This research investigates the relationship between machining technology parameters and surface roughness to optimize the cost efficiency of machining processes. In modern manufacturing, particularly in the automotive sector, achieving the desired surface quality while minimizing costs is critical. By evaluating tools from various manufacturers under different combinations of cutting parameters—such as cutting speed, feed, and depth—this study focuses on determining the most effective settings for producing an optimal surface roughness. The experiments highlight that selecting appropriate technological parameters impacts the machining process’s surface finish and economic efficiency. This study provides insights into balancing surface quality requirements with cost constraints, contributing to more efficient and sustainable manufacturing practices.

This study focuses on the mechanical characterization of GGV30 vermicular cast iron. GGV30 has gained increasing recognition in the automotive and railway industries, particularly for its use in critical components, like brake discs and clutch parts. Given the demanding nature of these applications, a thorough understanding of the material's mechanical properties and their variations under different operating conditions is essential to ensuring reliability and performance. A comprehensive review of various testing methods is provided, to analyze the mechanical behaviors of GGV30. These methods assess key parameters such as strength, durability and hardness, which are crucial for evaluating suitability, for automotive applications. By conducting these investigations, this study lays the foundation for future machining tests, offering valuable data from the workpiece perspective. This approach enhances the testing process, by identifying critical factors, reducing redundant experiments and optimizing the overall assessment of the material's performance.