Synergistic manufacturing method and system of micro-stiffness flat wire spring, product and medium

Abstract

The invention discloses a collaborative manufacturing method and system of a micro-stiffness flat wire spring, a product and a medium. According to the method, a complete closed-loop manufacturing system is constructed through the four steps of material gradient pretreatment, precise winding forming, composite post-treatment and process feedback optimization which are coordinated in sequence. Specifically, the method comprises the following steps: firstly, carrying out finish rolling and pre-aging on a ribbon-like filament raw material to optimize the structure uniformity of the ribbon-like filament raw material; dynamic monitoring and feedback adjustment of the tension of the flat filament are realized based on a preset tension model during winding; performing staged heat treatment and selective edge strengthening on the spring blank; finally, pre-process parameters are adjusted in a self-adaptive mode according to finished product performance test data. According to the method, the problems of performance discretization, short fatigue life, lack of closed-loop optimization and the like caused by a traditional sectional process are effectively solved, and the rigidity consistency, the fatigue life and the dimensional precision of the micro-rigidity flat wire spring are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of precision elastic element manufacturing technology, specifically to a method, system, product, and medium for the collaborative manufacturing of micro-stiffness flat wire springs. Background Technology

[0002] As an elastic element requiring high-precision stiffness control, the low-stiffness flat wire spring is widely used in high-end fields such as precision instruments, microelectronic devices, and aerospace components. Its performance directly determines the operational stability, response accuracy, and service life of the end device. With the rapid development of these fields towards miniaturization and high precision, more stringent requirements have been placed on the core performance indicators of low-stiffness flat wire springs, such as stiffness consistency, fatigue life, and dimensional accuracy. Traditional manufacturing processes are no longer sufficient to meet current application demands.

[0003] In existing technologies, the manufacturing of low-stiffness flat wire springs often employs a segmented process: simple raw material processing – conventional winding – single post-processing. The lack of coordinated design and dynamic optimization in each stage leads to numerous performance defects in the finished springs. In the material pretreatment stage, existing processes mostly use conventional rolling and aging treatments, making it difficult to precisely control the thickness tolerance of the flat wire and resulting in insufficient uniformity and stability of the microstructure. This easily leads to stress concentration issues in the subsequently wound spring blank, affecting the consistency of the finished product's stiffness. In the winding stage, traditional winding equipment often uses fixed tension parameters for feeding, failing to consider the subtle differences in the material properties of the flat wire after pretreatment, and lacking real-time tension monitoring and dynamic feedback adjustment mechanisms. This results in excessive tension fluctuations during winding, making it difficult to guarantee the coil diameter accuracy and pitch consistency of the spring blank, further exacerbating the performance dispersion of the finished springs.

[0004] In the post-processing stage, existing technologies mostly employ single-temperature heat treatment processes for stress relief, which struggles to simultaneously release both macroscopic and microscopic internal stresses. This can easily lead to stiffness decay and deformation issues in springs during subsequent use. Furthermore, the treatment of spring wire edges often involves only general grinding or lacks targeted reinforcement, failing to effectively remove microscopic defects and easily compromising the dimensional accuracy of the wires. This makes the edges prone to fatigue cracks during cyclic loading, reducing fatigue life. In addition, existing manufacturing processes lack a robust process feedback optimization mechanism, relying solely on finished product sampling to determine product quality. They fail to establish a correlation between performance test data and process parameters at each manufacturing stage, making it impossible to adaptively adjust upstream process parameters based on finished product performance deviations. This results in poor performance stability between production batches and a high scrap rate.

[0005] In summary, the current manufacturing process of low-stiffness flat wire springs suffers from technical defects such as poor coordination among various stages, insufficient parameter control precision, weak post-processing targeting, and lack of closed-loop feedback optimization. As a result, the core performance of the finished springs is difficult to meet the application requirements of high-end fields. Summary of the Invention

[0006] The purpose of this invention is to provide a collaborative manufacturing method, system, product, and medium for low-stiffness flat wire springs, in order to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for the collaborative manufacturing of a low-stiffness flat wire spring, comprising the following sequential steps: S1 Material Gradient Pretreatment Step: The flat wire raw material used to make micro-stiffness flat wire springs is pretreated to improve its microstructure uniformity and stability; the pretreatment includes fine rolling of the flat wire to improve its thickness uniformity, and pre-aging treatment of the finely rolled flat wire to optimize its microstructure. S2 Precision Winding Forming Step: The flat wire, after being processed by the material gradient pretreatment step, is wound into a spring blank using a winding equipment; during the winding process, the actual feed tension of the flat wire is dynamically monitored and adjusted based on a preset tension model so that the winding process parameters are kept within a predetermined range. S3 post-processing steps: The wound spring blank is subjected to stress relaxation and shaping treatment and edge strengthening treatment in sequence; the stress relaxation and shaping treatment includes at least two heat treatments under different process conditions, and the edge strengthening treatment is performed on specific edge areas of the spring blank; S4 Process Feedback Optimization Step: Based on the performance test data of the finished spring, at least one process parameter in the material gradient pretreatment step, the precision winding forming step, and the composite post-processing step is adaptively adjusted.

[0008] Preferably, the material gradient pretreatment step specifically includes: The purchased precision alloy flat wires are subjected to a single precision rolling process to compress their thickness tolerance range. The precision-rolled flat wire is placed in a preset low-temperature environment for aging treatment to form a diffusely distributed reinforcing phase inside the material and release some of the internal stress.

[0009] Preferably, the dynamic monitoring and feedback adjustment in the precision winding forming step specifically includes: Real-time acquisition of feed tension data for flat wire during the winding process; The actual tension data collected is compared in real time with the ideal tension model established based on the properties of the pre-processed flat wire material; When the actual tension data deviates from the preset tolerance range of the ideal tension model, the spindle speed and / or flat wire feeding speed of the winding equipment are dynamically adjusted.

[0010] Preferably, the stress relaxation and shaping treatment in the post-composite processing step includes: First heat treatment stage: The spring blank is subjected to the first heat treatment at a first temperature in a protective atmosphere to eliminate the main macroscopic internal stress introduced by winding; Second heat treatment stage: The spring blank that has undergone the first heat treatment is subjected to a long-term heat treatment at a second temperature lower than the first temperature to homogenize the micro-stress and promote the stability of the material structure.

