Selective in-mold bonding 4D injection molding device and product deformation regulation and control method

Abstract

The invention discloses a selective in-mold bonding 4D injection molding device and a product deformation regulation and control method, and belongs to the technical field of material molding. The device comprises an injection molding machine, a mold and a selective in-mold bonding system consisting of a mechanical arm, a gripper, an insert block and a control system. The method comprises the following steps: designing and preparing an insert serving as a part of a product; the insert block is positioned and fixed to a preset position of a mold cavity through a mechanical arm; injection molding is carried out, so that the molten material and the insert block are bonded in the mold; and ejecting the product. According to the invention, the specific insert block is selectively embedded into the mold cavity, non-uniform temperature and pressure gradients are actively established in space and time dimensions, and the spatial and temporal distribution difference of material volume shrinkage is regulated and controlled, so that the buckling deformation of a product is accurately controlled. And in combination with a response surface method or an artificial intelligence algorithm, process parameters can be reversely deduced according to target deformation, programmable control of product shapes and batch production of'different models' are realized, and the production flexibility and the intelligent level are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of material molding technology, specifically to a selective in-mold bonding 4D injection molding apparatus and deformation control method for injection molding and shape control of products. Background Technology

[0002] Polymer materials are high-molecular materials widely used in agriculture, construction, transportation, electrical and electronic industries, and daily life. Their molding processes mainly include extrusion molding, injection molding, calendering, and melt spinning. Different process parameters can affect the quality of the finished product. Injection molding is the cornerstone of mass-produced plastic products and is renowned for its efficiency and versatility. Furthermore, the field of injection molding has expanded to include rubber, metals, ceramics, glass, wood, and composite materials. The growing global demand for polymer components in food, medical, transportation, packaging, and electronics products highlights the need for efficient injection molding. Injection molds are typically made of metal to withstand high pressure and clamping forces, representing a significant investment. While a single mold is usually expensive, it can typically produce tens of thousands of products.

[0003] Injection-molded products are typically formed in the same mold. The ideal manufacturing goal is to achieve "identical" products, meaning high repeatability and minimal dimensional deviation, which are key indicators for precision injection molding. Within the injection mold cavity, localized changes in temperature (T) and pressure (p) cause uneven volume shrinkage (Δv) in the material, leading to warping deformation in the shaped product. Therefore, achieving "zero warpage" in the final product has become the ideal goal for injection molding engineers and scientists in the field of polymer molding. Conformal cooling runner mold design and intelligent process control technologies have been developed to reduce process-induced dimensional deviations, thereby achieving the ideal of "identical" production. However, due to the complex structure of the injection mold cavity and the inherent spatiotemporal thermomechanical behavior and shrinkage anisotropy of the raw materials, "absolute zero warpage" is theoretically still impossible to achieve.

[0004] Compared to conventional injection molding, which aims to eliminate warpage, this invention proposes a reverse approach, utilizing the shrinkage properties of raw materials to mold products of different shapes using the same mold, achieving "one mold, different results" production. This concept is termed four-dimensional (4D) injection molding, which involves generating non-uniform temperature T and pressure p distributions in the spatiotemporal dimensions to induce differential volume shrinkage Δv and specific deformations in the product, thereby enabling the batch production of products with different shapes, properties, and functions from a single mold. In the spatial dimension, the volume shrinkage Δv of the product includes flow shrinkage (Δv... sl ), lateral contraction (Δv) sw ) and thickness shrinkage (Δvst In the time dimension, volumetric shrinkage Δv includes intramolecular shrinkage (Δv). t1 ) and post-molding shrinkage (Δv t2 ). Δv t1 This causes in-plane mold constraint deformation, and Δv t2 This leads to out-of-plane free deformation. The deformation of injection-molded articles is attributed to differences in spatiotemporal volumetric shrinkage Δv driven by anisotropic effects of non-uniform thickness, temperature T, and pressure p, as well as the orientation of molecular chains, fibers, or fillers. From a regulatory perspective, these volumetric shrinkage Δv variations are influenced by material properties, article design, mold structure, and process conditions. When raw materials and mold design remain constant, 4D injection molding achieves shape customization by adjusting process conditions. However, existing technologies or process parameter adjustments offer limited control over the large deformation of articles. By introducing a 4D factor—time (t)—to extend the differential difference in spatiotemporal volumetric shrinkage Δv, a wide range of control over article shape and function can be achieved.

[0005] In the field of additive manufacturing, particularly in the technology known as 4D printing, techniques such as thermal activation, bonding, electric / magnetic fields, ultrasonic assistance, photo / photoinduced activation, and mesocrystalline interactions have been explored to control the shape and function of products over time. However, these techniques have not yet been adopted in conventional injection molding. This invention proposes a 4D injection molding method that combines these advanced technologies with the inherent capabilities of injection molding, enabling online adjustment of product deformation and facilitating the mass production of diverse products from a single mold without requiring modifications to the injection molding machine and mold.

[0006] Creating a T-gradient can drive transient deformation and motion in materials, and if transferred to injection molding, it can enable the production of articles with permanent deformation. While non-uniform T-distributions are common in conventional injection molding, the deformation induced by the T-gradient is usually constrained by the mold and process. To overcome this limitation, there is a need to develop a 4D injection molding apparatus and method capable of achieving large and permanent deformation of the product.

