Investigation on Machinability Characteristics of Inconel 718 Alloy in Cryogenic Machining Processes

被引:8
作者
Gong, Le [1 ,2 ]
Su, Yu [1 ]
Liu, Yong [1 ]
Zhao, Wei [2 ]
Khan, Aqib Mashood [3 ]
Jamil, Muhammad [2 ]
机构
[1] Jiangsu Univ Sci & Technol, Coll Mech Engn, Zhenjiang 212100, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Mech & Elect Engn, Nanjing 210016, Peoples R China
[3] Univ Chakwal, Dept Mechatron Engn, Chakwal 48800, Pakistan
关键词
Inconel; 718; alloy; turning; cryogenic machining; machinability characteristics; RESPONSE-SURFACE METHODOLOGY; COATED CARBIDE TOOLS; CUTTING FORCES; TURNING PROCESS; STAINLESS-STEEL; FRICTION MODEL; DRY; PERFORMANCE; OPTIMIZATION; WEAR;
D O I
10.3390/lubricants11020082
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In this innovative work, Inconel 718 alloy turning simulation models under dry and cryogenic machining (Cryo) conditions are developed. The machinability characteristics of the aforementioned alloy were assessed with relation to cutting temperature (Tct) and cutting force (Fcf). The comparison of the Tct and Fcf results from simulation with those obtained under the identical experimental conditions served as additional evidence of the effectiveness of the suggested simulation model. By varying the cutting speed, the reduction in Tct under Cryo conditions was 9.36% to 11.98% compared to dry cutting. Regarding the force comparison under experiment and simulation, the average difference between the simulation and experimental values for the main cutting force (Fc) was 13.73%, whereas the average deviation for the feed force (Ff) was 14.63%. Response surface methodology (RSM) was employed to build the forecasting models for Tct and Fcf in cryogenic settings. These mathematical models showed excellent predictive performance and were able to estimate the Tct and Fcf under machining operations settings, according to the present research. When compared to dry cutting, Cryo reduced the cutting temperature, which had a positive impact on the alloy's machinability.
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页数:22
相关论文
共 53 条
[1]   Heat generation and temperature prediction in metal cutting: A review and implications for high speed machining [J].
Abukhshim, N. A. ;
Mativenga, P. T. ;
Sheikh, M. A. .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2006, 46 (7-8) :782-800
[2]  
[Anonymous], 2015, ADVANTEDGE 7 1 US MA
[3]   Identification of a friction model for minimum quantity lubrication machining [J].
Banerjee, Nilanjan ;
Sharma, Abhay .
JOURNAL OF CLEANER PRODUCTION, 2014, 83 :437-443
[4]   Response surface methodology (RSM) as a tool for optimization in analytical chemistry [J].
Bezerra, Marcos Almeida ;
Santelli, Ricardo Erthal ;
Oliveira, Eliane Padua ;
Villar, Leonardo Silveira ;
Escaleira, Luciane Amlia .
TALANTA, 2008, 76 (05) :965-977
[5]   InconelA®718 superalloy machinability evaluation after laser cladding additive manufacturing process [J].
Calleja, Amaia ;
Urbikain, Gorka ;
Gonzalez, Haizea ;
Cerrillo, Iker ;
Polvorosa, Roberto ;
Lamikiz, Aitzol .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 97 (5-8) :2873-2885
[6]   Comparison between sustainable cryogenic techniques and nano-MQL cooling mode in turning of nickel-based alloy [J].
Chetan ;
Ghosh, S. ;
Rao, P. V. .
JOURNAL OF CLEANER PRODUCTION, 2019, 231 :1036-1049
[7]   Environmental, technological and economical aspects of cryogenic assisted hard machining operation of inconel 718: A step towards green manufacturing [J].
Danish, Mohd ;
Gupta, Munish Kumar ;
Rubaiee, Saeed ;
Ahmed, Anas ;
Sarikaya, Murat ;
Krolczyk, Grzegorz M. .
JOURNAL OF CLEANER PRODUCTION, 2022, 337
[8]   Dry machining of Inconel 718, workpiece surface integrity [J].
Devillez, A. ;
Le Coz, G. ;
Dominiak, S. ;
Dudzinski, D. .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2011, 211 (10) :1590-1598
[9]   Cryogenic turning of the Ti-6Al-4V alloy with modified cutting tool inserts [J].
Dhananchezian, M. ;
Kumar, M. Pradeep .
CRYOGENICS, 2011, 51 (01) :34-40
[10]   Semi-Empirical Prediction of Residual Stress Profiles in Machining IN718 Alloy Using Bimodal Gaussian Curve [J].
Dong, Penghao ;
Peng, Huachen ;
Cheng, Xianqiang ;
Xing, Yan ;
Tang, Wencheng ;
Zhou, Xin .
MATERIALS, 2019, 12 (23)