[0011] Preferably, the edge strengthening process in the post-composite processing step is a selective process, which focuses on the side edges of the flat wire of the spring blank. The edge strengthening treatment employs chemical polishing or plasma treatment to remove microscopic defects on the side edges and form a surface strengthening layer.

[0012] Preferably, the process feedback optimization step specifically includes: Samples were extracted from the finished springs obtained after the composite post-processing step, and force-displacement curve tests and fatigue characteristic tests were conducted to obtain data related to the stiffness and fatigue life of the samples. The acquired test data is compared and analyzed with the preset design target value to determine the performance deviation; Based on the performance deviation and in conjunction with historical process data, determine the process parameters that need to be adjusted in the material gradient pretreatment step, the precision winding forming step, or the composite post-treatment step. Based on the determined results, the corresponding process parameters in subsequent production batches are fine-tuned.

[0013] This application also proposes a collaborative manufacturing system for low-stiffness flat wire springs, used to implement the above-described collaborative manufacturing method, the system comprising: The pretreatment unit is configured to sequentially perform fine rolling and pre-aging treatments on the flat wire raw materials. The winding unit includes a winding machine, a tension sensing module, and a control module; the tension sensing module is used to monitor the tension of the flat wire during the winding process in real time and output tension data; the control module is configured to receive the tension data and output dynamic adjustment commands for the winding parameters according to a preset tension model. The post-processing unit is configured to sequentially perform multi-stage heat treatment and selective edge strengthening treatment on the spring blank output from the winding unit; The detection and feedback unit is configured to perform sampling performance tests on the finished springs output by the post-processing unit, analyze the test data, output test analysis results, and feed the test analysis results back to the control module or the central process management module for optimizing the process parameters of each unit.

[0014] Preferably, the control module of the winding unit stores the ideal tension model and is configured with a feedback control algorithm; The feedback control algorithm is used to calculate and output adjustment commands for the rotational speed and / or wire feeding speed of the winding machine spindle based on the deviation between the tension data collected in real time by the tension sensing module and the ideal tension model.

[0015] This application also proposes a low-stiffness flat wire spring, which is manufactured by the above-described collaborative manufacturing method.

[0016] This application also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a process feedback optimization step.

[0017] Compared with the prior art, the beneficial effects of the present invention are: by sequentially executing the material gradient pretreatment step to optimize the microstructure of the flat wire, the precision winding forming step to dynamically adjust the tension to ensure parameter stability, the composite post-treatment step to strengthen the edges and relax the stress, and the process feedback optimization step to adaptively adjust the process parameters, the present invention effectively solves the performance dispersion problem caused by the fragmented process in the prior art, and has the advantages of improving the microstructure uniformity, dimensional accuracy control capability, stiffness consistency and fatigue life of the micro-stiffness flat wire spring. Attached Figure Description

[0018] Figure 1 This is a flowchart of the collaborative manufacturing method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the collaborative manufacturing system structure according to an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1-2 A collaborative manufacturing method for low-stiffness flat wire springs is proposed. This method includes the following sequential steps: material gradient pretreatment, precision winding forming, composite post-processing, and process feedback optimization. Through the synergistic effect of these steps, it aims to address the shortcomings of existing manufacturing processes.

[0021] For ease of understanding, the following explains some key terms in this embodiment: Low-stiffness flat wire springs are springs made of flat cross-section metal wires. They are characterized by high-precision stiffness control and can achieve accurate displacement response under small force values. They are often used in precision machinery and electronic equipment with strict requirements for elastic performance.

[0022] Collaborative manufacturing is a manufacturing model that integrates multiple independent stages in the product manufacturing process into an organic whole through information sharing, parameter linkage, and optimization feedback mechanisms, aiming to improve efficiency and control quality throughout the entire process.

[0023] Gradient pretreatment of materials refers to a series of physical or chemical treatments performed on flat yarn raw materials before they enter the main forming process, in order to improve the internal structure, mechanical properties or surface condition of the materials, making them more suitable for subsequent processing and providing a basic guarantee for the performance of the final product.

[0024] Precision rolling refers to the precise control of the thickness or width of flat wire materials through multi-pass or high-precision rolling equipment, in order to reduce tolerances, improve surface quality and internal structure uniformity.

[0025] Pre-aging treatment refers to heat-treating materials under specific temperature and time conditions before forming them, in order to promote the precipitation of strengthening phases, grain refinement, or release of internal stress, thereby optimizing the microstructure and mechanical properties of the materials.

[0026] Precision winding refers to the process of using high-precision winding equipment to precisely wind flat wire materials into spring blanks with specific geometric shapes and dimensions under strict control of process parameters.

[0027] The preset tension model refers to a mathematical model or parameter curve established based on the physical properties, geometric dimensions, and structural requirements of the flat wire material, through theoretical calculations or empirical data, to guide the change of flat wire feed tension during the winding process.

[0028] Dynamic monitoring and feedback adjustment refers to the process of collecting key process parameters in real time during manufacturing, comparing them with preset target values, and automatically or semi-automatically adjusting relevant equipment or process parameters based on deviations to maintain process stability and product quality.

[0029] Composite post-treatment refers to the combination of various post-processing techniques with different properties applied to the spring blank after it has been formed, in order to further eliminate internal stress, stabilize dimensions, and enhance surface or edge properties, thereby comprehensively improving the overall performance of the spring.

[0030] Stress relaxation and shaping treatment refers to the process of gradually releasing residual stress inside the spring blank through heat treatment or other physical methods at a certain temperature and time, while stabilizing its geometry and dimensions to prevent deformation or performance degradation during use.

[0031] Edge reinforcement treatment refers to the localized strengthening of specific edge areas of spring flat wires using physical or chemical methods to improve the hardness, wear resistance, or fatigue resistance of that area, thereby extending the service life of the spring.

[0032] Process feedback optimization refers to using product performance test data as input, analyzing and evaluating it to identify key process parameters that affect product performance, and then adjusting and improving relevant process parameters in the manufacturing process to achieve continuous improvement in product quality.

[0033] Adaptive adjustment refers to the ability of a system or process parameter to automatically adjust and optimize itself based on changes in the external environment or internal feedback information in order to achieve a preset goal or maintain a stable operating state.

