Sensitivity analysis and acoustic emission-based quality improvement in MQL-assisted turning of SCM۴۴۰ steel

SCM۴۴۰ steel is extensively utilized in industrial applications due to its advantageous mechanical properties. However, challenges such as vibration and wear can arise during its machining. To address these issues in a cost-effective manner, Minimum Quantity Lubrication technology has emerged as an effective alternative. Acoustic emission signals and vibration measurements serve as reliable indicators for monitoring tool wear and surface roughness. Undesirable phenomena occurring during machining can be employed as diagnostic parameters to assess process behavior. The evaluation of various parameters through regression analysis facilitates the identification of faults and inefficiencies in the machining process. Key process variables can then be leveraged to enhance product quality and optimize production efficiency. Among these, feed rate is identified as the most sensitive factor influencing surface roughness, while depth of cut is recognized as the most sensitive factor affecting tool wear, both exerting significant influence on overall machining quality.

کلیدواژه ها:

MQL ، Sensitivity Analysis ، Machining Quality ، SCM۴۴۰