[0007] In the prior art, insert injection molding and film embedding injection molding (FIM) or in-mold decoration (IMD) technologies are partially similar to the implementation of this invention, but their purposes and principles are fundamentally different. The main technological trends are as follows:

[0008] Insert injection molding is a common method for manufacturing integrated components. Typically, a mold is designed to define the structure and location of the insert. During molding, the insert is pre-positioned, and molten plastic is injected into the mold cavity using an injection molding machine. The molten plastic encapsulates and bonds the insert together. After cooling and solidification, the mold is opened to obtain the integrated component. This technology is widely used in the production of automotive and electrical components. Inserts are typically made of metals, polymers, and fiber-reinforced polymer composites.

[0009] Prior art US7238307B2 relates to a method for pre-treating an insert to improve adhesion and replication of the molded surface during subsequent injection molding. The method includes providing an insert having a curvature that is measurably different from the average curvature of the molded surface, placing the insert in a suitable position on the molded surface, and hot-dip immersion of the insert. Hot-dip immersion is achieved by subjecting the insert to energy preferentially absorbed and distributed throughout the insert. Preferably, the insert is heated on one surface of the mold surface before the introduction of molten plastic, with the heat provided by infrared energy, such as broadband infrared energy. Furthermore, the insert may comprise a single layer or multiple layers, wherein one layer has one or more selected optical or physical properties. Examples of optical properties include polarization, color, photochromism, electrochromism, selective visible light transmittance, selective ultraviolet transmittance, selective infrared transmittance, a higher refractive index than at least one other layer, and a lower refractive index than at least one other layer. Examples of physical properties include abrasion resistance, impact resistance, chemical resistance, and mechanical support. This method can be used to achieve good replication in the final part, even if the insert curvature differs from the expected average curvature of the final molded part by more than 10%. This technology also relates to composite optical components fabricated using specific methods. This technology belongs to a one-piece molding technology, particularly emphasizing the consistency of insert curvature with the mold cavity surface and its application in optical product molding, but it does not constrain dimensions and positions. It also emphasizes the need for consistent product consistency and minimal curvature deviation; therefore, this technology does not address the purpose or means of controlling product deformation. Furthermore, its technical principles do not involve introducing time as a fourth dimension to realize the novel concept of 4D injection molding mentioned in this invention.

[0010] Film embedding injection molding (FIM), also known as in-mold decoration (IMD), is a technology similar in principle to insert injection molding. It allows for the one-step molding of plastic products with decorative or functional surfaces. The primary insert used in this technology is a plastic film, typically back-printed with decorations, which is then embedded into the mold after molding and finishing. As an in-mold decoration, FIM eliminates the need for separate steps such as painting or spraying for decorative or functional plastic components, even those with complex shapes. This expands the manufacturer's design and manufacturing flexibility and significantly reduces costs, time, and machinery investment.

[0011] Prior art KR102300175B9 discloses an insert molding lamination method involving embedding an insert film into an injection mold, filling the mold with resin, and molding the insert film integrally with the resin. The present invention is characterized by simplifying the process flow compared to existing insert film pretreatment methods, thereby reducing costs and shortening processing time. In the insert molding lamination method, the insert film is inserted into the injection mold, and the insert film is formed as an integral part of the injection molding resin. Since the first and second film layers are made of the same material, when deformation occurs due to heat during injection molding, defects such as warping or bending due to the same shrinkage rate can be minimized. Prior art DE102020128074A discloses an integral double-walled insert that can be designed such that its first insert and its second insert are integrally connected to each other, preferably made of the same material via an insertion connection portion. During the injection of a flowable, curable substance, this embedded connector can be encapsulated and molded by the latter, thus integrating the connector into the finished composite through force fit, shape fit, or cohesion. The objectives and implementation methods of the two related technologies mentioned above are fundamentally different from the objective and technical principle of this invention, which uses inserts to guide an imbalance in temperature and pressure gradients to generate large-scale warping deformation. Conversely, related technologies all mention minimizing warping or bending defects. Furthermore, the thin films or thin-walled products used as inserts in related technologies cannot achieve the controllable deformation of the product proposed in this invention, and they do not fundamentally involve the fourth dimension of time, thus not belonging to 4D injection molding.

[0012] In summary, while existing technologies involve insert bonding, none actively control the spatiotemporal distribution of volume shrinkage Δv by introducing a time dimension (t), nor do they treat product warpage as a controllable parameter. During insert injection molding, the heat transfer process at the bonding interface between the material and the insert causes Δv differences and residual stress, leading to warpage in the final product. Preheating or post-treatment techniques are typically required to eliminate this warpage. This invention, through reverse thinking, considers utilizing this principle of warpage by introducing time as a fourth dimension. By embedding inserts of specific shapes and sizes at specific locations, different temperature and pressure distributions and varying cooling and depressurization gradients over time are created, thereby amplifying warpage. The scale of warpage can be controlled through design and process parameter adjustments, thus achieving the 4D injection molding proposed in this invention. This invention uses a selective in-mold bonding system to embed inserts of specific shapes and sizes at specific locations, establishing non-uniform temperature and pressure gradients. By utilizing time-dependent cooling and depressurization processes, warpage is amplified, achieving programmable shape control. This contradicts the prior art's aim of "reducing warpage," demonstrating the innovation and creativity of this invention. Summary of the Invention

[0013] The present invention aims to solve the problems mentioned above.

