Optimization of CO2 laser welding process parameters on cupronickel alloys using multi-objective techniques
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Optimization of process parameters for welding cupronickel alloys using CO2 laser welding process was investigated in thisstudy. Laser Beam Welding (LBW) process, is one of the beneficial techniques for airplane fastening. Turbine motorcomponents were made up of superalloy because of its high specific, low heat input, high heat focus, high-power density, andlow contortion. Using CO2 LBW process, welding can be done on a wide range of materials, especially alloys which aredifficult to weld by conventional welding process. This investigation focuses on optimizing the LBW process parameters ofcupronickel alloys utilizing multi criteria decision making (MCDM) methodology and TOPSIS analysis. The inputparameters like laser power, welding speed, welding angle and welding current are preferred as the fundamental part toenhance the welding. Welding process is carried out on 16 specimens in order to improve and support mechanical andmetallurgical qualities of the welded parts. Welding is made with four input variables in two levels of values. TOPSIS hasbeen employed as a statistical design tool to identify the most significant parameters on the overall Multiobjective function. Among the experiments, the best mechanical properties were observed in welding made with the parameters like Weldingcurrent (900 W), Welding angle (90°), Welding speed (1.4mm/min) and Laser power (30 W). This investigation strives toreveal the better process parameters, mechanical properties and energy consumption of CO2 LBW welded elements ofcupronickel alloy.
Abstract
Optimization of process parameters for welding cupronickel alloys using CO2 laser welding process was investigated in thisstudy. Laser Beam Welding (LBW) process, is one of the beneficial techniques for airplane fastening. Turbine motorcomponents were made up of superalloy because of its high specific, low heat input, high heat focus, high-power density, andlow contortion. Using CO2 LBW process, welding can be done on a wide range of materials, especially alloys which aredifficult to weld by conventional welding process. This investigation focuses on optimizing the LBW process parameters ofcupronickel alloys utilizing multi criteria decision making (MCDM) methodology and TOPSIS analysis. The inputparameters like laser power, welding speed, welding angle and welding current are preferred as the fundamental part toenhance the welding. Welding process is carried out on 16 specimens in order to improve and support mechanical andmetallurgical qualities of the welded parts. Welding is made with four input variables in two levels of values. TOPSIS hasbeen employed as a statistical design tool to identify the most significant parameters on the overall Multiobjective function. Among the experiments, the best mechanical properties were observed in welding made with the parameters like Weldingcurrent (900 W), Welding angle (90°), Welding speed (1.4mm/min) and Laser power (30 W). This investigation strives toreveal the better process parameters, mechanical properties and energy consumption of CO2 LBW welded elements ofcupronickel alloy.
참고문헌 (28)
- N. Saravanan, , J. Nat. Fibers, pp.1~13 (2021)
- M. Wahba, , J. Mater. Eng. Perform, 25, pp.2889~2894 (2016)
- V. Jeyabalaji, , J. Nat. Fibers, pp.1~13 (2021)
- K. Raja, , Arab. J. Sci. Eng, 45, pp.9481~9495 (2020)
- P. Muthurasu, "Optimization and analysis of microstructural friction stir welded AA5083 grade aluminium alloy", Journal of Ceramic Processing Research, 22(6), pp.697~704 (2021), 청정에너지연구소[DOI]
- S. A. Pichuzhkin, , Metallurgist, 59, pp.968~973 (2016)
- M. P. Chakravarthy, , Proc. Inst. Mech. Eng. Part B J. Eng. Manuf, 228, pp.1153~1161 (2014)
- C. Tan, , Mater. Des, 49, pp.766~773 (2013)
- J. Shen, , Mater. Sci. Eng. A, 578, pp.303~309 (2013)
- Y. B. Chen, , Int. J. Adv. Manuf. Technol, 68, pp.1351~1359 (2013)
- M. Behzadian, , Expert Syst. Appl, 39, pp.13051~13069 (2012)
- M. Rajeshwaran, , J. Appl. Fluid Mech, 11, pp.257~270 (2018)
- V. Vignesh Kumar, , Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng, 235, pp.2180~2188 (2021)
- P. Gopi Krishnan, "Optimization of process parameters in friction stir welding of aluminium matrix SiC-Al2O3 composites by genetic algorithm", Journal of Ceramic Processing Research, 21(2), pp.157~163 (2020), 청정에너지연구소[DOI]
- R. Pandiyarajan, "Characterization of AA6061-ZrO2-C friction stir welded composite joints", Journal of Ceramic Processing Research, 21(6), pp.690~698 (2020), 청정에너지연구소[DOI]
- B. R. Kumar, , Adv. Mat. Res, 585, pp.430~434 (2012)
- A. Belhadj, , J. Laser Appl, 22, pp.56~61 (2010)
- P. Ferro, , Sci. Technol. Weld. Join, 10, pp.299~310 (2005)
- V. Yamunadevi, , Mater. Res. Express, 6, pp.95057~ (2019)
- G. Radhaboy, , Energy Sources, Part A Recover. Util. Environ. Eff (2019)
- V. V. Kumar, , J. Brazilian Soc. Mech. Sci. Eng, 41, pp.1~14 (2019)
- Suresh Babu B, "Production and characterization of mechanical and microstructural behaviour of friction stir welded Al6063 composites reinforced with Gr", B4C, Journal of Ceramic Processing Research, pp.2018, 19(1)[DOI]
- C. Chanakyan, "Parametric studies in friction stir welding on Al-Mg alloy with (HCHCr) tool by Taguchi based desirability function analysis (DFA)", Journal of Ceramic Processing Research, 21(6), pp.647~655 (2020), 청정에너지연구소[DOI]
- L. Shi, , Sci. Technol. Weld. Join, 26, pp.363~370 (2021)
- M. Gao, , Sci. Technol. Weld. Join, 11, pp.517~522 (2006)
- N. Selvakumar, , Exp. Tech, 40, pp.129~135 (2016)
- P. Ferro, , Sci. Technol. Weld. Join, 10, pp.299~310 (2005)
- K. A. S. Lewise, , Mater. Manuf. Process, 37, pp.34~42 (2022)