Sustainable machining: an experimental investigation and optimization of machining Inconel 825 with dry and MQL approach

被引:49
作者
Tamang, S. K. [1 ]
Chandrasekaran, M. [1 ]
Sahoo, A. K. [2 ]
机构
[1] NERIST, Mech Engn Dept, Itanagar, Arunachal Prade, India
[2] KIIT Univ, Sch Mech Engn, Bhubaneswar, Odisha, India
关键词
Sustainability; Inconel; 825; RSM; GA; Turning; SURFACE INTEGRITY; CUTTING PARAMETERS; COATED CARBIDE; SUPER ALLOY; SPEED; CVD; MACHINABILITY; WEAR;
D O I
10.1007/s40430-018-1294-2
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Sustainability is a vital issue for present and future generation, and it aims to obtain overall efficiency in terms of economic, environmental and social aspects. Inconel 825 belongs to the family of nickel-based super alloy and is widely used in the chemical and marine industries. This work attempts to investigate machining performance of Inconel 825 using physical vapor deposition-titanium nitrate inserts, with a focus on sustainable machining. The effect of cutting parameters, viz. cutting speed (v), feed (f) and depth of cut (d) on three aspects of sustainability has been explored in two different machining environments, viz. dry and minimum quantity lubrication (MQL). The experimental results show a significant improvement in MQL machining and tool wear, and cutting power is reduced by 16.57 and 8.47%, respectively, and surface roughness is improved by 10.41%. The interacting effects of parameters on responses are studied using 3-D surface plots; it shows cutting speed and feed are found as dominating parameters on all the three responses. The novelty of this work is to optimize the process for the sustainable production of components by optimizing the process parameters with multiple and conflicting objectives. The sustainable optimization using genetic algorithm provides surface roughness (R (a)) as 0.49 A mu m, tool flank wear (VB) as 110.68 A mu m and cutting power (P) as 5.44 kW with better convergent capability having 4% deviation. For the application of manufacturing industry, an optimization table is generated for selection of optimum process parameters for achieving desired surface roughness with minimum VB or minimum P.
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页数:18
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