Personally customized false eyelash manufacturing method

Abstract

The invention provides a private customized false eyelash manufacturing method. The method comprises the following steps: collecting eye data; performing digital modeling on false eyelashes according to the eye data; preparing a material of the false eyelashes according to the digital modeling; and manufacturing false eyelashes from the material by adopting a laser cutting technology. The method has the advantages that medical engineering design and precision manufacturing are combined, it is ensured that each pair of eyelashes is perfectly matched with the eye biological characteristics of a user through multiple process control points, and the customization precision, production efficiency and biological compatibility of false eyelashes are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of false eyelashes, in particular to a method for producing customized false eyelashes. Background Art

[0002] As a key product in the beauty industry, false eyelashes are manufactured using a technology that integrates material science, fine craftsmanship, and aesthetic design. This technology is evolving from a labor-intensive process to one that is intelligent and environmentally friendly. In the future, with breakthroughs in biomaterials and micro-nanofabrication technologies, false eyelashes will not only serve as a beauty tool but may also integrate sensors (such as those for monitoring intraocular pressure) or drug-release capabilities, becoming part of "smart wearables." Companies must balance cost, innovation, and compliance to meet consumers' growing demands for safety, personalization, and sustainability. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for producing customized false eyelashes to solve the problem in the existing technology that companies need to balance cost, innovation and compliance to meet consumers' higher demands for safety, personalization and sustainability.

[0004] The present invention provides a method for producing customized false eyelashes, comprising:

[0005] Collect eye data;

[0006] Digitally model false eyelashes based on eye data;

[0007] Prepare the material of the false eyelashes according to digital modeling;

[0008] Laser cutting technology is used to make false eyelashes from the material.

[0009] The collecting of eye data includes:

[0010] Take photos of the customer's eye shape;

[0011] Perform 3D dynamic scanning based on the pictures taken;

[0012] Biomechanical analysis was performed on the model obtained by 3D dynamic scanning.

[0013] The 3D dynamic scanning based on the pictures taken includes:

[0014] An infrared structured light scanner was used to obtain the curvature radius of the eyelid;

[0015] Use an infrared structured light scanner to obtain the eyelash root baseline;

[0016] The length of the palpebral fissure was obtained using an infrared structured light scanner.

[0017] Performing biomechanical analysis on the model obtained from 3D dynamic scanning includes:

[0018] Recording the swinging amplitude of eyelashes and the movement speed of eyelids when the customer blinks through a camera;

[0019] Measuring the weight-bearing threshold at the root of eyelashes through a pressure sensor.

[0020] Digitally modeling the false eyelashes based on the eye data includes:

[0021] Generating the model for digital modeling;

[0022] Setting the tuft parameters for digital modeling;

[0023] Performing mechanical simulation on the digital modeling.

[0024] Generating the model for digital modeling includes:

[0025] Generating a B-spline curve basis;

[0026] Calculating the width of the support band.

[0027] Setting the tuft parameters for digital modeling includes:

[0028] Setting the follicle positions based on the Voronoi algorithm, including setting the root area, middle transition area, and top densification area of the follicles.

[0029] Performing mechanical simulation on the digital modeling includes:

[0030] Performing a wind tunnel test on the digital modeling;

[0031] Performing a fatigue test on the digital modeling.

[0032] Preparing the materials for the false eyelashes based on the digital modeling includes:

[0033] Preparing a multi-layer composite substrate using a vacuum coating technique;

[0034] Performing plasma surface modification on the multi-layer composite substrate.

[0035] The multi-layer composite substrate includes a bottom layer, an intermediate layer, and a surface layer. The bottom layer is a medical-grade TPU film, the intermediate layer is a silk protein adhesive layer, and the surface layer is a PET shaping film.

