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首页> 外文期刊>Journal of the Institution of Engineers (Inida) >Optimization of MQL Parameters During Turning for the Minimization of Flank Wear using DoE, PSO and SAA
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Optimization of MQL Parameters During Turning for the Minimization of Flank Wear using DoE, PSO and SAA

机译：使用DoE，PSO和SAA优化车削过程中的MQL参数以最小化侧面磨损

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摘要

The concept of minimum quantity lubrication (MQL) has come into practice since a decade ago in order to overcome the disadvantages of flood cooling. This experimental investigation deals with the effects of MQL parameters during turning for the minimization of flank wear with surface roughness as constraint. The parameters of MQL selected are density of coolant, mass flow rate of coolant and pressure of air. The selected MQL parameters are varied through four levels. The flank wear values of the cutting inserts after machining are observed and recorded. The best levels of MQL parameters are identified by using Taguchi's design of experiments. A validation experiment is conducted with the identified best levels of parameters and the corresponding flank wear value is recorded. This analysis further inter-relates the performances of particle swarm optimization and simulated annealing algorithm (SAA). The result obtained from SAA is comparatively better than that of the results obtained from other techniques.
机译：最小量润滑（MQL）的概念自10年前就开始应用，以克服洪水冷却的缺点。此实验研究处理了车削过程中MQL参数的影响，以以表面粗糙度为约束条件来最小化侧面磨损。选择的MQL参数是冷却液的密度，冷却液的质量流量和空气压力。所选的MQL参数分为四个级别。观察并记录加工后切削刀片的侧面磨损值。通过使用Taguchi的实验设计，可以确定MQL参数的最佳水平。用确定的最佳参数水平进行验证实验，并记录相应的侧面磨损值。该分析进一步将粒子群优化和模拟退火算法（SAA）的性能相互关联。从SAA获得的结果比从其他技术获得的结果要好。

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