A Method for Determining the Minimum Thickness of the Cut Layer in Precision Milling

Area of Science:

• Materials Science and Engineering
• Manufacturing Processes
• Metrology

Background:

• The minimum cutting thickness (hmin) is crucial in machining, defining the transition from elastic/plastic deformation to chip formation.
• Current methods for measuring hmin are often complex and time-consuming, hindering industrial application.
• Accurate determination of hmin is essential for optimizing cutting processes and tool wear.

Purpose of the Study:

• To develop and validate a simplified, industrially applicable method for determining the minimum cutting thickness (hmin).
• To utilize a contact profilometer for direct and high-resolution measurement of hmin and related interaction zones.
• To investigate the influence of machining parameters on hmin and develop a predictive model.

Main Methods:

• Development of a simplified specimen preparation technique using rectangular specimens on an inclined plane.
• Direct measurement of hmin, tool-workpiece interaction zone length, and specimen inclination angle using a contact profilometer.
• Experimental testing on C45 steel, including ANOVA to assess the impact of grinding parameters (feed rate, cutting speed) on hmin.
• Development of a mathematical model to predict hmin based on cutting speed and feed per tooth.

Main Results:

• The contact profilometer method provides high-resolution data, reducing measurement error and simplifying the identification of tool-material interaction zones.
• The simplified specimen setup allows for smooth variation of cutting depth.
• Feed rate was identified as the dominant factor influencing hmin, accounting for 93% of the variation, while cutting speed had a lesser effect.
• A mathematical model was successfully developed to predict hmin.

Conclusions:

• The proposed contact profilometer method offers a simplified, accurate, and efficient approach for determining minimum cutting thickness in industrial settings.
• The findings highlight the significant impact of feed rate on hmin, providing valuable insights for process optimization.
• The developed mathematical model enables prediction of hmin, facilitating better control and efficiency in machining operations.