[0036] As described above, a method for making customized false eyelashes according to the present invention has the following beneficial effects:

[0037] Combining medical engineering design with precision manufacturing, and ensuring that each pair of false eyelashes perfectly fits the user's eye biometrics through multiple process control points, which improves the customization accuracy, production efficiency, and biocompatibility of false eyelashes. Description of the Drawings

[0038] Figure 1 It is a flowchart of a method for making customized false eyelashes provided by an embodiment of the present invention. Detailed Embodiments

[0039] The following uses specific specific examples to illustrate the embodiments of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0040] It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Therefore, only the components related to the present invention are shown in the diagrams, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0041] It should be known that the structures, ratios, sizes, etc. shown in the diagrams of this specification are only used to cooperate with the content disclosed in the specification for those skilled in this technology to understand and read, and are not used to limit the limited conditions under which the present invention can be implemented. Therefore, they do not have a technical essence. Any modification of the structure, change of the proportional relationship, or adjustment of the size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope that can be covered by the technical content disclosed in the present invention. At the same time, the terms such as "upper", "lower", "left", "right", "middle", and "one" cited in this specification are only for the convenience of clear narration, and are not used to limit the scope under which the present invention can be implemented. The change or adjustment of their relative relationship, without substantial change in the technical content, should also be regarded as the scope within which the present invention can be implemented.

[0042] As Figure 1 shown, Figure 1 It is a flowchart of a method for making customized false eyelashes provided by an embodiment of the present invention. The method for making false eyelashes includes steps S1 - S4:

[0043] S1. Collect eye data; step S1 includes steps S11 - S13:

[0044] S11. Take a photo of the customer's eye shape.

[0045] In this embodiment, the planar analysis is based on the function of generating pictures by taking photos, and realizes the analysis of the customer's eye shape. For example, a professional camera is used to take pictures of the eyes from multiple angles to capture details (single / double eyelids, eye length, eye width, eye distance, eye corner arc, etc.).

[0046] During the process of planar shooting, an AI algorithm analysis can be implanted. Specifically, a pre-trained machine learning model (such as a convolutional neural network CNN) is used to automatically identify eye shape features:

[0047] 1. Classify single / double eyelids, eye fissure height, and the degree of upward / downward drooping of the outer eye corners.

[0048] 2. Quantify parameters: the arc of the eyelash growth line, the degree of eyeball protrusion, the eyelid thickness, etc.

[0049] S12. Perform a 3D dynamic scan based on the picture obtained by taking photos; step S12 includes steps S121 - S123:

[0050] S121. Use an infrared structured light scanner to obtain the radius of curvature of the eyelid.

[0051] In this embodiment, the accuracy of the infrared structured light scanner is set to ±0.02 mm, and the average radius of curvature of the eyelid is 7.5 - 9.2 mm.

[0052] S122. Use an infrared structured light scanner to obtain the reference line of the eyelash roots.

[0053] In this embodiment, 15 - 18 anchor points need to be located for the reference line of the eyelash roots.

[0054] S123. Use an infrared structured light scanner to obtain the length of the eye fissure.

[0055] In this embodiment, the length of the eye fissure is the distance from the inner canthus to the outer canthus, and the standard value is 28 ± 2 mm.

[0056] S13. Perform a biomechanical analysis on the model obtained from the 3D dynamic scan. Step S13 includes steps S131 - S132:

[0057] S131. Record the swing amplitude of the eyelashes and the movement speed of the eyelids when the customer blinks through a camera.

[0058] In this embodiment, it is recorded through high-speed shooting (240 fps): the swing amplitude of the eyelashes when blinking (the normal opening and closing angle is 42° - 55°); the movement speed of the eyelids (the average closing speed is 18 cm / s).

[0059] S132. Measure the bearing threshold of the eyelash roots through a pressure sensor.

[0060] In this embodiment, the bearing threshold of the eyelash roots: single point > 0.8 N.

[0061] S2. Digitally model false eyelashes based on eye data; Step S2 includes steps S21 - S23:

[0062] S21. Generate the model for digital modeling; Step S21 includes steps S211 - S212:

[0063] S211. Generate the B - spline curve basis.

