Design Of Experiment (DOE) Based Response Prediction In Machining
Laser cutting has great ability in cutting material and the use of laser cutting become widely in manufacturing field. In this project, the improvement planning is focused on the laser cutting machine parameters. The experimentation purposes are to determine the significant and insignificant factors...
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| Format: | Monograph |
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UTeM
2010
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| Capaian Atas Talian: | http://library.utem.edu.my:8000/elmu/index.jsp?module=webopac-d&action=graphicFullDisplayRetriever.jsp&szMaterialNo=0000063620 http://library.utem.edu.my:8000/elmu/index.jsp?module=webopac-d&action=graphicFullDisplayRetriever.jsp&szMaterialNo=0000063620 http://eprints.utem.edu.my/2523/1/Design_Of_Expereriment_%28DOE%29_Based_Response_Prediction_In_Machining_24_pages.pdf http://eprints.utem.edu.my/2523/2/Design_Of_Expereriment_%28DOE%29_Based_Response_Prediction_In_Machining_-_Full_Pages.pdf |
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| Ringkasan: | Laser cutting has great ability in cutting material and the use of laser cutting become widely in manufacturing field. In this project, the improvement planning is focused on the laser cutting machine parameters. The experimentation purposes are to determine the significant and insignificant factors which influence the quality of a product which manufactured by laser cutting machine and to optimize the machining parameters to obtain best cut quality. Factorial design based optimal parametric analysis has been performed to determine the optimal setting of process parameters for 2.5mm and 5.0 mm mild steel (RST37-2) where the response was surface roughness (Ra). Focal distance, gas pressure, power and cutting speed are the process parameter that was investigated in this study. The lowest and highest Ra value for 2.5mm mild steel that obtained was 1.69 μm and 11.09 μm. As for the 5mm mild steel lowest and highest Ra value that obtained was 2.25μm and 19.82 μm. From the analysis, cutting speed and gas pressure has significant effect to the surface roughness for 2.5mm mild steel. Meanwhile cutting speed, gas pressure and power has significant effect to the response surface roughness for 5 mm mild steel. A set of mathematical model for each 2.5mm and 5mm mild steel cutting process has been established with the aid of Balanced ANOVA analysis to generate the best optimize value of process parameters.. |
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