[0034] The collaborative manufacturing method of this application includes the following sequential steps: S1 Material Gradient Pretreatment Steps: Pretreatment is performed on the flat wire raw materials used to manufacture micro-stiffness flat wire springs to improve their microstructure uniformity and stability. Pretreatment includes precision rolling of the flat wire to improve its thickness uniformity, and pre-aging treatment of the precision-rolled flat wire to optimize its microstructure. Precision rolling can be performed on a conventional rolling mill, where the thickness of the flat wire is initially controlled by adjusting the roll gap and rolling speed. Pre-aging treatment can be carried out in a conventional heating furnace, where the precision-rolled flat wire is held at a constant temperature for a period of time to promote changes in the internal microstructure of the material.

[0035] S2 Precision Winding Forming Steps: The flat wire, after the material gradient pretreatment step, is wound into a spring blank using a winding machine. During the winding process, the actual feed tension of the flat wire is dynamically monitored and adjusted based on a preset tension model to keep the winding process parameters within a predetermined range. The winding of the flat wire can be completed by the winding machine, which uses a robotic arm or CNC winding machine to wind the flat wire onto a mandrel to form the spring blank. During the winding process, the feed tension of the flat wire can be monitored using a simple tension sensor, and the operator manually adjusts the wire feed speed or mandrel speed of the winding machine based on experience to try to maintain the tension within a certain range. The preset tension model can be a fixed tension value or a simple tension range.

[0036] S3 Post-Processing Steps: The wound spring blank undergoes stress relaxation and shaping treatment followed by edge strengthening treatment. Stress relaxation and shaping treatment includes at least two heat treatments under different process conditions, while edge strengthening treatment targets specific edge areas of the spring blank. For example, stress relaxation and shaping treatment may involve two heat treatments in a single furnace, with the first at a higher temperature and the second at a lower temperature. Edge strengthening treatment may involve simple mechanical polishing or sandblasting of all edge areas of the spring blank to remove surface burrs.

[0037] S4 Process Feedback Optimization Step: Based on the performance test data of the finished springs, adaptive adjustments are made to at least one process parameter in the material gradient pretreatment step, precision winding and forming step, and composite post-processing step. The performance test data of the finished springs can be used for process feedback optimization. Data such as stiffness and dimensions are obtained by sampling and testing the finished springs. This data can be compared with the design targets. If deviations exist, technicians will judge based on experience and manually adjust a certain process parameter in the material pretreatment, winding and forming, or composite post-processing step to improve the performance of subsequent batches of products.

[0038] The collaborative manufacturing method of this application improves the uniformity and stability of the material from the source by performing precision rolling and pre-aging treatment on the flat wire raw material. During the winding process, dynamic monitoring and feedback adjustment of the flat wire feed tension are achieved to ensure the forming accuracy of the spring blank. The spring blank undergoes multi-stage stress relaxation shaping and targeted edge strengthening, comprehensively improving the mechanical properties and fatigue life of the spring. A process feedback optimization mechanism based on finished product performance data is established to achieve adaptive adjustment of manufacturing parameters. This effectively solves the problems of poor coordination among various stages in the manufacturing of micro-stiffness flat wire springs, insufficient parameter control precision, weak post-processing targeting, and lack of closed-loop feedback optimization. It effectively improves the stiffness consistency, fatigue life, and dimensional accuracy of micro-stiffness flat wire springs, enabling them to meet the stringent requirements of high-precision elastic components in high-end fields such as precision instruments and microelectronic devices.

[0039] In some of the solutions mentioned above in this application, a material gradient pretreatment step is proposed to improve the uniformity and stability of the microstructure of flat wire raw materials. Conventional pretreatment methods are difficult to accurately control the thickness tolerance of flat wires, and the microstructure uniformity and stability are insufficient, which can easily lead to subsequent stress concentration risks.

[0040] In this regard, this application further proposes a material gradient pretreatment step, which specifically includes: performing a single precision rolling process on the purchased precision alloy flat wire to compress its thickness tolerance range, and placing the precision rolled flat wire in a preset low temperature environment for aging treatment to form a dispersed strengthening phase inside the material and release some internal stress.

[0041] This finishing rolling process aims to achieve extremely precise control over the thickness of the flat wire. This can be achieved by using a precision rolling mill equipped with high-precision rolls and a real-time thickness detection system. A laser thickness gauge is used to monitor the wire thickness online, and the roll gap is precisely adjusted via a servo motor or hydraulic system to ensure the required thickness accuracy is achieved in a single rolling pass. Alternatively, a multi-roll precision rolling mill can be used. By optimizing the rolling pass design and rolling force control, precise control of the flat wire thickness can be achieved while ensuring uniform plastic deformation of the material, thereby improving the thickness uniformity of the flat wire.

[0042] This low-temperature aging treatment refers to heat treatment of the precision-rolled flat wire in a preset low-temperature environment below the conventional aging temperature. Its purpose is to promote the uniform and dispersed distribution of precipitated phases within the material and effectively release residual internal stress introduced by precision rolling, without causing significant macroscopic deformation. This can be achieved by placing the flat wire in a precisely temperature-controlled low-temperature furnace, for example, within a temperature range of 0℃ to 150℃, and holding it for several hours to tens of hours to induce the alloying elements to form fine, uniformly distributed strengthening phases, thereby improving the material's strength and hardness. Alternatively, a segmented low-temperature aging process can be used, first performing pre-aging at a lower temperature, such as 50℃, and then performing main aging at a slightly higher temperature, such as 120℃, to more precisely control the precipitation kinetics of the strengthening phases and the release process of internal stress, ensuring the stability and uniformity of the microstructure.

[0043] By employing the aforementioned technical solution, a single-pass precision rolling process on the flat wire raw material can compress the thickness tolerance range of the flat wire, ensuring a high degree of thickness consistency along its entire length. This effectively avoids the potential for stress concentration caused by uneven thickness. Simultaneously, placing the precision-rolled flat wire in a pre-designed low-temperature environment for aging treatment promotes the uniform and dispersed distribution of the reinforcing phases within the material and effectively releases the internal stress generated during the precision rolling process, optimizing the material's microstructure. This refined material pretreatment improves the uniformity and stability of the flat wire's structure from the source, providing high-quality raw materials for subsequent precision winding steps. This ensures uniform stress distribution on the spring blank during winding, reduces performance dispersion caused by material defects, and ultimately results in a finished low-stiffness flat wire spring with superior stiffness consistency and a longer fatigue life.