[0064] In this embodiment, the scanned data is imported into Rhino Grasshopper to generate the B - spline curve basis (curvature continuity G3) and automatically calculate the support band width. The B - spline curve basis is a set of piece - wise polynomial functions defined by a knot vector, which is used to construct spline curves with local controllability and adjustable continuity. The B - spline basis functions are generated through the knot vector and recurrence formula, achieving local control, flexible continuity adjustment, and convex hull properties, and are the core tools for complex curve modeling. Its mathematical structure balances computational efficiency and design freedom and is widely used in fields such as CAD, animation, and numerical analysis. Grasshopper is a parametric modeling plug - in under the Rhino environment, mainly used to generate models through program algorithms. Grasshopper allows users to quickly create complex geometric shapes and structures by dragging different components and connecting the data flow between them through an intuitive graphical programming interface. This node - based interface makes parametric design, algorithm - generated models, and simulation of complex systems easier to understand and operate.

[0065] S212. Calculate the support band width.

[0066] In this embodiment, the support band width can be a gradient from 0.8 - 1.2 mm. In mathematics and computer graphics, the support band width (SupportWidth) usually refers to the interval length of the non - zero region of a function within its domain. Specifically, in the context of B - spline basis functions, the support band width describes the range of influence of a single basis function on the curve. The support band width is a key property of the B - spline basis function, which determines the range of influence of a single control point on the curve. Its value is jointly determined by the knot vector and the degree of the basis function, directly affecting the local controllability, computational efficiency, and continuity of the curve. Understanding this concept helps optimize design parameters in geometric modeling and numerical calculations to achieve efficient and flexible curve and surface construction.

[0067] S22. Set the hair bundle parameters for digital modeling; among them, the hair follicle positions are set based on the Voronoi algorithm, including setting the root region, middle transition region, and top densification region of the hair follicles.

[0068] In this embodiment, the Voronoi algorithm is a mathematical tool for generating Voronoi diagrams (also known as Thiessen polygons). Its core idea is to divide space into multiple regions based on a given set of seed points (or sites) such that the distance from any point within each region to its corresponding seed point is less than the distance to all other seed points. Among them, the root region is set to a density of 120 roots / cm 2 , with a diameter of 0.08 mm; the middle transition region is set to a density of 80 roots / cm 2 , with a diameter of 0.05 mm; the top encryption region is set to a density of 150 roots / cm 2 , with a length of 13 mm.

[0069] S23. Conduct a mechanical simulation on the digital model. Step S23 includes steps S231 - S232:

[0070] S231. Conduct a wind tunnel test on the digital model.

[0071] In this embodiment, both the wind tunnel test and the fatigue test are carried out in ANSYS Workbench. The environmental coefficient settings for the wind tunnel test include simulating the deformation amount < 2 mm under an 8 - level wind force. ANSYS Workbench is a collaborative simulation environment launched by ANSYS Inc., aiming to solve the heterogeneous problems of CAE software in the enterprise product R & D process. It builds a simulation system with independent intellectual property rights by integrating multi - disciplinary heterogeneous CAE technologies and supports various analysis types such as structural statics, structural dynamics, rigid body dynamics, and fluid dynamics. The wind tunnel test is an experimental method of placing an object model in a wind tunnel to study the gas flow and its interaction with the model to understand the aerodynamic characteristics of the actual object.

[0072] S232. Conduct a fatigue test on the digital model.

[0073] In this embodiment, the environmental coefficient settings for the fatigue test include a deformation rate < 3% after 5000 opening and closing cycles. The fatigue test refers to evaluating the durability performance of a material under cyclic loading by conducting a fatigue test on the material when it is subjected to cyclic loading. The main purpose of the fatigue test is to determine the fatigue limit and fatigue life of the material, that is, the number of cycles that the material can withstand under a certain stress amplitude.

[0074] In addition, the digital model can also be corrected through an AI algorithm. That is, the 3D model of the eyelashes can be corrected using the AI algorithm, which can be achieved through the following steps, combining computer vision, deep learning, and 3D modeling technologies to improve the naturalness and personalized adaptation of the model:

[0075] I. Construct a 3D eyelash database: Obtain the geometric data of real eyelashes (such as point clouds or mesh models) through a high-precision 3D scanner, or export diverse eyelash templates from professional modeling software. Label parameters such as the density, length, curl, and growth direction of the eyelashes to form a structured dataset.

