Performance evaluation in micro-milling of Inconel 718 with coated tools through an integrated optimization framework

Area of Science:

• Manufacturing Engineering
• Materials Science

Background:

• Micro-milling is crucial for miniaturized systems in aerospace, biomedical, and microelectronics.
• Challenges include tool wear, burr formation, and size effects in high-strength alloys like Inconel 718.

Purpose of the Study:

• To investigate the machinability of Inconel 718 using low-speed micro-milling.
• To assess the impact of uncoated and coated micro-end mills on surface roughness, tool wear, and burr formation.
• To determine optimal machining parameters for Inconel 718 micro-milling.

Main Methods:

• Utilized Taguchi L16 orthogonal array to study cutting speed, feed rate, depth of cut, and tool coating.
• Employed Analysis of Variance (ANOVA) for statistical evaluation.
• Applied Grey Relational Analysis (GRA) and Response Surface Methodology (RSM) for optimization.

Main Results:

• TiAlN coatings improved surface finish, nACo coatings reduced burrs, and uncoated tools showed better wear resistance.
• Optimal conditions identified: 10.5 m/min cutting speed, 1.5 μm/tooth feed, 120 μm depth of cut with uncoated tools.
• RSM achieved average reductions of 23.81% in surface roughness, 11.49% in tool wear, and 18.11% in burr formation.

Conclusions:

• The integrated Taguchi-ANOVA-GRA-RSM Optimization (TANGRO) framework effectively identifies optimal micro-milling conditions.
• Findings provide robust insights for enhancing machining performance of Inconel 718 in micro-scale applications.