[0014] The purpose of this invention is to provide an apparatus and method for 4D injection molding using selective in-mold bonding. The main approach involves establishing spatial and temporal gradients in the temperature and pressure of the filling material during the injection molding process. This is achieved through various means, including uneven temperature and pressure distribution, different cooling and depressurization rates, thickness variations, polymer chain orientation, and viscoelasticity and integral effects. These methods regulate the spatiotemporal distribution Δv(x, y, z, t) of material volume shrinkage in specific regions of the mold cavity, thereby achieving controlled deformation of the molded product. Further, using response surface methodology (RSM) or artificial intelligence algorithms, programmable control of the product's shape and deformation dimensions can be achieved. Moreover, 4D injection molding can be extended to composite materials and elastomers, enabling the creation of products with different shapes, sizes, and customized mechanical properties and functional requirements.

[0015] The technical solution adopted by this invention to solve its technical problem is:

[0016] A selective in-mold bonding 4D injection molding apparatus includes an injection molding machine, a mold, and a selective in-mold bonding system. The selective in-mold bonding system comprises a robotic arm, a gripper, inserts, and a control system. The inserts are part of the injection-molded product and are bonded in-mold with the material injected into the mold cavity. The mold includes a mold frame, a core, a cavity plate, and a support plate. The core forms the cavity structure and is fixed by the cavity plate. The cavity has space and a set position for the inserts. The cavity plate is bolted to the support plate, and the support plate is bolted to the mold frame.

[0017] Furthermore, the core has an insert positioning structure, which is a tiny pit.

[0018] Furthermore, the back of the insert is covered with double-sided adhesive for positioning the insert within the cavity.

[0019] Furthermore, the insert contains the same material as the injection-molded material.

[0020] Furthermore, the insert contains the same material as the injection-molded material, while also containing heterogeneous materials, including fibers, nanofillers, magnetic fillers, and inorganic fillers.

[0021] Furthermore, the selective in-mold bonding 4D injection molding apparatus also includes a preheating system for preheating the mold cavity and the insert surface.

[0022] A method for selective in-mold bonding 4D injection molding and product deformation control, using the aforementioned selective in-mold bonding 4D injection molding apparatus, comprises the following steps:

[0023] Step 1: Based on the shape requirements of the product, pre-design the product and insert structure, select the insert as part of the product and attach it to the exact position of the whole product; at the same time, determine the shape and size of the insert and prepare the insert in advance;

[0024] Step 2: Install the mold onto the mold clamping system of the injection molding machine for mold adjustment; after the mold adjustment is completed, set the control system program of the selective in-mold bonding system. The program includes using a robotic arm and gripper to pick up the insert and place it into the cavity of the opened mold at a set position for fixation.

[0025] Step 3: Set the injection molding process conditions and carry out injection molding. Inject the molten material from the injection molding machine into the mold cavity, and the material adheres to the pre-embedded inserts in the mold.

[0026] Step 4: The injection molding machine opens the mold and ejects the product, completing one injection molding cycle.

[0027] Furthermore, the selective in-mold bonding 4D injection molding method also employs response surface methodology. Using the shape and size of the insert, the bonding position, and the injection molding process parameters as independent variables, and the warpage displacement of the product as the response variable, the experimental design is conducted using response surface methodology. Selective in-mold bonding 4D injection molding experiments are performed sequentially according to the designed experiments, and the warpage displacement of each obtained product is detected. The data of the independent and response variables are analyzed and processed using response surface methodology, and the parameters of the response surface model equation are regressed to obtain the equation. The warpage displacement of the product is manually determined based on the desired product shape and size, and then used as the target value. Based on the expectation function and the response surface model, the combination of independent variables with a high expectation value is calculated in reverse. Using the inversely derived combination of independent variables, the insert shape and size, bonding position, and injection molding process parameters are set respectively, and injection molding is performed to obtain products with the set target warpage displacement.

[0028] Furthermore, the accuracy of the response surface model is measured by the residuals and the coefficient of determination R0. 2 The smaller the residual, the closer the coefficient of determination is to 1, and the higher the accuracy.

[0029] Furthermore, the response surface methodology is replaced by experimental design and machine learning-based artificial neural network models.

[0030] Beneficial effects

[0031] 1) This invention enables rapid mass production of products of different shapes using a single set of molds and injection molding machines, achieving the production of injection-molded products that are "different from one mold";

[0032] 2) The selective in-mold bonding system of the present invention can realize the automatic embedding action of the insert. The control system drives the robotic arm and gripper to pick up the insert and place the insert in the pre-selected mold cavity position.