[0076] The data volume can also be expanded through transformations such as rotation, scaling, and distortion. Generate rendered images under different lighting conditions to enhance the robustness of the model.

[0077] II. Process the eyelash point cloud data, extract global and local geometric features, or directly analyze the mesh model to identify unnatural connections or abnormal topological structures. Thus, automatically detect areas with breaks, intersections, or uneven density in the eyelash model. Output a heat map of the defect locations to guide the correction direction.

[0078] III. Model correction based on the Generative Adversarial Network (GAN). First, conduct model design. Input a defective eyelash model and output a repaired 3D structure (such as using 3D-GAN or Voxel-GAN). Secondly, distinguish between the generative model and real eyelash data to enhance the authenticity of the generated details. At the same time, combine adversarial loss and reconstruction loss (such as Chamfer Distance) to ensure geometric consistency. Introduce an attention mechanism to focus on the fine generation of details at the tip and root of the eyelashes.

[0079] IV. Personalized parameter-driven adjustment. The user inputs parameters (such as curl, length, density). Through conditional vector embedding in the generation process, use a Variational Autoencoder (VAE) to map the user's needs to the latent space to guide model generation. Combine slider or gesture input to dynamically adjust parameters and render the correction effect in real time (requiring a lightweight model such as MobileNet3D).

[0080] By combining 3D geometric analysis and generative models, AI algorithms can efficiently correct the morphological defects of eyelash models and support personalized customization. In the future, with the integration of Neural Radiance Field (NeRF) and physical simulation (such as hair dynamics) technologies, AI-generated eyelashes will not only be statically realistic but also dynamically respond to facial expression changes, becoming one of the core components in virtual avatar construction.

[0081] S3. Prepare the materials for the false eyelashes according to digital modeling; Step S3 includes steps S31 - S32:

[0082] S31. Prepare a multi-layer composite substrate using vacuum coating technology; The multi-layer composite substrate includes a bottom layer, an intermediate layer, and a surface layer. The bottom layer is a medical-grade TPU film, the intermediate layer is a silk protein adhesive layer, and the surface layer is a PET shaping film.

[0083] In this embodiment, the bottom layer (medical-grade TPU film) is set to have a thickness of 50 μm and an oxygen permeability of 1200 cm 3 / m 2 ·24h; the middle layer (silk fibroin adhesive layer) is set to have a thickness of 5 μm; the surface layer (PET shaping film) is set to have a thickness of 20 μm and a modulus of 3.5 GPa.

[0084] S32. Perform plasma surface modification on the multi-layer composite substrate.

[0085] In this embodiment, the contact angle is increased from 75° to 152°, and the protein adsorption amount is reduced by 83%. Plasma surface modification is a technology that uses high-energy particles, free radicals, and active substances in plasma (ionized gas) to physically or chemically treat the material surface, aiming to change the surface composition, structure, morphology, or properties of the material without significantly affecting its bulk properties.

[0086] S4. Use laser cutting technology to make false eyelashes from the material.

[0087] In this embodiment, the equipment used is: IPG Photonics picosecond laser for cutting the shape. The set parameters of the laser are as follows:

[0088] Wavelength: 1064 nm (fundamental frequency) + 532 nm (second harmonic);

[0089] Power: 8 W (substrate cutting) / 3 W (hair bundle engraving);

[0090] Repetition frequency: 200 kHz;

[0091] Scanning speed: 2000 mm / s.

[0092] Determine the curl length of the eyelashes according to the distance between the eyebrows and eyes, cut the base contour (tolerance ±10 μm), three-dimensional engrave the hair bundles (taper of single eyelash 0.03 - 0.08), and process the ventilation hole array (diameter 30 μm, pitch 200 μm).