[0044] In some of the solutions mentioned above in this application, dynamic monitoring and feedback adjustment are proposed to maintain the stability of winding process parameters. However, due to the lack of specific real-time data acquisition mechanisms, model comparison methods based on material properties, and dynamic parameter adjustment methods, the fluctuation of flat wire feed tension may not be effectively controlled, thereby affecting the coil diameter accuracy and pitch consistency of the spring blank.

[0045] In response, this application further proposes dynamic monitoring and feedback adjustment in the precision winding forming process, specifically including: real-time acquisition of the feed tension data of the flat wire during the winding process, and real-time comparison of the acquired actual tension data with an ideal tension model established based on the pre-processed flat wire material properties. When the actual tension data deviates from the preset tolerance range of the ideal tension model, the spindle speed and / or flat wire feed speed of the winding equipment are dynamically adjusted.

[0046] Real-time acquisition of the feed tension data of the flat wire during winding aims to obtain the instantaneous tension value experienced by the flat wire during winding, which is the foundation for achieving precise tension control. This data acquisition can be achieved in various ways. High-precision tension sensors, such as piezoelectric, strain gauge, or capacitive tension sensors, can be installed on the feed path of the flat wire, and tension data can be acquired in real time through the analog or digital signals output by the sensors. Alternatively, non-contact measurement methods can be used, such as those based on laser displacement sensors or visual recognition systems, to indirectly calculate and acquire tension data by monitoring the minute deformations or vibration frequencies of the flat wire under specific tension.

[0047] The actual tension data collected is compared in real time with an ideal tension model established based on the properties of the pre-treated flat wire material. The purpose is to establish an optimal winding tension benchmark for the characteristics of the pre-treated flat wire material and to promptly detect deviations between the actual tension and this benchmark. The ideal tension model can be a mathematical function established using parameters such as the width, thickness, elastic modulus, yield strength, winding speed, and winding radius of the flat wire, combined with pre-treated material test data, through finite element analysis or empirical formulas. Real-time comparison involves the control system numerically comparing sensor data with the model's calculation results. Alternatively, the ideal tension model can also be a model based on machine learning or artificial intelligence algorithms. This model, trained with a large amount of historical production data, can predict the optimal feed tension of the flat wire under specific winding conditions. Real-time comparison then calculates the deviation between the ideal value output by the model and the actual collected value.

[0048] When the actual tension data deviates from the preset tolerance range of the ideal tension model, the mandrel speed and / or flat wire feed speed of the winding equipment are dynamically adjusted. This aims to correct the tension deviation by adjusting key winding parameters, ensuring that the flat wire remains within the desired tension range during winding, thereby guaranteeing the consistency of spring forming. The control system can calculate the adjustment amount for the mandrel speed and / or flat wire feed speed based on the magnitude and direction of the tension deviation using a PID proportional-integral-derivative controller or other advanced control algorithms, and send commands to the servo motor or frequency converter to achieve precise speed adjustment. Alternatively, a rule-based expert system or fuzzy logic controller can be used, pre-setting a series of rules corresponding to tension deviations and adjustment strategies. When a tension deviation from the preset tolerance is detected, the system selects an appropriate adjustment scheme based on the rule base: if the tension is too high, the mandrel speed is reduced and / or the flat wire feed speed is increased; if the tension is too low, the opposite is true.

[0049] By employing the aforementioned technical solution, real-time acquisition of flat wire feed tension data enables timely and accurate acquisition of the tension state during the winding process, avoiding the control blind spots caused by data lag in traditional methods. Simultaneously, the acquired actual tension data is compared in real-time with an ideal tension model established based on the pre-treated flat wire material properties. This fully considers the individual differences in flat wire materials after pre-treatment, making the ideal tension value more closely match actual working conditions, thus enabling more accurate identification of tension deviations. When the actual tension data deviates from the preset tolerance range, the system can dynamically adjust the spindle speed and / or flat wire feed speed of the winding equipment, achieving rapid and precise correction of tension fluctuations. These measures work synergistically to form a highly efficient closed-loop feedback control system, effectively suppressing fluctuations in the flat wire feed tension during winding, improving the coil diameter accuracy and pitch consistency of the spring blank, thereby laying a solid foundation for obtaining high-performance, low-stiffness flat wire springs.

[0050] In some embodiments of this application, a stress relaxation and shaping process in the composite post-processing step is proposed to eliminate the stress in the spring blank. If only a single heat treatment process is used, it may not be able to effectively take into account the simultaneous release of macroscopic internal stress and microscopic stress, resulting in stiffness reduction and deformation problems in the spring during subsequent use, affecting the long-term stability and performance consistency of the finished spring.

[0051] In this regard, this application further proposes that the stress relaxation and shaping process in the composite post-processing steps includes: First heat treatment stage: The spring blank is subjected to the first heat treatment at a first temperature in a protective atmosphere to eliminate the main macroscopic internal stress introduced by winding; Second heat treatment stage: The spring blank that has undergone the first heat treatment is subjected to a long-term heat treatment at a second temperature lower than the first temperature to homogenize the micro-stress and promote the stability of the material structure.

[0052] The protective atmosphere refers to a specific gaseous environment introduced during heat treatment to prevent oxidation, decarburization, or other harmful chemical reactions on the surface of the spring blank. Its function is to maintain the original chemical composition and surface state of the material, ensuring the purity of the heat treatment effect. This can be achieved, but is not limited to: introducing inert gases such as high-purity argon or nitrogen, processing in a vacuum furnace, or using a reducing atmosphere such as a mixture of hydrogen and nitrogen. The first temperature is a relatively high temperature used for the initial heat treatment. Its main function is to provide sufficient energy to give the atoms inside the spring blank a high migration ability, thereby quickly eliminating the main macroscopic internal stresses formed during winding. The selection of this temperature is usually based on the type of flat wire material and its recrystallization temperature. For commonly used stainless steel or nickel-based alloys, the first temperature can be set within or slightly below the material's solution treatment temperature range, for example, between 600°C and 900°C. The first heat treatment refers to the process of rapidly heating the spring blank to the first temperature and holding it for a certain period of time during the first heat treatment stage. This process aims to rapidly release the large, unevenly distributed macroscopic stress generated during winding through high temperature, laying the foundation for subsequent microscopic stress homogenization. The processing time is typically short, ranging from minutes to hours, to avoid excessive grain growth.

[0053] Furthermore, the second temperature is a lower temperature used for prolonged heat treatment, set below the first temperature. The main function of this temperature is to provide continuous energy without causing excessive softening or grain coarsening of the material, thereby promoting the homogenization of micro-stress and the stability of the crystal structure. The second temperature is typically selected within the stress relief temperature range or aging strengthening temperature range of the material, for example, 50°C to 150°C lower than the first temperature, or between 300°C and 600°C. Prolonged heat treatment refers to a longer isothermal treatment of the spring blank at the second temperature. This process, by extending the heat treatment time, allows sufficient time for the atoms within the material to diffuse and rearrange, thereby more thoroughly homogenizing micro-stress, eliminating residual stress gradients, and promoting the stability of the crystal structure and the repair of defects. The holding time is usually long, such as several hours to tens of hours, to ensure that the microstructure reaches its optimal stable state.

[0054] The above technical solution optimizes the traditional single heat treatment process into a staged stress relaxation and shaping treatment, effectively solving the problem of simultaneously and effectively eliminating macroscopic and microscopic stresses. The first heat treatment stage involves initial heat treatment of the spring blank at a first temperature in a protective atmosphere, which rapidly eliminates the main macroscopic internal stresses introduced during winding, preventing early deformation or failure of the spring blank due to macroscopic stress concentration during subsequent processing or use. Subsequently, the second heat treatment stage involves prolonged heat treatment of the spring blank after the first heat treatment at a second temperature lower than the first temperature, which specifically homogenizes the microscopic stresses within the material and promotes the stability of the crystal structure, thereby effectively preventing stiffness decay and long-term creep deformation caused by uneven microscopic stress during spring use. This staged, gradient heat treatment strategy, combined with the application of a protective atmosphere, not only ensures the stability and consistency of spring material properties but also improves the long-term reliability and fatigue resistance of micro-stiffness flat wire springs, enabling them to better meet the needs of high-precision, long-life elastic elements in high-end applications.

[0055] In some embodiments of this application, edge strengthening treatment in the composite post-processing step is proposed to improve spring performance. If the edge strengthening treatment is not selective but global, it will lead to the inability to effectively remove edge micro-defects, damage dimensional accuracy, increase the risk of fatigue cracks, and reduce fatigue life.

[0056] In this regard, this application further proposes that the edge strengthening treatment in the composite post-processing step is a selective treatment, which focuses on the side edges of the flat wire of the spring blank; the edge strengthening treatment adopts chemical polishing or plasma treatment to remove micro-defects on the side edges and form a surface strengthening layer.

[0057] The edge strengthening process is designed as a selective process to avoid unnecessary intervention or damage to non-critical areas of the spring blank flat wire, thereby maintaining its overall dimensional accuracy and surface integrity. This selective processing can be achieved in various ways, such as using precision jigs or masking techniques to expose only the side edge areas requiring strengthening, or employing a high-precision positioning system to allow processing tools, including plasma beams or chemical jets, to precisely act on the target side edge. The processing target is focused on the side edge of the spring blank flat wire because the side edge is prone to microscopic defects during the winding process, and this area is often the primary location for stress concentration and fatigue crack initiation when the spring is under load. Therefore, precisely limiting the processing target to the side edge can address these critical issues. Optical recognition systems or mechanical positioning devices can be used to ensure that the processing equipment can accurately identify and act on the side edge of the flat wire.

[0058] The edge strengthening treatment employs either chemical polishing or plasma treatment. Chemical polishing is a method that removes microscopic irregularities and defects from the material surface through chemical dissolution. Its advantage lies in achieving stress-free material removal and avoiding the introduction of new mechanical damage. For stainless steel flat wire, a mixed acid solution such as phosphoric acid, sulfuric acid, and nitric acid can be used for immersion treatment. For nickel-based alloys, acidic or alkaline solutions containing specific oxidants may be used. Treatment parameters such as solution formulation, temperature, and time need to be precisely controlled according to material characteristics and the desired surface roughness. Plasma treatment utilizes ionized gas to undergo physical or chemical reactions with the material surface, thereby altering surface properties. It is characterized by cleanliness, high efficiency, and strong controllability. Argon plasma can be used for physical sputtering etching to remove surface defects, or plasma containing reactive gases such as nitrogen or hydrocarbons can be used to form hard coatings such as nitrides or diamond-like carbon films on the side edges, or surface modification and strengthening can be achieved through ion implantation. The treatment process is usually carried out in a vacuum environment, and the treatment effect is controlled by adjusting parameters such as gas type, flow rate, power, and treatment time. The above-described treatment method is used to remove microscopic defects on the side edges and form a surface strengthening layer. Removing microscopic defects aims to eliminate stress concentration sources such as microcracks, burrs, oxide layers, or inhomogeneous structures that may occur during flat wire manufacturing and spring winding, thereby reducing the probability of fatigue crack initiation. Forming a surface strengthening layer aims to improve the hardness, wear resistance, corrosion resistance, or introduce compressive stress by altering the surface microstructure of the side edges or introducing new material layers, thereby enhancing the fatigue strength and service life of the spring. Chemical polishing results in a smoother surface and a more uniform passivation layer, while plasma treatment may form a modified layer with higher hardness and toughness.

[0059] By employing the aforementioned technical solutions, the edge strengthening process in the composite post-processing steps is limited to selective treatment, focusing on the side edges of the flat wire in the spring blank. This effectively avoids the damage to the overall dimensional accuracy of the spring caused by traditional full-area processing. Chemical polishing or plasma treatment can gently and precisely remove microscopic defects at the side edges in a non-mechanical contact manner, avoiding the introduction of new mechanical stress concentration points. These treatments also form a uniform and dense surface strengthening layer at the side edges, improving the hardness, wear resistance, and fatigue strength of this critical area. Given that the side edges are weak points for stress concentration and fatigue failure under cyclic loading, this targeted strengthening treatment can fundamentally improve the fatigue life and stiffness stability of the spring, thereby enhancing the overall performance of the micro-stiffness flat wire spring and meeting the demands of high-end applications for high-precision, long-life springs.

[0060] In some of the embodiments described above in this application, a process feedback optimization step is proposed to adjust process parameters based on finished product performance. However, it lacks a systematic testing mechanism and data analysis method, and cannot accurately determine the specific process parameters that need to be adjusted based on performance deviations. This results in poor performance stability between production batches and a high scrap rate.

