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2023 | Buch

Minimum Quantity Lubrication Machining

Process Analysis and Analytical Modeling

verfasst von: Xia Ji

Verlag: Springer Nature Singapore


Über dieses Buch

This book focuses on the effect of minimum quantity lubrication (MQL) on the mechanical and thermal history, which will mainly determine the quality of the machined components. By analyzing the details of the lubrication and cooling effects in MQL machining, the book provides readers with an accurate and fast way to predict the residual stress of machined components. These process analyses and quality prediction will be beneficial for understanding the MQL machining theory and its widespread application in industry.


Chapter 1. Introduction
With the rapid development of the manufacturing technology, the quality requirements of the machined components are getting higher and higher. The machined components not only require high geometric accuracy, but also superior mechanical properties such as fatigue strength, corrosion resistance, wear resistance and etc.
Xia Ji
Chapter 2. The Effects of MQL on Tribological Attributes in Machining
In order to establish the prediction model of cutting force and cutting temperature in MQL machining, the friction characteristics of MQL on the cutting model must be analyzed first. In the process of MQL machining, only a small amount of cutting fluid is sprayed in the cutting area by the compressed air. On one hand, a thin boundary lubrication film is formed at the interface of tool and chip and the tool and machined surface by physical adsorption or chemical reaction forming, which effectively reduce the friction coefficient, lower cutting force and reduce frictional heat.
Xia Ji
Chapter 3. Force-Temperature Coupled Prediction Model
According to the influence of minimum quantity lubrication (MQL) on the friction characteristics in cutting process, the effect of MQL on the cutting force and cutting temperature are discussed in details. Firstly, the force prediction model in orthogonal cutting is introduced with the given cutting temperature. Secondly, the temperature prediction model is introduced with the given cutting force. Finally, the coupling predictive model of cutting force and cutting temperature under MQL condition is established. Different from other prediction model, the proposed MQL prediction model does not relied upon the measurement of cutting temperature or cutting force, and it can directly predict the cutting force and cutting temperature according to the cutting conditions in the machining process.
Xia Ji
Chapter 4. Residual Stress Model in MQL Machining
Based on the coupling prediction model of cutting force and cutting temperature under minimum quantity lubrication (MQL), the prediction model of residual stress in MQL is introduced in details. Firstly, the stress distribution on the workpiece surface is calculated according to the Hertzian contact model based on the predicted cutting force and cutting temperature. Then, the stress distribution is substituted into the modified McDowell algorithm model to calculate the residual stress distribution on the machined surface under MQL condition.
Xia Ji
Chapter 5. Experimental Validation by Orthogonal Cutting of AISI 4130 Alloy
In order to verify the prediction model of MQL introduced in the previous chapters, the orthogonal turning test of AISI4130 alloy steel is conducted, the cutting force, cutting temperature and residual stress on the surface of the workpiece during the cutting process is measured. Comparisons are made between the experimental results and prediction results.
Xia Ji
Chapter 6. Sensitivity Analysis of Machined Residual Stress in MQL Machining
In order to quantitatively analyze how the machined residual stress varies with the cutting conditions in MQL machining, a sensitivity analysis of residual stress is carried out based on the verified MQL prediction model. The cutting conditions mainly include the MQL parameters, cutting parameters, and tool geometry parameters.
Xia Ji
Minimum Quantity Lubrication Machining
verfasst von
Xia Ji
Springer Nature Singapore
Electronic ISBN
Print ISBN