[0093] In addition, a Keyence 3D profiler can be used for on-line quality inspection, and the inspection indexes can be set as: height consistency of hair bundles (±5 μm), roughness Ra of the root bonding surface <0.2 μm.

[0094] False eyelashes can also be automatically woven according to the design parameters (materials can be selected from mink hair, protein fiber, etc.) and the eyelash base film can be rapidly prototyped through 3D printing technology to perfectly fit the eyelid curvature (suitable for sensitive eye types).

[0095] After the false eyelashes are made, when subsequent users make private customizations, they can be intelligently matched with the existing style library.

[0096] For example: According to the eye shape parameters, recommend suitable styles from the preset style library, giving priority to: support force (curling materials with stronger support for single eyelids), length gradient (styles with shorter front and longer back are suitable for those with drooping eye tails), and density distribution (round eyes can increase the density in the middle to elongate the eye shape).

[0097] Parametric generation during personalized customization: If the existing styles do not match, generate new designs through algorithms. For example, input the eye shape parameters, and then adjust the curvature, length (with an accuracy of 0.05 mm), and angle (such as 60° - 90° curling) of each cluster of eyelashes.

[0098] In addition, during subsequent personalized customization, virtual try-on can also be carried out. The wearing effect is rendered in real time through AR technology, supporting customers to fine-tune the parameters.

[0099] The above embodiments are only illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes completed by those with ordinary knowledge in the technical field without departing from the spirit and technical idea disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A method for making customized false eyelashes, characterized in that, Including: Collecting eye data; Digitally modeling false eyelashes based on the eye data; Preparing the materials for the false eyelashes according to the digital modeling; Using laser cutting technology to make false eyelashes from the materials.

2. The method for manufacturing false eyelashes according to claim 1, wherein The collecting of the eye data includes: Taking pictures of the customer's eye shape; Performing 3D dynamic scanning based on the pictures obtained from the photographing; Performing biomechanical analysis on the model obtained from the 3D dynamic scanning.

3. The method for manufacturing false eyelashes according to claim 2, characterized in that, The performing of 3D dynamic scanning based on the pictures obtained from the photographing includes: Using an infrared structured light scanner to obtain the curvature radius of the eyelid; Using an infrared structured light scanner to obtain the root baseline of the eyelashes; Using an infrared structured light scanner to obtain the palpebral fissure length.

4. The method for manufacturing false eyelashes according to claim 3, characterized in that, The performing of biomechanical analysis on the model obtained from the 3D dynamic scanning includes: Recording the swing amplitude of the eyelashes and the movement speed of the eyelid when the customer blinks through photography; Measuring the root load-bearing threshold of the eyelashes through a pressure sensor.

5. The method for manufacturing false eyelashes according to claim 2, wherein, The digitally modeling of the false eyelashes based on the eye data includes: Generating the model number of the digital modeling; Setting the tuft parameters of the digital modeling; Performing mechanical simulation on the digital modeling.

6. The method for manufacturing false eyelashes according to claim 5, wherein The generating of the model number of the digital modeling includes: Generating a B-spline curve basis; Calculating the width of the support band.

7. The method for manufacturing false eyelashes according to claim 6, wherein, The setting of the tuft parameters of the digital modeling includes: Setting the follicle positions based on the Voronoi algorithm, including setting the root area, middle transition area, and top encryption area of the follicles.

8. The method for manufacturing false eyelashes according to claim 7, characterized in that, The performing of mechanical simulation on the digital modeling includes: Performing wind tunnel testing on the digital modeling; Performing fatigue testing on the digital modeling.

9. The method for manufacturing false eyelashes according to claim 2, characterized in that, The preparing of the materials for the false eyelashes according to the digital modeling includes: Preparing a multi-layer composite substrate using vacuum coating technology; Performing plasma surface modification on the multi-layer composite substrate.

10. The method for manufacturing false eyelashes according to claim 9, wherein, The multi-layer composite substrate includes a bottom layer, an intermediate layer, and a surface layer. The bottom layer is a medical-grade TPU film, the intermediate layer is a silk protein adhesive layer, and the surface layer is a PET shaping film.

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