[0061] In response, this application further proposes a process feedback optimization step that specifically includes: extracting samples from the finished springs obtained after the composite post-processing step, conducting force-displacement curve tests and fatigue characteristic tests, obtaining data related to the stiffness and fatigue life of the samples, comparing and analyzing the obtained test data with the preset design target values ​​to determine the performance deviation, and based on the performance deviation and combined with historical process data, determining the process parameters that need to be adjusted in the material gradient pre-processing step, the precision winding forming step, or the composite post-processing step, and fine-tuning the corresponding process parameters in subsequent production batches according to the determination results.

[0062] Samples are extracted from the finished springs obtained after the composite post-processing steps for force-displacement curve testing and fatigue characteristic testing. This yields data related to the stiffness and fatigue life of the samples, aiming to quantify key performance indicators, namely stiffness and fatigue life, through physical property testing of the finished springs. This serves as the foundational data source for subsequent performance evaluation and process adjustments. A universal testing machine or specialized spring testing equipment can be used to apply gradually increasing loads to the extracted samples, while simultaneously recording the spring's deformation to plot the force-displacement curve and calculate the spring's stiffness. Alternatively, a fatigue testing machine can be used to apply cyclic loads to the extracted samples, simulating the spring's working state in actual use, recording the number of cycles before spring failure, thereby assessing its fatigue life. Sample extraction can employ statistical methods such as random sampling, stratified sampling, or batch sampling to ensure sample representativeness.

[0063] The acquired test data is compared and analyzed with the preset design target values ​​to determine the performance deviation. This step involves comparing the actual measured spring performance data with the expected, ideal design indicators to quantify the gap between the actual performance and the target performance, i.e., the performance deviation. This is the key basis for judging whether the product is qualified and what adjustments need to be made. The measured stiffness values ​​and fatigue life values ​​can be compared with the upper and lower limits or target values ​​specified in the design specifications using data processing software or manual comparison. Performance deviation can be expressed as an absolute deviation, such as the actual stiffness minus the target stiffness, or a relative deviation, such as the difference between the actual stiffness and the target stiffness divided by the target stiffness and then multiplied by 100%, with corresponding tolerance ranges set. The preset design target values ​​are usually derived from product design specifications, customer requirements, or industry standards, including stiffness tolerances, minimum fatigue life, etc.

[0064] Based on the performance deviations and combined with historical process data, the process parameters that need to be adjusted in the material gradient pretreatment step, the precision winding forming step, or the composite post-treatment step are determined. This step intelligently identifies the potential process links and specific parameters causing the performance deviations based on quantified performance deviations and utilizing past production experience and data. This is a crucial step from problem discovery to problem localization. Specific performance deviation patterns can be associated with potentially relevant process parameters through a pre-set rule base or expert system. Low stiffness may be related to insufficient winding tension or inappropriate heat treatment temperature. Historical process data can include production parameters, test results, and corresponding adjustment records for each batch of products. Data mining, regression analysis, or machine learning algorithms are used to analyze the correlation between process parameters and product performance in historical data, thereby assisting decision-making. The determined process parameters can be the finishing rolling reduction, pre-aging temperature, or time in the material gradient pretreatment step; the winding tension, mandrel speed, or feed speed in the precision winding forming step; or the heat treatment temperature, holding time, and edge strengthening parameters in the composite post-treatment step.

[0065] Based on the determined results, the corresponding process parameters in subsequent production batches are fine-tuned. This step involves applying the adjustment instructions to the production line based on the analysis results of the previous step, making small, refined corrections to the production process parameters of subsequent batches to gradually approach optimal performance. Fine-tuning can be done by manually inputting parameters into the control system or by automatically adjusting equipment parameters according to instructions through the automated control system. Fine-tuning is usually done in small steps within a preset safe or effective range to avoid large changes that could cause new problems. The adjusted parameters are then applied to new production orders or the next batch of production, forming a closed-loop optimization cycle.

[0066] Through the above technical solution, this application provides a systematic process feedback optimization mechanism. By conducting precise force-displacement curve tests and fatigue characteristic tests on the finished springs, stiffness and fatigue life data reflecting the core performance of the springs can be obtained, providing an accurate basis for subsequent analysis. Comparing the obtained test data with preset design target values ​​can quantify performance deviations and clarify the gap between the finished product and the ideal state. More importantly, based on performance deviations and combined with historical process data, the process parameters that need to be adjusted are determined. Utilizing historical data to assist decision-making ensures the targetedness and effectiveness of adjustments, avoiding blind adjustments based solely on a single test result. Finally, based on the determined results, the corresponding process parameters in subsequent production batches are fine-tuned, achieving dynamic optimization of process parameters, thereby improving the performance consistency between production batches and effectively reducing the scrap rate. This closed-loop feedback optimization mechanism, combined with material gradient pretreatment steps, precision winding forming steps, and composite post-processing steps, ensures the performance controllability and stability of the micro-stiffness flat wire springs throughout the entire manufacturing process, enabling them to better meet the needs of high-end applications for high-precision, high-reliability springs.

[0067] In the manufacturing process of low-stiffness flat wire springs, the traditional segmented process has problems such as insufficient material pretreatment precision leading to stress concentration, unstable winding tension control affecting the consistency of coil diameter and pitch, weak post-processing causing stiffness decay and fatigue cracks, and lack of closed-loop feedback optimization resulting in performance dispersion and high scrap rate. It is difficult to meet the stringent requirements of high-end fields such as precision instruments and microelectronic devices for stiffness consistency, fatigue life and dimensional accuracy.

[0068] To address this issue, this application proposes a collaborative manufacturing system for improving the performance of low-stiffness flat wire springs. The system includes a pretreatment unit, a winding unit, a post-processing unit, and a detection and feedback unit. The pretreatment unit is configured to sequentially perform precision rolling and pre-aging treatments on the flat wire raw materials. The precision rolling process reduces thickness tolerance through multi-pass high-precision rolling, improving material uniformity and surface quality. The pre-aging treatment involves holding the material at a specific temperature to promote the precipitation of strengthening phases and release internal stress, thereby optimizing the microstructure and reducing the risk of stress concentration during subsequent winding. The winding unit includes a winding machine, a tension sensing module, and a control module. The tension sensing module monitors the flat wire tension in real time during the winding process and outputs tension data. The control module receives the tension data and outputs dynamic adjustment commands for the winding parameters based on a preset tension model, achieving real-time feedback control based on the differences in flat wire material properties. This ensures stable tension during the winding process and avoids the impact of tension fluctuations on the coil diameter accuracy and pitch consistency of the spring blank. The post-processing unit is configured to sequentially perform multi-stage heat treatment and selective edge strengthening treatment on the spring blanks output from the winding unit. The multi-stage heat treatment involves high-temperature and low-temperature treatments in stages to simultaneously eliminate macroscopic and microscopic internal stresses and stabilize the microstructure. The selective edge strengthening treatment involves chemical polishing or plasma treatment of the spring blank edge areas to precisely remove microscopic defects and form a strengthening layer, preventing fatigue cracks during cyclic loading. The detection and feedback unit is configured to perform sampling performance tests on the finished springs output from the post-processing unit, analyze the test data, output test analysis results, and feed these results back to the control module or central process management module to optimize the process parameters of each unit and establish a closed-loop feedback mechanism based on performance data.

