2890 KB49 KB199920252015Agnihotri, GeetaKrishna, ChimataPare, Vikasštevilka:3letnik:61str. 176-186, SI 34ISSN:0039-2480COBISSID:13936923URN:URN:NBN:SI:doc-1OQI03VZenZveza strojnih inženirjev in tehnikov Slovenije et al.Strojniški vestnikgravitacijski iskalni algoritmikompoziti s kovinskim matriksomoptimizacijapovršinska hrapavostvisokohitrostna obdelavaSelection of optimum process parameters in high speed CNC end-milling of composite materials using meta heuristic techniques - a comparative study|The machining of aluminium metal matrix composites in CNC high speed conditions is significant because such composites have diverse applications in the aeronautics industry. Because that industry requires high quality outcomes, the prediction of surface roughness, which depends on input process parameters, assumes significance in the maintaining quality of products. Even though many researchers have worked in the area of conventional machining, very few of them have explored optimization techniques, such as teaching-learning-based optimization (TLBO) and gravitational search algorithms (GSA) in high speed environments. In this research, an attempt is made to determine the optimum machining conditions for the end-milling of composite materials using GSA. Input process parameters, such as cutting speed, feed, the depth of cut and the step-over ratio are taken as independent variables, and surface roughness is taken as dependent variable. Experiments were conducted on Al 2 O 3 + SiC metal matrix composite by considering selected variations in the input process parameters. Surface roughness is measured in each of cases, and the required data is obtained for further analysis. An empirical relationship is established between dependent and independent variables in the form of linear and non-linear regression equations, and the results are analysed. The results showed that GSA gives better results for surface roughness when compared to the genetic algorithm, simulated annealing and TLBO methods. An additional set of experiments was conducted to validate the results obtainedVisokohitrostna CNC-obdelava kompozitnih materialov z aluminijastim matriksom je pomembna za letalsko in vesoljsko industrijo. Letalska in vesoljska industrija zahteva visoko kakovost in napovedovanje površinske hrapavosti na podlagi vhodnih parametrov procesa je pomembno za zagotavljanje kakovosti izdelkov. Veliko raziskovalcev se ukvarja s konvencionalno obdelavo, le malo pa se jih je lotilo tehnik optimizacije na področju visokohitrostnih obdelav, kot so npr. optimizacija na osnovi poučevanja in učenja (TLBO) ter gravitacijski iskalni algoritmi (GSA). Namen tega raziskovalnega članka je modeliranje odvisnosti med površinsko hrapavostjo in izbranimi vhodnimi parametri, optimizacija površinske hrapavosti z mehkimi računskimi tehnikami kot so GSA, TLBO, SA in GA, primerjava rezultatov, kakor tudi verifikacija in validacija rezultatov iz prejšnjega koraka z izvedbo dodatnega nabora eksperimentovTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaUniverza v Ljubljani, Fakulteta za strojništvo