[0033] 3) Different shapes, sizes and positions of the inserts in this invention can lead to completely different temperature and pressure distributions, establish different temperature and pressure gradients, and cause different volume shrinkage rates inside the product after the inserts are bonded, which in turn leads to different warping deformations.

[0034] 3) The core of the present invention has an insert positioning structure inside, which is a tiny pit, which can facilitate the accurate positioning and fixing of the insert;

[0035] 4) The back of the insert of the present invention is covered with double-sided tape for positioning the insert in the cavity. This reduces the need for changes to the mold cavity structure and is simple and effective. The double-sided tape can be removed mechanically or washed off with solvent after molding.

[0036] 5) The insert of the present invention contains the same material as the injection-molded material. When the molten material covers and bonds the insert, the homogeneous material of the insert heats up due to contact with the molten material and partially melts and cools and solidifies together with the covered and bonded material. Because of the homogeneous material, a good interfacial bond can be formed without the need for additional bonding technology.

[0037] 6) The inserts of this invention contain the same materials as the injection-molded materials, and also contain heterogeneous materials, including fibers, nanofillers, magnetic fillers, and inorganic fillers. The orientation of the fibers can be further controlled to achieve more complex shapes. The nanofillers, magnetic fillers, and inorganic fillers can realize the functionality of the final product at the embedding position. For example, adding carbonaceous materials such as graphene, carbon nanotubes, and carbon black can realize the local thermal and electrical conductivity functionality control of the product. Adding magnetic fillers can realize the local magnetic control of the product. Adding inorganic fillers can realize the local flame retardancy, heat insulation, and other functional control of the product.

[0038] 7) The selective in-mold bonding 4D injection molding apparatus of the present invention also includes a preheating system for preheating the mold cavity and the surface of the insert, which is beneficial to the interfacial bonding between the insert and the injection material.

[0039] 8) The selective in-mold bonding 4D injection molded product deformation control method of the present invention is applicable to different materials and different products, and has the characteristics of flexibility and convenience; it can achieve the selectivity of "attaching wherever needed", and by changing the shape and size of the insert, it can guide the local deformation at the bonding position; at the same time, it can be combined with different injection molding process parameters to adjust the warpage displacement of the final product even under the same bonding position and the same bonding insert conditions.

[0040] 9) The selective in-mold bonding 4D injection molding method of this invention employs a combination of experimental design and response surface methodology, enabling programmable control of the product shape based on a model; that is, the independent variables (instrument shape and size, bonding position, and injection molding process parameters) are inferred from the specified product deformation displacement value. The core objective is to construct a quantitative prediction model for designing warpage, that is, to establish a positive mapping relationship between the temperature and pressure gradient field caused by actively applied in-mold bonding and the resulting product deformation. This is fundamentally different from traditional process optimization models used to eliminate warpage in terms of objective. The key to the experimental design and response surface methodology in this invention is to match independent variables such as insert shape and size, bonding position, and injection molding process parameters to obtain model-based control.

[0041] 10) The selective in-mold bonding 4D injection molding method of the present invention adopts an artificial neural network algorithm based on machine learning, which can realize artificial intelligence control of product shape and size.

[0042] 11) Wide applicability of materials: This invention is applicable to a variety of material types, not limited to polymers (such as typical materials for molding corresponding products, including polypropylene PP, polyethylene PE, ABS, polyamide PA6, PA66, polyoxymethylene POM, etc.), but also applicable to polymer-based composite materials (glass fiber / carbon fiber reinforced polymer composite materials), glass, lignin, rubber, elastomers, and ceramics.

[0043] 10) Application Areas: In actual production using existing technologies, batch molding of plastic products with varying dimensions typically requires the creation of new molds, resulting in very high costs. Different models of compressors, pumps, drives, and drones require fans and propellers with varying helical angles to adapt to different operating conditions. Cooling towers and heat exchangers often require filler products with different structural angles depending on operating conditions (different gas-liquid ratios, flow rates). This invention enables 4D injection molding of typical filler materials such as polypropylene (PP), modified PP, and flame-retardant PP, allowing for the mass production of filler products with different warpage angles. For components in electronic housings, automotive interiors, and home appliances, where assembly forces and springback forces need to be customized according to customer requirements, this invention can adjust the appropriate warpage deformation to achieve the required bending angle and clamping force, avoiding secondary heat treatment. For cover plates, shells, and sealing frames, different assembly tolerances need to be established to achieve different fitting deformations. This invention can compensate for assembly errors by adjusting minute deformations. For disposable, variable medical consumables, such as ankle braces, support plates, and medical implants, this invention can produce products of different shapes to meet the needs of patient body conformation in various injuries and conditions. When using inserts with added heterogeneous reinforcing materials, structural components with localized reinforcement functions can be prepared. Uneven shrinkage after demolding forms the target curvature or preload state, which is particularly suitable for reinforced thermoplastic composites with added continuous fiber filaments or continuous fiber cloth. When using inserts with added magnetic properties (such as blends with magnetite particles), components with magnetic attraction functions can be prepared. Traditional methods for producing the above-mentioned products require multiple sets of molds and secondary assembly. This invention, however, can achieve "multiple forms from the same mold," enabling mass production by simply adjusting the in-mold bonding position and process conditions of the inserts without changing the mold. Attached Figure Description

[0044] Figure 1 These are the overall system diagram and partial enlarged view of the selective in-mold bonding 4D injection molding apparatus of the present invention.