[0069] The core innovation of this embodiment lies in integrating the pretreatment unit, winding unit, post-processing unit, and detection and feedback unit into an organic whole through information sharing and parameter linkage, thereby achieving collaborative control and closed-loop optimization of the entire manufacturing process. The precision rolling and pre-aging treatments in the pretreatment unit provide a highly uniform material base for subsequent processes; the real-time tension monitoring and dynamic adjustment in the winding unit ensure forming accuracy; the multi-stage heat treatment and selective edge strengthening treatment in the post-processing unit comprehensively improve mechanical properties; and the detection and feedback unit adaptively adjusts process parameters based on performance test data. Through these technical solutions, key defects in the manufacturing of low-stiffness flat wire springs are effectively solved, improving the stiffness consistency, fatigue life, and dimensional accuracy of the finished product, meeting the stringent requirements of high-precision elastic elements in high-end applications.

[0070] In some of the embodiments described above in this application, a control module is proposed to receive tension data and output adjustment commands. However, in its implementation, there is a lack of a specific ideal tension model and feedback control algorithm, resulting in insufficient adjustment accuracy and an inability to reduce tension fluctuations accurately in real time, which in turn affects the coil diameter accuracy and pitch consistency of the spring blank.

[0071] In this regard, this application further proposes that the control module of the winding unit stores the ideal tension model and is configured with a feedback control algorithm. The feedback control algorithm is used to calculate and output adjustment commands for the rotational speed and / or wire feeding speed of the winding machine core shaft based on the deviation between the tension data collected in real time by the tension sensing module and the ideal tension model.

[0072] The control module of the winding unit stores the ideal tension model. This ideal tension model is a pre-established tension reference curve or set of values ​​used to guide the flat wire winding process. It can be obtained through theoretical calculations, simulations, or experimental data fitting based on the material properties and geometric dimensions of the flat wire and the structural parameters of the target spring. The model can be stored in the form of parametric equations, dynamically calculating the ideal tension value at the current moment according to the winding progress or the number of spring turns, or it can be stored in the form of a lookup table, which contains the ideal tension settings corresponding to different winding stages or specific geometric points.

[0073] Meanwhile, the control module is also equipped with a feedback control algorithm. This feedback control algorithm is a control strategy that can adjust the system input based on the deviation between the system output and the desired output. For example, the algorithm can use the classic proportional-integral-derivative (PID) control algorithm, which generates the control quantity by calculating the proportional, integral, and derivative terms of the tension deviation. Alternatively, the algorithm can use an adaptive control algorithm, which can adjust the control parameters online according to changes in the flat wire material characteristics or environmental conditions during the winding process to maintain the best control effect.

[0074] The feedback control algorithm is used to calculate and output adjustment commands for the winding machine mandrel speed and / or wire feeding speed based on the deviation between the tension data collected in real time by the tension sensing module and the ideal tension model. Specifically, the tension sensing module continuously monitors the actual feed tension of the flat wire during the winding process and transmits this real-time data to the control module. The feedback control algorithm in the control module compares this actual tension data with the stored ideal tension model in real time to calculate the current tension deviation. Based on this deviation, the feedback control algorithm generates corresponding adjustment commands. When the actual tension is higher than the ideal tension, the algorithm may command to reduce the winding machine mandrel speed or increase the wire feeding speed; when the actual tension is lower than the ideal tension, it may command to increase the mandrel speed or decrease the wire feeding speed. These adjustment commands are sent to the actuator of the winding machine to dynamically adjust the mandrel speed and / or wire feeding speed, thereby maintaining the actual feed tension of the flat wire within the preset tolerance range of the ideal tension model.

[0075] The above technical solution stores an ideal tension model in the control module of the winding unit, providing a precise tension control benchmark for the flat wire winding process and avoiding tension fluctuations caused by the lack of a clear reference in traditional methods. Simultaneously, a feedback control algorithm is configured, enabling the system to monitor the deviation between the actual tension and the ideal tension model in real time and dynamically adjust the winding parameters based on this deviation, thereby achieving closed-loop precise control of the flat wire feed tension. This dynamic, real-time adjustment mechanism reduces tension fluctuations during the winding process, ensuring the coil diameter accuracy and pitch consistency of the spring blank, thus improving the overall performance and batch stability of the low-stiffness flat wire spring.

[0076] In response, this application proposes a low-stiffness flat wire spring, manufactured using the aforementioned collaborative manufacturing method. The core innovation of this embodiment lies in the collaborative integration of material gradient pretreatment, precision winding, composite post-processing, and process feedback optimization steps in a closed-loop manner throughout the entire process. This effectively solves the problems of performance instability, short fatigue life, and low dimensional accuracy of low-stiffness flat wire springs in high-end applications caused by disconnected manufacturing processes, achieving the technical effects of improved stiffness consistency, extended service life, and ensured dimensional accuracy.

[0077] In some of the embodiments described above in this application, the manufacturing of low-stiffness flat wire springs suffers from performance defects caused by inaccurate material pretreatment, fluctuations in winding forming parameters, insufficient targeted post-processing, and lack of feedback mechanisms. In response, this application further proposes a micro-stiffness flat wire spring manufactured by the aforementioned collaborative manufacturing method. The specific implementation includes: in the material gradient pretreatment step, the flat wire raw material undergoes precision rolling to improve thickness uniformity, and pre-aging treatment is combined to optimize microstructure stability, thereby eliminating stress concentration risks caused by uneven raw material structure; in the precision winding forming step, the flat wire feed tension is monitored in real time based on a preset tension model and dynamically adjusted to ensure stable winding process parameters, thus guaranteeing the coil diameter accuracy and pitch consistency of the spring blank; in the composite post-treatment step, multi-stage stress relaxation and shaping treatment is sequentially performed to simultaneously release macroscopic and microscopic stresses, and specific edge areas of the spring flat wire are reinforced to effectively avoid stress residue and edge fatigue cracks; in the process feedback optimization step, the pre-process parameters are adaptively adjusted based on the performance test data of the finished spring, forming a closed-loop optimization mechanism for manufacturing parameters, reducing batch-to-batch performance dispersion and scrap rate.

