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

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.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-23
DOI
https://doi.org/10.5281/zenodo.21506596
Primary Topic
Advanced machining processes and optimization
Type
article
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article

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

D. A. Deshmukh, Pratik Amol Meshram, Prof. Harshal B. Chothe
Zenodo (CERN European Organization for Nuclear Research)
Advanced machining processes and optimization
article

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

D. A. Deshmukh, Pratik Amol Meshram, Prof. Harshal B. Chothe
article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 16%
Advanced machining processes and optimization
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A Comprehensive Review on Tool Geometry Optimization in Drilling Processes for Enhancing Machining Performance — D. A. Deshmukh, Pratik Amol Meshram, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS