Multi-Objective Optimization of Performance Indicators in Turning of AISI 1045 under Dry Cutting Conditions
نویسندگان
چکیده
In machining operations, minimizing the usage of resources such as energy, tools, costs, and production time, while maximizing process outputs surface quality productivity, has a significant impact on environment, sustainability, profit. this context, paper reports utilization advanced multi-objective algorithms for optimization turning-process parameters, mainly cutting speed, feed rate, depth cut, in dry AISI 1045 steel high-efficient process. Firstly, number experimental tests were conducted which forces temperatures are measured. Then material removal rate obtainable roughness determined examined range parameters. Next, regression models developed to formulate relationships between parameters four responses. After that, different algorithms, (1) Gray Wolf Optimizer (GWO) (2) Weighted Value (WVGWO), (3) Multi-Objective Genetic Algorithm (MOGA), (4) Pareto Search (MOPSA), applied. The results reveal that optimal running conditions turning obtained by WVGWO 0.050 mm/rev, speed 156.5 m/min, cut 0.57 mm. These produce high level 4460.25 mm3/min, addition satisfying with average 0.719 µm. found be dependent objective outcomes’ order. Moreover, comparative evaluation dimensional accuracy both wet operations was carried out, revealing minimal relative error 0.053% maximum two conditions. research work assist obtaining precise, optimal, cost-effective solutions, can deliver high-throughput, controllable, robust manufacturing when steel.
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ژورنال
عنوان ژورنال: Metals
سال: 2023
ISSN: ['2075-4701']
DOI: https://doi.org/10.3390/met13010096