A Comprehensive Review on Tool Geometry Optimization in Drilling Processes for Enhancing Machining Performance

Subject area: Mechanical Engineering DOI: https://doi.org/10.5281/zenodo.21506596

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Abstract

Drilling is one of the most important machining operations used in manufacturing industries, where drilling performance is significantly influenced by drill tool geometry and machining conditions. This review paper presents a comprehensive overview of the influence of tool geometry parameters, including point angle, helix angle, rake angle, clearance angle, and chisel edge geometry, on drilling quality, cutting forces, burr formation, tool wear, and hole accuracy. Recent developments in experimental investigations, statistical modelling, finite element analysis, and multi-objective optimization techniques are critically reviewed to evaluate their effectiveness in improving machining performance. The paper also discusses the application of modern optimization approaches such as Response Surface Methodology, Grey Relational Analysis, Genetic Algorithms, Particle Swarm Optimization, and artificial intelligence-based methods for drill design optimization. Furthermore, current research trends, existing challenges, research gaps, and future opportunities related to sustainable manufacturing and Industry 4.0-enabled intelligent drilling systems are highlighted. The review concludes that integrated optimization of drill geometry and machining parameters can significantly improve productivity, machining quality, tool life, and overall manufacturing efficiency while supporting sustainable and smart manufacturing practices.

Keywords

Drilling ProcessTool Geometry OptimizationMachining PerformanceStatistical ModellingMulti-Objective Optimization

Cite this article

Pratik Amol Meshram, Prof. Harshal B. Chothe, Prof. D. A. Deshmukh (2026). A Comprehensive Review on Tool Geometry Optimization in Drilling Processes for Enhancing Machining Performance. International Innovations & Scholarly Trends Journal, 2(7), 759–772. https://doi.org/10.5281/zenodo.21506596

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© 2026 — Authors retain the copyright of this article. This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.