Application of TOPSIS Optimization in Abrasive Water Jet Machining of Military Grade Armor Steel
Rolled Homogeneous Armor (RHA) is a high tensile strength, toughness, and hardness is widely used in defense battlefield vehicles. RHA is high-strength low alloy steel and it is best suited for all battlefield applications in defense vehicles as it withstands any projectile attack. The TOPSIS method...
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Published in | Human factors and mechanical engineering for defense and safety Vol. 5; no. 1 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Singapore
Springer Singapore
01.12.2021
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Subjects | |
Online Access | Get full text |
ISSN | 2509-8004 2367-2544 |
DOI | 10.1007/s41314-021-00039-4 |
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Abstract | Rolled Homogeneous Armor (RHA) is a high tensile strength, toughness, and hardness is widely used in defense battlefield vehicles. RHA is high-strength low alloy steel and it is best suited for all battlefield applications in defense vehicles as it withstands any projectile attack. The TOPSIS method was used in this study to conduct an experimental investigation of abrasive water jet machining (AWJM) cutting on RHA steel. Process parameters like jet water pressure (
P
), jet traverse rate (
T
), and standoff distance (SOD) are optimized with multiresponse output characteristics such as kerf angle (Ka), material removal mate (MRR), and surface roughness (Ra). The experiments are conducted under L27 factorial design, and Simos’ weightage approach is used to calculate the weight of the output parameter. The ANOVA test is employed to determine the level of contribution of each input parameter. The optimal closeness output response gives maximum MRR and minimum Ka and Ra values.
T
is the most influencing factor in the three output responses and SOD is the second influencing factor. The better optimal process parameter SOD = 1 mm,
T
= 5 mm/min and
P
= 240 MPa is identified using the TOPSIS method. |
---|---|
AbstractList | Rolled Homogeneous Armor (RHA) is a high tensile strength, toughness, and hardness is widely used in defense battlefield vehicles. RHA is high-strength low alloy steel and it is best suited for all battlefield applications in defense vehicles as it withstands any projectile attack. The TOPSIS method was used in this study to conduct an experimental investigation of abrasive water jet machining (AWJM) cutting on RHA steel. Process parameters like jet water pressure (
P
), jet traverse rate (
T
), and standoff distance (SOD) are optimized with multiresponse output characteristics such as kerf angle (Ka), material removal mate (MRR), and surface roughness (Ra). The experiments are conducted under L27 factorial design, and Simos’ weightage approach is used to calculate the weight of the output parameter. The ANOVA test is employed to determine the level of contribution of each input parameter. The optimal closeness output response gives maximum MRR and minimum Ka and Ra values.
T
is the most influencing factor in the three output responses and SOD is the second influencing factor. The better optimal process parameter SOD = 1 mm,
T
= 5 mm/min and
P
= 240 MPa is identified using the TOPSIS method. |
ArticleNumber | 3 |
Author | Velayudham, A. Uthayakumar, M. Rammohan, S. Kumaran, S. Thirumalai |
Author_xml | – sequence: 1 givenname: S. surname: Rammohan fullname: Rammohan, S. organization: Department of Automobile Engineering, Kalasalingam Academy of Research and Education – sequence: 2 givenname: S. Thirumalai surname: Kumaran fullname: Kumaran, S. Thirumalai email: thirumalaikumaran@yahoo.com organization: Faculty of Mechanical Engineering, Kalasalingam Academy of Research and Education – sequence: 3 givenname: M. surname: Uthayakumar fullname: Uthayakumar, M. organization: Faculty of Mechanical Engineering, Kalasalingam Academy of Research and Education – sequence: 4 givenname: A. surname: Velayudham fullname: Velayudham, A. organization: Combat Vehicles Research and Development Establishment, Ministry of Defense |
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Cites_doi | 10.1007/s40033-020-00211-8 10.1080/10426914.2012.700159 10.1016/j.eswa.2012.05.056 10.1007/s12206-015-1217-4 10.1007/s41779-017-0023-0 10.1007/978-3-642-46768-4_5 10.1007/s00170-004-2348-4 10.1504/IJMMM.2018.090543 10.1016/0923-4748(95)00011-7 10.1080/10426914.2015.1103859 10.1007/s12633-020-00766-x 10.1007/s13369-019-03978-5 10.1016/j.mcm.2004.10.003 10.1080/10426914.2018.1544707 10.1243/09544054JEM1238 10.1007/s00170-018-2321-2 10.1007/978-3-642-48318-9_3 10.1080/10426914.2014.994763 10.1080/10426914.2011.593231 10.1080/10426914.2012.736661 10.1016/j.msea.2013.11.018 10.1080/02533839.2002.9670684 10.1515/JMSP.2011.002 10.1007/s00170-010-2905-y 10.1007/s40430-019-1823-7 |
