Image Processing Approach to Investigate the Correlation between Machining Parameters and Burr Formation in...

Area of Science:

• Materials Science and Engineering
• Manufacturing Processes
• Surface Metrology

Background:

• Precise machining is essential for modern manufacturing, impacting assembly efficiency and product quality.
• Micro-milling of materials like AISI 316 is critical for producing compatible components.
• Burr formation and slot dimension control are key challenges in micro-milling.

Purpose of the Study:

• To investigate the influence of machining parameters on burr formation and slot dimensions.
• To analyze the effects of cutting speed, feed rate, and depth of cut in micro-milling AISI 316.
• To establish methods for characterizing and minimizing burr formation.

Main Methods:

• Micro-milling experiments were performed on AISI 316 material.
• Scanning electron microscopy (SEM) was used for detailed examination of burr formations.
• Image processing techniques were employed for accurate quantification of burr and slot widths.

Main Results:

• Feed rate and depth of cut were identified as significant factors influencing burr formation.
• Lower feed rates and depths of cut led to reduced burr formation.
• Higher feed rates correlated with more pronounced burrs; down-milling sides exhibited wider burrs than up-milling sides.

Conclusions:

• Machining parameters, particularly feed rate and depth of cut, can be effectively managed to minimize burr formation during micro-milling.
• Image processing provides a reliable method for quantifying burr characteristics.
• Optimizing these parameters enhances the precision and quality of micro-milled components.