[0045] Figure 2 This is a product cavity model and actual photograph of Embodiment 1 of the present invention. In the figure, 1' to 3' correspond to the three selectable bonding positions of the insert.

[0046] Figure 3 This is a simulation result of the injection molding process of the product in Embodiment 1 of the present invention through 1' bonding, including the model used for simulation, the calculated melt front temperature distribution, the pressure distribution at the end of injection, and the in-mold shrinkage (Δv). t1 Displacement changes and post-modulus shrinkage (Δv) caused by ) t2 The resulting displacement change and total Z-direction warping deformation displacement.

[0047] Figure 4These are photographs of three products prepared by 4D injection molding at three different bonding positions (1' to 3') according to Embodiment 1 of the present invention.

[0048] Figure 5 This is the experimental design table and results of the response surface methodology for the selective in-mold bonding 4D injection molding method in Embodiment 2 of the present invention.

[0049] Figure 6 These are the three response surface models and equations corresponding to the bonding positions 1' to 3' obtained in Embodiment 2 of the present invention.

[0050] Figure 7 yes Figure 6 Model accuracy evaluation table

[0051] Figure 8 This is Embodiment 2 of the present invention, which describes programmable control of product shape based on target deformation displacement. The table includes the values ​​of five independent variables (I to V) obtained by back-calculating the target deformation displacement from the model, as well as the actual deformation displacement of the product obtained from experiments. The figure shows photographs of five products corresponding to the five target values, along with a graph of the correlation between the independent variable values ​​and the measured displacement and the target displacement for each product.

[0052] Figure 9 This is a hand-shaped cavity model, mold photograph, numerical simulation model, and simulation results of the warping deformation displacement of the product in the Z direction, as shown in Embodiment 3 of the present invention. In the figure, 1' to 4' correspond to four different bonding positions of different fingers.

[0053] Figure 10 This is the experimental design table and results of the response surface methodology for the selective in-mold bonding 4D injection molding and product deformation control method in Embodiment 3 of the present invention.

[0054] Figure 11 These are the response surface model equations and model accuracy evaluation results for the corresponding bonding position 1' obtained in Embodiment 3 of the present invention.

[0055] Figure 12 This is the programmable control of the product shape based on the target deformation displacement in Embodiment 3 of the present invention. The table includes the values ​​of five independent variables (I to V) obtained by back-calculating the target deformation displacement corresponding to the model, as well as the actual deformation displacement of the product obtained from experiments. The figure shows three product photos corresponding to the three target values, and a correlation diagram between the independent variable values ​​and the measured displacement and the target displacement for each product.

[0056] Figure 13The selective in-mold bonding 4D injection molding and product deformation control method of Embodiment 4 of the present invention uses six different shaped inserts to prepare product photos (dashed lines indicate the shape and bonding position of the corresponding inserts) (Figure A), product top view and deformation displacement test point position (Figure B), and actual test point displacement (Figure C).

[0057] Figures 1 to 4 In the middle: 1—injection molding machine, 2—mold, 3—selective in-mold bonding system, 4—product, 2-1—mold frame, 2-2—core, 2-3—cavity plate, 2-4—support plate, 2-5—cavity, 3-1—instrument, 1'~3'—bonding position.

[0058] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the invention. To better illustrate the embodiments, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings. Detailed Implementation

[0059] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] Example 1 like Figures 1-13 As shown, a selective in-mold bonding 4D injection molding apparatus includes an injection molding machine 1, a mold 2, and a selective in-mold bonding system 3. The selective in-mold bonding system 3 consists of a robotic arm, a gripper, an insert 3-1, and a control system. The insert 3-1 is part of the injection-molded product 4 and bonds in-mold with the material injected into the cavity. The mold 2 includes a mold frame 2-1, a core 2-2, a cavity plate 2-3, and a support plate 2-4. The core 2-2 forms a cavity 2-5 structure and is fixed by the cavity plate 2-3. The cavity 2-5 has space and a set position for placing the insert 3-1. The cavity plate 2-3 is bolted to the support plate 2-4, and the support plate 2-4 is bolted to the mold frame 2-1. Double-sided adhesive is attached to the back of the insert 3-1 for positioning it within the cavity 2-5.

[0062] This embodiment of the selective in-mold bonding 4D injection molding and product deformation control method uses the above-mentioned selective in-mold bonding 4D injection molding device, and the steps are as follows:

[0063] Step 1: Based on the shape requirements of product 4, pre-design the structure of product 4 and insert 3-1, and select insert 3-1 as part of product 4 to be glued to the exact position of the whole product 4. The glueable position is marked as 1' to 3'. Figure 2At the same time, the shape and size of insert 3-1 are clearly defined, and insert 3-1 is prepared in advance;

[0064] Step 2: Install mold 2 onto the mold clamping system of injection molding machine 1 for mold adjustment; after mold adjustment, set the control system program of selective in-mold bonding system 3. The program includes using a robotic arm and gripper to grab the insert 3-1 and place it into the cavity 2-5 of the opened mold 2 for fixed position.

