Multi-Objective Optimization of Performance Indicators in Turning of AISI 1045 under Dry Cutting Conditions

被引:13
作者
Abbas, Adel T. [1 ]
Al-Abduljabbar, Abdulhamid A. [1 ]
El Rayes, Magdy M. [1 ]
Benyahia, Faycal [1 ]
Abdelgaliel, Islam H. [2 ,3 ]
Elkaseer, Ahmed [4 ,5 ,6 ]
机构
[1] King Saud Univ, Coll Engn, Dept Mech Engn, POB 800, Riyadh 11421, Saudi Arabia
[2] Amer Univ Cairo, Sch Sci & Engn, Dept Mech Engn, AUC Ave, New Cairo 11835, Egypt
[3] Fayoum Univ, Fac Engn, Dept Mech Engn, Al Fayyum 63514, Egypt
[4] Karlsruhe Inst Technol, Inst Automat & Appl Informat, D-76344 Eggenstein Leopoldshafen, Germany
[5] Port Said Univ, Fac Engn, Dept Prod Engn & Mech Design, Port Fouad 42526, Egypt
[6] British Univ Egypt BUE, Fac Engn, Dept Mech Engn, El Sherouk City 11837, Egypt
关键词
AISI; 1045; turning operation; dry-cutting condition; multi-objective optimization; cutting forces; cutting temperature; surface roughness; dimensional accuracy; performance indicator; MACHINING PARAMETERS; SURFACE-ROUGHNESS; TOOL LIFE; DESIGN; STEEL; WEAR;
D O I
10.3390/met13010096
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In machining operations, minimizing the usage of resources such as energy, tools, costs, and production time, while maximizing process outputs such as surface quality and productivity, has a significant impact on the environment, process sustainability, and profit. In this context, this paper reports on the utilization of advanced multi-objective algorithms for the optimization of turning-process parameters, mainly cutting speed, feed rate, and depth of cut, in the dry machining of AISI 1045 steel for high-efficient process. Firstly, a number of experimental tests were conducted in which cutting forces and cutting temperatures are measured. Then the material removal rate and the obtainable surface roughness were determined for the examined range of cutting parameters. Next, regression models were developed to formulate the relationships between the process parameters and the four process responses. After that, four different multi-objective optimization algorithms, (1) Gray Wolf Optimizer (GWO) and (2) Weighted Value Gray Wolf Optimizer (WVGWO), (3) Multi-Objective Genetic Algorithm (MOGA), and (4) Multi-Objective Pareto Search Algorithm (MOPSA), were applied. The results reveal that the optimal running conditions of the turning process of AISI 1045 steel obtained by WVGWO are a feed rate of 0.050 mm/rev, cutting speed of 156.5 m/min, and depth of cut of 0.57 mm. These conditions produce a high level of material removal rate of 4460.25 mm(3)/min, in addition to satisfying the surface quality with a roughness average of 0.719 mu m. The optimal running conditions were found to be dependent on the objective outcomes' order. Moreover, a comparative evaluation of the obtainable dimensional accuracy in both dry and wet turning operations was carried out, revealing a minimal relative error of 0.053% maximum between the two turning conditions. The results of this research work assist in obtaining precise, optimal, and cost-effective machining solutions, which can deliver a high-throughput, controllable, and robust manufacturing process when turning AISI 1045 steel.
引用
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页数:22
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