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<p>Hybrid abrasive flow finishing (HAFF) is an advanced process for achieving superior surface integrity in complex geometries and hard-to-machine materials, such as superalloys and ceramics. This process integrates auxiliary energies, including ultrasonic vibrations, magnetic fields, laser heating, and electrochemical reactions, with fluid dynamics to enhance abrasive particle interactions. The fundamental removal mechanisms, encompassing micro-cutting, plowing, and shearing, were analyzed to reveal synergies that yielded material removal rates up to 90% higher and surface roughness reductions to sub-micron levels. Advanced computational tools, such as computational fluid dynamics (CFD) for media flow, finite element analysis (FEA) for stress distributions, discrete element method (DEM) for particle behavior, and molecular dynamics simulation (MDS) for nanoscale abrasion and atomic interactions, enable predictive optimization and the transition from empirical to data-driven design of HAFF. Machine learning facilitates adaptive parameter control and real-time monitoring in hybrid variants, such as ultrasonic, magnetic, and rotational electrochemical configurations. These applications extend to additive manufacturing post-processing, aerospace components, biomedical implants, and microelectronics, where they mitigate defects such as porosity. However, scalability limitations, sustainable media development, and computational precision challenges persist. The roadmap outlines AI integration, IoT-enabled systems, and eco-friendly abrasives for Industry 4.0 compliance. This review synthesizes recent advancements to guide precision-engineering innovations.</p>

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Multiphysics Modeling and Synergistic Mechanisms in Hybrid Abrasive Flow Finishing of Hard-to-Machine Materials: A State-of-the-Art Review

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Abdul Wahab Hashmi,
  • Yebing Tian,
  • Jinoop Arackal Narayanan,
  • Mamilla Ravi Sankar,
  • Mohammed Jameel,
  • M. Ijaz Khan

摘要

Hybrid abrasive flow finishing (HAFF) is an advanced process for achieving superior surface integrity in complex geometries and hard-to-machine materials, such as superalloys and ceramics. This process integrates auxiliary energies, including ultrasonic vibrations, magnetic fields, laser heating, and electrochemical reactions, with fluid dynamics to enhance abrasive particle interactions. The fundamental removal mechanisms, encompassing micro-cutting, plowing, and shearing, were analyzed to reveal synergies that yielded material removal rates up to 90% higher and surface roughness reductions to sub-micron levels. Advanced computational tools, such as computational fluid dynamics (CFD) for media flow, finite element analysis (FEA) for stress distributions, discrete element method (DEM) for particle behavior, and molecular dynamics simulation (MDS) for nanoscale abrasion and atomic interactions, enable predictive optimization and the transition from empirical to data-driven design of HAFF. Machine learning facilitates adaptive parameter control and real-time monitoring in hybrid variants, such as ultrasonic, magnetic, and rotational electrochemical configurations. These applications extend to additive manufacturing post-processing, aerospace components, biomedical implants, and microelectronics, where they mitigate defects such as porosity. However, scalability limitations, sustainable media development, and computational precision challenges persist. The roadmap outlines AI integration, IoT-enabled systems, and eco-friendly abrasives for Industry 4.0 compliance. This review synthesizes recent advancements to guide precision-engineering innovations.