[0065] Step 3: Set the injection molding process conditions and carry out injection molding. Inject the molten material from the injection molding machine 1 into the cavity 2-5 of the mold 2. The material is then bonded to the pre-embedded inserts 3-1 in the mold.

[0066] Step 4: The injection molding machine 1 drives the mold to open and eject the product, completing one injection molding cycle.

[0067] This embodiment of the experiment used an injection molding machine (Haitian ZE1200) and a mold with a cross-shaped cavity structure. Figure 1 The cross-shaped cavity has a total size of 70mm × 70mm, with each blade being 10mm wide and the cavity thickness 1mm. This embodiment uses polypropylene (PP 579S, manufactured by Sabic) as the raw material. Insert 3-1 is made from the same material as the injection-molded material, prepared by hot pressing. A TY-7006 hot press manufactured by Jiangsu Tianyuan Experimental Equipment Co., Ltd. was used. The polypropylene raw material granules were compacted at 180℃ and 6MPa for 5 minutes, producing a polypropylene sheet with a size of 100mm × 60mm × 0.4mm. The prepared sheet was then cut into the required size of 10mm × 10mm × 0.4mm for in-mold bonding of insert 3-1.

[0068] Because the adhesive of insert 3-1 pre-occupies the thickness space, local temperature T and pressure p gradients are generated during injection molding. Numerical simulation technology is used ( Figure 3 The mechanism of selective in-mold bonding 4D injection molding was studied, with the insert bonding location selected as 1', i.e., the blade root. The process conditions were: melt temperature 250℃, holding pressure 24MPa, holding time 4s, and cooling time 13s. Simulations showed a maximum melt front temperature difference of 7℃ and a pressure difference of 22MPa at the end of injection. The insert bonding area accelerated heat dissipation, reduced local volume shrinkage Δv, and ultimately caused the blade portion of the product to deform towards the high-temperature region. The simulated in-mold shrinkage (Δv) was... t1 The displacement change caused by ) is small, while the post-modulus shrinkage (Δv) t2 The displacement change caused by this is relatively large, with a total Z-direction warping deformation displacement of 3.355 mm.

[0069] In this embodiment, three locations were selected for selective in-mold bonding 4D injection molding experiments: 1', 2', and 3'. Figure 2 Subsequently, experiments were conducted on three bonding sites under the same injection molding process conditions. The process conditions were: melt temperature 220℃, holding pressure 18MPa, holding time 4s, and cooling time 13s. Three products with different warpage displacements were prepared. Figure 4 Using an HG-C100 laser displacement sensor with a measurement platform, the deformation of the workpiece was detected in the Z-direction displacement relative to pre-marked reference and measurement points on the workpiece. The warpage displacements of the workpieces corresponding to selective in-mold bonding inserts 1', 2', and 3' were measured at the vertical distance (Z-direction) at the root and edge of the blade, respectively, and were 3.62 mm, 2.4 mm, and 0.44 mm. It is evident that under the same process conditions and using the same inserts, the warpage displacements obtained at different locations differ significantly. Compared to bonding at the middle (2') and edge (3') of the blade, bonding near the gate (1') generated a larger temperature field ΔT and pressure difference Δp, thus leading to more pronounced deformation.

[0070] To ensure the bonding strength of the inserts and the integrity of the finished product, numerical simulation of the interface temperature T distribution revealed that the bonding locations near and far from the gate do not cause changes in the interface temperature during the melt injection stage. The overall interface temperature reached the melting temperature of the inserts. Therefore, it can be determined that the inserts can bond with the melt injected into the cavity at high temperatures and ultimately cool and solidify together. To further confirm this, [further details are needed]. Figure 4 Nanoindentation experiments were conducted on local samples of the three prepared products. The specific nanoindentation experiment process is as follows: The local interface strength of the cross-shaped part was evaluated using a nanoindenter (G200, KLA Corporation); to meet the size requirements of the equipment, the bonded part of the product was cut into 14×10×1mm pieces. 3The surface area of ​​the embedded parts was tested under load-displacement mode, with a maximum displacement of 2.5 μm, a holding time of 20 s, and a loading speed of 10 nm / s. Significant deviations in load were observed at different test points at different locations on the bonded 1' sample, indicating that the bonded location 1' was more significantly affected by changes in temperature T and pressure p, as well as the generation of residual stress. In contrast, the load variation deviations of the bonded 2' and 3' samples were smaller, indicating more uniform bond strength. The bonded 2' sample had the highest elastic modulus and hardness, while the bonded 1' sample showed significant deviations, and the bonded 3' sample showed moderate and stable values. The modulus distribution of the bonded 3' sample was the most uniform, slightly lower than that of the bonded 2' sample, but higher than that of the bonded 1' sample in several different locations, indicating that despite the distance of the bonded 3' location from the gate, sufficient interfacial bonding was still achieved through effective melting and re-curing. The moduli at the interfacial bonding locations of all three samples were above 1 GPa, confirming that this embodiment can achieve sufficient interfacial bonding, ensuring the integrity of the product structure.

