the shorter routes on the existing situation.
Keywords:mill, optimization deployment machines, optimization, evolutionary computation, genetic algorithms;


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