Three-Dimensional Topography Prediction in Milling Medically Difficult-to-Process Materials: Mechanism, Modeling and Evaluation

Abstract

Milling serves as the core manufacturing process for medical, difficult-to-process materials. The three-dimensional topography of machined surface directly determines the service performance, biocompatibility, and service life of medical implants. This work targets unclear formation mechanism, incomplete modeling factors, and insufficient verification methods of three-dimensional topography in milling medical difficult-to-process materials. It systematically reviews the research progress of three-dimensional topography modeling and prediction. The core generation mechanism is analyzed by coupling the tool-workpiece relative motion with the material dynamic response, with a focus on the deformation features of difficult-to-process medical materials. The three-dimensional topography modeling methods of side milling, end milling, and five-axis ball-end milling are elaborated. Model characteristics considering material properties, cutting conditions, and dynamic factors are compared. Validation and evaluation methods are summarized from two-dimensional contour, three-dimensional topography, and texture fractal features. Limitations of existing models in adaptability, multi-factor coupling, and accuracy-efficiency balance are pointed out. Future research directions of hybrid modeling driven by physics and data for medical, difficult-to-process materials are prospected. This review offers a theoretical framework for precision machining and quality control of medical key components.

Keywords

Surface topography / Milling processes / Generation mechanism / Predicting model / Medically difficult-to-process materials

Statement of the Use of Generative AI and AI-Assisted Technologies in the Writing Process

During the preparation of this manuscript, the authors used ChatGPT in order to refine the sentence overall. After using this service, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

Author Contributions

Conceptualization, Z.G. and Q.A.; Methodology, Z.G.; Software, Z.G.; Validation, Z.G., Z.X., T.Z., D.Y., L.W. and Q.A.; Formal Analysis, Z.G.; Investigation, Z.G. and Z.X.; Resources, T.Z., D.Y., L.W. and Q.A.; Data Curation, Z.G. and Z.X.; Writing-Original Draft Preparation, Z.G.; Writing-Review & Editing, Z.G., Z.X. and Q.A.; Visualization, Z.G.; Supervision, Q.A.; Project Administration, Q.A.; Funding Acquisition, Q.A.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data available on request.

Funding

The work is supported by National Natural Science Foundation of China (52375454).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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