2317 KB267 KB0 KB2014Balič, JožeFicko, MirkoGjelaj, AfrimXV, 140 f., 30 cmCOBISSID:18385686URN:URN:NBN:SI:doc-CUO6QIJRenA. Gjelajvisokošolska delaautomated programmingAvtomatsko programiranjeCNC strojidiscrete systemDisertacijediskretni sistemidoktorske disertacijeinteligent CNC programminginteligentna proizvodnjainteligentno CNC programiranjeintelligent manufacturingMOGAmultiobjective genetic algorithm MOGAvečkriterijski genetski algoritmiSamodejno in inteligentno programiranje CNC strojev| Automated and intelligent programming of CNC machine tools| doctoral thesis|Nowadays, many scientists focus on increasing the level of automation, respectively flexibility in manufacturing systems. In addition, automated programming of CNC machine tools has reached a high level of machining operations. However, it is still impossible for a machine to manipulate completely in an autonomous way. Special attention in this doctoral thesis is focused on the automated programming of CNC machine tools regarding artificial intelligence. The purpose of automated programming is to improve quality and to fulfil the requirements of manufacturing industry and provide commercial solutions. This thesis also provides a description of artificial intelligence usage in order to solve optimal tool path-length and tool selection, as well as the preparation of planned technology. Firstly, the automated programming of CNC machine tools enjoys great success when applying artificial intelligence in regard to the machining processes. Choices of path length and tool selection are analysed in great detail in order to ascertain the optimal problems of tool path- length and tool selection. However, in order to achieve automated and intelligent CNC programming of machine tools, their flexibilities are of major importance. Automation today tends to improve and implement manufacturing flexibility at a strategic level. This means increasing the degree of flexibility whilst at the same time increasing the degree of automation regarding CNC machine tools. In addition to the above-mentioned investigated problems, the influences of cutting force (Fc), power cutting (Pc), tool life (T) and surface roughness (Ra) as functions of tool path- length are also analysed. Analytical and mathematical models are optimised using a multi-objective genetic algorithm (MOGA). MOGA enables optimisation by employing two or more equations simultaneously. Another problem for the automated and intelligent CNC programming of machine tools focuses on the application of Discrete Systems (DS). The discrete system in our work focuses on analysing cutting force (Fc) in regard to the turning operationRazvoj obdelovalnih sistemov poteka danes v smeri vse večje avtomatizacije in njihove prilagodljivosti. To je povzročilo tudi pospešen razvoj sistemov za avtomatsko programiranje CNC strojev, ki so danes v veliki meri avtomatizirani. Popolno avtomatizacijo je nemogoče doseči. Zato je poudarek te doktorske naloge na razvoju sistema avtomatskega programiranja CNC strojev, ki je podprt z metodami umetne inteligence. Tak sistem mora omogočiti avtomatizacijo CNC programiranja na inteligenten način, da se tako dvigne kvaliteta programiranja, zanesljivost in določi optimalno zaporedje obdelave ter izbere optimalne rezalne pogoje. Doktorska disertacija obravnava pregled različnih pristopov k samodejnemu programiranju CNC obdelovalnih strojev in predstavlja prispevek k razvoju takšnega samodejnega inteligentnega programiranja CNC-obdelovalnih strojev, ki bo uporabno v industrijski praksi. Raziskana in analizirana sta dva trenda razvoja in raziskav, ki med seboj hkrati konkurirata in se dopolnjujeta; to je samodejno programiranje, ki vključuje deterministične pristope in inteligentno samodejno programiranje. Poleg tega so raziskani in opisani postopki CNC-programiranja ter stanje med komercialno dobavljivimi programi in raziskavami na tem področju. Izpostavljeni so cilji samodejnega in/ali inteligentnega programiranja in izdelan je ustrezni model, ki uporablja večkriterijsko optimizacijo, kjer so cilji podvrženi dinamičnemu tehniško-ekonomskemu okolju, ki pogosto menja pomembnost ciljev. Zaradi teh omejitev, je uporabljena večkriterijska optimizacija z genetskimi algoritmi (Ang.: Multi-Objective Genetic Algorithm - MOGA) in diskretna predstavitev problema. Večkriterijska optimizacija je logično nadaljevanje dosedanjih raziskav na področju določanja optimalnega programa, ker človek-strokovnjak izvaja prav tako večkriterijsko optimizacijo pri svojem delu. Obdelava na CNC-rezkalnih strojih vključuje tehniške, ekonomske in organizacijske kriterije, ki jih človek mimogrede upošteva, zato umetni sistem, ki uporablja enokriterijsko optimizacijo ne zagotavlja dovolj dobrih rezultatov za uporabo v praksi. Diskretna predstavitev problema poenostavi problem, zagotavlja omejitev iskalnega prostora in tako izboljša možnost uporabe metode v realnem časuTEXTvisokošolska delatheses and dissertationsSlovenian National E-content AggregatorNational and University Library of SloveniaUniverza v Mariboru, Fakulteta za strojništvo