Parametric Study and Optimization of End-Milling Operation of AISI 1522H Steel Using Definitive Screening Design and...

Area of Science:

• Manufacturing Engineering
• Materials Science
• Tribology

Background:

• End-milling hard-to-cut materials like AISI 1522H steel presents significant challenges.
• Optimizing cutting parameters and lubrication is crucial for enhancing productivity, surface finish, and tool longevity.

Purpose of the Study:

• To investigate the end-milling performance of AISI 1522H steel using a novel vegetable oil blend (canola and olive oil) under minimum-quantity lubrication (MQL).
• To determine the optimal cutting parameters for improved surface quality, reduced cutting forces, minimized tool wear, and maximized material removal rate.

Main Methods:

• Utilized a definitive screening design (DSD) to plan experimental runs.
• Employed analysis of variance (ANOVA) to identify significant process parameters.
• Developed nonlinear prediction models for response variables (surface roughness, cutting forces, tool wear, material removal rate).
• Applied the combinative distance-based assessment (CODAS) method with criteria importance through inter-criteria correlation (CRITIC) for multi-response optimization.

Main Results:

• Feed rate was identified as a significant factor influencing all measured responses.
• Validated nonlinear prediction models accurately represented the relationships between parameters and responses.
• Optimized parameters determined were: spindle speed (1200 rpm), feed rate (320 mm/min), depth of cut (0.6 mm), width of cut (8 mm), and lubrication rate (100 mL/h).

Conclusions:

• The developed vegetable oil blend and optimized parameters effectively improved the end-milling process for AISI 1522H steel.
• The CODAS-CRITIC approach proved effective for multi-response optimization in this machining scenario.
• The findings offer valuable insights for sustainable and efficient machining of difficult-to-cut steels.