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(1992) Fuzzy Multiple attribute decision making methods. In: Fuzzy Multiple attribute decision making. Lecture notes in economics and mathematical systems, vol 375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46768-4_5 KarakurtIAydinGAydinerKAn experimental study on the depth of cut of granite in abrasive waterjet cuttingMater Manuf Processes20122753854410.1080/10426914.2011.593231 ChauOLSelection of a manufacturing process with multiple attributes: a case studyJ Eng Tech Manage19951221923710.1016/0923-4748(95)00011-7 KumarARaiRNGrey-Taguchi and TOPSIS-Taguchi-based optimisation of performance parameters of Spark EDM on heat-treated AA7050 / 5 B4C compositeJ Inst Eng India Ser D2020101717910.1007/s40033-020-00211-8 Hwang CL, Yoon K (1981) Methods for multiple attribute decision making. In: Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems, vol 186. 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J Braz Soc Mech Sci Eng 41:323. https://doi.org/10.1007/s40430-019-1823-7 – reference: ChakladarNDChakrabortySA combined TOPSIS-AHP-method-based approach for non-traditional machining processes selectionProc Inst Mech Eng B J Eng Manuf2008222121613162310.1243/09544054JEM1238 – reference: UthayakumarMKhanMAKumaranSTSlotaAMachinability of nickel based superalloy by abrasive water jet machiningMater Manuf Processes2016311733173910.1080/10426914.2015.1103859 – reference: ThamizhvalavanPArivazhaganSYuvarajNRameshBMachinability study of abrasive aqua jet parameters on hybrid metal matrix compositeMater Manuf Process20180012410.1080/10426914.2018.1544707 – reference: KumarARaiRNGrey-Taguchi and TOPSIS-Taguchi-based optimisation of performance parameters of Spark EDM on heat-treated AA7050 / 5 B4C compositeJ Inst Eng India Ser D2020101717910.1007/s40033-020-00211-8 – reference: Bobbili R, Madhu V, Gogia AK (2013) Effect of wire-EDM machining parameters on surface roughness and material removal rate of high strength armor steel. Mater Manuf Process 28(4):37–41. https://doi.org/10.1080/10426914.2012.736661 – reference: Chen SJ., Hwang CL. (1992) Fuzzy Multiple attribute decision making methods. In: Fuzzy Multiple attribute decision making. Lecture notes in economics and mathematical systems, vol 375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46768-4_5 – reference: BehzadianMOtaghsaraSKYazdaniMIgnatiusJExpert Systems with Applications A state-of the-art survey of TOPSIS applicationsExpert Syst Appl201239130511306910.1016/j.eswa.2012.05.056 – reference: SinghADattaSSankarSApplication of TOPSIS in the Taguchi method for optimal machining parameter selectionJ Manuf Sci Prod201111496010.1515/JMSP.2011.002 – reference: RajSONPrabhuSInvestigation on slicing Behavior of Single Crystal Silicon Wafer in AWJM and Influence of Micro Dimple Textured Surface for Solar ApplicationsSilicon202010.1007/s12633-020-00766-x – reference: GeethapriyanTMuthuramalingamTKalaichelvanKInfluence of process parameters on machinability of Inconel 718 by electrochemical micromachining process using TOPSIS techniqueArab J Sci Eng2019447945795510.1007/s13369-019-03978-5 – reference: HuCJLeePYChenJSBallistic performance and microstructure of modified rolled homogeneous armor steelJ Chin Inst Eng20022519910710.1080/02533839.2002.9670684 – reference: ShanmugavelRMokkandiPJayamaniMRajiniNUthayakumarMThirumalaikumaranSMechanical and machinability characteristics of Al-NiTi composites reinforced with SiC particulatesJ Aust Ceram Soc20175317718510.1007/s41779-017-0023-0 – reference: KarakurtIAydinGAydinerKAn experimental study on the depth of cut of granite in abrasive waterjet cuttingMater Manuf Processes20122753854410.1080/10426914.2011.593231 – reference: ChauOLSelection of a manufacturing process with multiple attributes: a case studyJ Eng Tech Manage19951221923710.1016/0923-4748(95)00011-7 – reference: GauriSKChakravortyROptimization of correlated multiple responses of ultrasonic machining (USM) processInt J Adv Manuf Technol2011531115112710.1007/s00170-010-2905-y – reference: NguyenHPhamVNgoNApplication of TOPSIS to Taguchi method for multi-characteristic optimization of electrical discharge machining with titanium powder mixed into dielectric fluidInt J Adv Manuf Technol2018981179119810.1007/s00170-018-2321-2 – reference: WhittingtonWROppedalALTurnageSHammiYRheeHAllisonPGCraneCKHorstemeyerMFCapturing the effect of temperature, strain rate, and stress state on the plasticity and fracture of rolled homogeneous armor (RHA) steelMater Sci Eng A2014594828810.1016/j.msea.2013.11.018 – reference: YuvarajNPradeep KumarMOptimisation of abrasive water jet cutting process parameters for AA5083-H32 aluminium alloy using fuzzy TOPSIS methodInt J Mach Mach Mater20182011814010.1504/IJMMM.2018.090543 – reference: MaitySRChakrabortySGrinding wheel abrasive material selection using fuzzy TOPSIS methodMater Manuf Process201328374110.1080/10426914.2012.700159 – reference: OlsonDLComparison of weights in TOPSIS models, Mathematical and Computer ModellingMath Comput Model20044072172710.1016/j.mcm.2004.10.0031066.90054 – reference: Hwang CL, Yoon K (1981) Methods for multiple attribute decision making. In: Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems, vol 186. 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Title | Application of TOPSIS Optimization in Abrasive Water Jet Machining of Military Grade Armor Steel |
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