[0071] Example 2

[0072] The selective in-mold bonding 4D injection molding and product deformation control method in this embodiment is based on Embodiment 1. It also adopts a combination of experimental design and response surface methodology. The interposer bonding position and injection molding process parameters are used as independent variables, and the warpage displacement of the product is used as the response variable. The experimental design is carried out using response surface methodology. Selective in-mold bonding 4D injection molding experiments are carried out sequentially according to the designed experiments, and the warpage displacement of each product is detected. The data of independent and response variables are analyzed and processed by response surface methodology, and the parameters of the response surface model equation are regressed to obtain the equation. The warpage displacement of the product is determined manually according to the desired product shape and size, and then used as the target value. Based on the expectation function and response surface model, the combination of independent variables with high expectation value is calculated in reverse. The interposer shape and size, bonding position, and injection molding process parameters are set according to the inversely calculated combination of independent variables, and injection molding is carried out to obtain a product with the set target warpage displacement.

[0073] This embodiment employs a Box-Behnken design within the response surface methodology framework. The insert bonding location is defined as variable I. Three bonding locations (1', 2', and 3') are defined sequentially from the root to the edge of a blade along the cross-shaped product. Figure 2 Each bonding location was modeled separately. The four injection molding process parameters—melt temperature, holding pressure, holding time, and cooling time—were treated as variables II, III, IV, and V, respectively. Each variable was assigned three levels, resulting in a total of 3*29=87 experimental runs. Figure 5 The response variable is the warpage displacement of the product, defined as the difference in the Z-direction between the measured values ​​at the blade edge and the blade root reference point. Figure 3 This was also used as a control target. 87 selective in-mold bonding 4D injection molding experiments were conducted sequentially, and the corresponding data are as follows: Figure 5 As shown.

[0074] The quadratic model exhibiting the best predictive power was selected to fit the collected data. All terms were retained in the final equation, resulting in three model equations ( Figure 6 The accuracy of the model is evaluated. Figure 7 The indicators include prediction bias (Std.Dev.), coefficient of variation (CV), and coefficient of determination R. 2 Corrected determination coefficient R 2 Predicting R 2 All of them showed very high prediction accuracy.

[0075] Based on the obtained model, customized warp deformation displacement products can be injection molded, achieving programmable control of the product shape. This embodiment specifies five warp deformation displacement targets: 3.6, 3.4, 3.2, 2.2, 1.8, and 0.5 mm, respectively. Based on the target values ​​and the model, combined with the expectation function, the values ​​of the independent variable parameters of the target values ​​can be derived.

[0076] The expected value of the expected function (d) i The formula for the calculation equation is as follows:

[0077] When Y i,min ≤Y i ≤T i ,

[0078] When T i <Y i ≤Y i,max , Where d i Y is the expected value of the i-th response (0≤di≤1). i T is the predicted value of the i-th response. i Y is the target value of the i-th response. i,min Y is the minimum acceptable value of the i-th response. i,max It is the maximum acceptable value for the i-th reaction. i The weights of the expectation function (w is calculated for a single expectation value). i =1).

[0079] Figure 8To deduce the values ​​of the independent variable parameters corresponding to the five target values, experiments were conducted based on the recommended independent variable parameter values. Three corresponding products were prepared, and the actual warpage displacement of the products was measured. The obtained experimental measured values ​​were 3.59, 3.18, 2.29, 1.73, and 0.53 mm, respectively. There was a strong consistency between the measured values ​​and the target values. The correlation coefficient R between the five experimental values ​​and the target values ​​was calculated. 2 The accuracy rate was 99.36%, indicating high model accuracy and confirming the model's robustness and applicability.

[0080] Example 3

[0081] This embodiment uses a hand-shaped cavity, with inserts glued to different positions of the four fingers to fix the glued positions. The programmable control of the deformation displacement target value is achieved by adjusting the injection molding process parameters. This embodiment uses the same materials and injection molding machine as embodiments 1 and 2, only changing the mold cavity structure.

[0082] Selective in-mold bonding 4D injection molding was performed on a hand-shaped product with four bonding positions. The four bonding positions are used together, with bonding points 1', 2', 3', and 4' located at the four positions of the four "fingers" respectively. Figure 9 Numerical simulations were performed on the injection molding process of hand-shaped products. The warping deformation was greatest at the 1' position near the base of the finger. With the bonding position unchanged, an experimental design was used, with melt temperature, holding pressure, holding time, and cooling time as independent variables, and the maximum displacement of each finger (i.e., the Z-direction displacement from the finger base to the edge) as the response variable. A Box-Behnken design using response surface methodology was employed, resulting in 4*29=116 sets of experiments. Figure 10 The results show that the displacement range at adhesive position 1' is the largest (3.027 to 3.768 mm), while the displacement range at adhesive position 4' is the smallest (-0.421 to -0.541 mm). Based on the independent variable and the displacement of adhesive position 1', a response surface model for adhesive position 1' is obtained. Figure 11 The model's accuracy is highly evaluated, and its predicted R0 is high. 2 The accuracy was 98.75%. Further application was made to programmable shape control of the product, deriving parameter values ​​through reverse engineering of the expected function. Verification experiments were conducted under the reverse-engineered programmable process conditions, with target displacements of 3.1, 3.4, and 3.7 mm. Figure 12 The results showed that the experimentally measured values ​​were 3.11, 3.37, and 3.67 mm, which were close to the target values, indicating that the accuracy of the programmable shape control was very high.

[0083] Example 4

[0084] Torsional deformation can be achieved by changing the geometry of the inserts. This embodiment experimentally studies the effect of the insert geometry on deformation. Based on Example 1, polypropylene sheets prepared by hot pressing were cut to obtain inserts with six shapes: " / ", "\", "<", ">", "s", and "x", which were used for selective bonding on the blades of cross-shaped products.

[0085] Six types of cross-shaped products were prepared using selective in-mold bonding 4D injection molding and product deformation control methods. Figure 13 A) The shape and position of the bonded inserts are marked with dashed lines in the figure. Three measurement points (1, 2, 3) and a reference point ( ) are measured using an HG-C100 laser displacement sensor. Figure 13 The Z-direction distance between B) and the blade edges of the six samples exhibited bending and torsional deformation in different directions. Figure 13 C). The maximum displacement reached over 1.8mm. The different blade deformations demonstrate that using inserts of different shapes can achieve more diverse 4D injection molding shapes.

Claims

1. A selective in-mold bonding 4D injection molding apparatus, comprising an injection molding machine, a mold, and a selective in-mold bonding system, characterized in that: The selective in-mold bonding system consists of a robotic arm, a gripper, inserts, and a control system. The inserts are part of the injection-molded product and are bonded to the material injected into the cavity within the cavity. The mold includes a mold frame, a core, a cavity plate, and a support plate. The cores form the cavity structure and are fixed by the cavity plate. The cavity has space and set positions for placing the inserts. The cavity plate is fixed to the support plate by bolts, and the support plate is fixed to the mold frame by bolts.

2. The selective in-mold bonding 4D injection molding apparatus according to claim 1, characterized in that: The core has an insert positioning structure, which consists of tiny pits.

3. The selective in-mold bonding 4D injection molding apparatus according to claim 1, characterized in that: The back of the insert is covered with double-sided adhesive for positioning the insert within the cavity.

4. The selective in-mold bonding 4D injection molding apparatus according to claim 1, characterized in that: The insert contains the same material as the injection-molded material.

5. The selective in-mold bonding 4D injection molding apparatus according to claim 1, characterized in that: The block contains the same material as the injection-molded material, and also contains heterogeneous materials, including fibers, nanofillers, magnetic fillers and inorganic fillers.

6. The selective in-mold bonding 4D injection molding apparatus according to claim 1, characterized in that: The selective in-mold bonding 4D injection molding apparatus also includes a preheating system for preheating the mold cavity and the surface of the inserts.

7. A selective in-mold bonding 4D injection molding and product deformation control method using the selective in-mold bonding 4D injection molding apparatus as described in any one of claims 1-6, characterized in that: The method includes the following steps: Step 1: Based on the shape requirements of the product, pre-design the product and insert structure, select the insert as part of the product and attach it to the exact position of the whole product; at the same time, determine the shape and size of the insert and prepare the insert in advance; Step 2: Install the mold onto the mold clamping system of the injection molding machine for mold adjustment; after the mold adjustment is completed, set the control system program of the selective in-mold bonding system. The program includes using a robotic arm and gripper to pick up the insert and place it into the cavity of the opened mold at a set position for fixation. Step 3: Set the injection molding process conditions and carry out injection molding. Inject the molten material from the injection molding machine into the mold cavity, and the material adheres to the pre-embedded inserts in the mold. Step 4: The injection molding machine opens the mold and ejects the product, completing one injection molding cycle.

8. A method for selective in-mold bonding 4D injection molding and product deformation control as described in claim 7, characterized in that: The selective in-mold bonding 4D injection molding method also employs response surface methodology, using the shape and size of the insert, the bonding position, and the injection molding process parameters as independent variables, and the warpage displacement of the product as the response variable. The experimental design is carried out using response surface methodology; the selective in-mold bonding 4D injection molding experiments are carried out sequentially according to the designed experiments, and the warpage displacement of each product is detected. The data of independent and response variables are analyzed and processed using the response surface methodology. The parameters of the regression response surface model equation are obtained to obtain the equation. The warpage displacement of the product is determined artificially according to the desired product shape and size, and then used as the target value. Based on the expectation function and the response surface model, the combination of independent variables with high expectation values ​​is calculated in reverse. The shape and size of the insert, the bonding position, and the injection molding process parameters are set according to the inversely calculated combination of independent variables. Injection molding is then performed to obtain a product with the set target warpage displacement.

9. The selective in-mold bonding 4D injection molding and product deformation control method according to claim 8, characterized in that: The accuracy of the response surface model and equations is measured by the residuals and the coefficient of determination R. 2 The smaller the residual, the closer the coefficient of determination is to 1, and the higher the accuracy.

10. The selective in-mold bonding 4D injection molding and product deformation control method according to claim 8, characterized in that: The response surface methodology is replaced by experimental design and machine learning-based artificial neural network models.

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