[0078] Through the above technical solution, the micro-stiffness flat wire spring achieves improved stiffness consistency, meeting the stringent requirements of precision instruments for accurate displacement response to minute force values. Its fatigue life is effectively extended due to edge strengthening treatment and synchronous stress release, making it suitable for microelectronic equipment applications with high cycle counts. Dimensional accuracy is strictly guaranteed through coordinated control of parameters throughout the entire process, ensuring reliable operation in high-end fields such as aerospace. Overall, this application fundamentally overcomes the limitations of traditional segmented processes through organic linkage and dynamic optimization of the manufacturing process, providing a complete technical path for the high-performance manufacturing of micro-stiffness flat wire springs.

[0079] In the manufacturing process of low-stiffness flat wire springs, existing technologies lack a sound process feedback optimization mechanism. Product qualification is judged solely through random sampling of finished products, without establishing a correlation between performance test data and process parameters at each manufacturing stage. This results in poor performance stability between production batches and a high scrap rate. To address this, this application also discloses a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements process feedback optimization steps.

[0080] The process feedback optimization steps include: First, sampling of finished springs, and conducting force-displacement curve tests and fatigue characteristic tests on the samples to obtain actual performance data; second, comparing and analyzing the obtained test data with the preset design target values ​​to determine performance deviations; next, based on the performance deviations and combined with historical process data, determining the process parameters that need to be adjusted; finally, fine-tuning the corresponding process parameters in subsequent production batches according to the determined results. Through the above steps, adaptive closed-loop optimization of the manufacturing process is achieved.

[0081] The core innovation of this embodiment lies in storing the computer program on a computer-readable storage medium and automatically triggering process feedback optimization steps during processor execution. This enables adaptive parameter adjustment based on finished product performance test data, improving performance stability between production batches and reducing scrap rates. When the computer program is executed by the processor, it automatically performs test data acquisition, deviation analysis, parameter decision-making, and fine-tuning operations, replacing traditional manual intervention and improving the efficiency and accuracy of the optimization process. Simultaneously, combining historical process data for decision-making ensures the scientific and targeted nature of parameter adjustments, avoiding blindly modifying process parameters based solely on current deviations, and effectively improving the stiffness consistency and fatigue life of the micro-stiffness flat wire springs. Through this technical solution, the performance dispersion problem caused by the lack of a closed-loop feedback optimization mechanism in the manufacturing process is solved, scrap rates are reduced, and the stringent requirements of high-precision elastic components in high-end fields such as precision instruments and microelectronic devices are met.

[0082] The following example will provide a more detailed explanation of the above technical solution: Using beryllium copper alloy flat wire as raw material, the manufacturing process begins with gradient pretreatment of the material. First, precision rolling is performed: a 20-roll precision rolling mill is used to roll the flat wire in a single pass at room temperature. Real-time online monitoring is conducted using a laser thickness gauge, and the data is fed back to the mill's hydraulic pressing system to dynamically adjust the roll gap, ultimately controlling the flat wire thickness stably within the target range of 0.100±0.001 mm. This reduces thickness tolerance and improves the geometric uniformity of the material. Next, pre-aging treatment is performed: the precision-rolled flat wire coil is placed in a controlled atmosphere heat treatment furnace, heated to 315℃ and held for 120 minutes under pure nitrogen protection, and then cooled in the furnace to below 80℃ before being removed. This process aims to promote the uniform distribution of beryllium atoms as dispersed, fine precipitates within the copper matrix, initially improving the material strength and releasing some of the rolling internal stress, thereby obtaining a flat wire material with a stable and uniform microstructure, laying the foundation for subsequent precision forming.

[0083] The pre-processed flat wire enters the precision winding process. This embodiment uses a high-precision CNC spring winding machine, whose core innovation lies in the integration of a real-time tension closed-loop control system. The system's preset tension model is not a fixed value, but a dynamic curve related to the winding position and speed. This model is established based on a materials mechanics and process database, and its simplified expression considers factors including the real-time cross-sectional moment of inertia of the flat wire, the elastic modulus of the material, and the instantaneous winding radius. During the winding process, a high-response-frequency piezoelectric tension sensor continuously measures the actual tension value of the flat wire before it enters the guide nozzle and transmits the signal to the control module at a frequency of 1000 Hz. The algorithm built into the control module compares the real-time collected tension data with the expected value generated by the ideal tension model at the current winding point. Once it detects that the actual value deviates from the expected value by more than ±2% of the preset tolerance band, the algorithm immediately calculates the required adjustment. For example, if the measured tension is too high, the algorithm will generate instructions to slightly increase the rotational speed of the winding mandrel by about 0.5% by adjusting the servo driver, and simultaneously adjust the speed of the wire feeding motor proportionally to slightly speed up the flat wire feed, thereby pulling the tension back to the set range within milliseconds. This model-based dynamic feedback adjustment ensures that the stress loading history experienced by each spring blank during the forming process is highly consistent, which is the key to obtaining extremely low stiffness dispersion within a batch.

[0084] The resulting spiral spring blank then undergoes post-processing. First, a phased stress relaxation shaping treatment is performed: In the first phase, the spring blank is placed in a tube furnace filled with high-purity argon gas at a flow rate of 15 liters / minute and an oxygen content below 10 ppm, heated to 380°C at a rate of 10°C / minute, and held for 25 minutes. The main purpose of this stage is to efficiently eliminate most of the macroscopic residual stress generated during winding. In the second phase, without compromising the protective atmosphere, the furnace temperature is lowered to 290°C, and held at this temperature for a long period of 480 minutes. This gentle yet sustained phase aims to fully homogenize the micro-stress within the material and further stabilize the precipitated phases, thereby obtaining an extremely stable microstructure to resist stress relaxation during long-term use. After heat treatment, selective edge strengthening is performed. This embodiment employs low-pressure plasma immersion ion implantation technology. The spring blank is fixed in a special fixture with the side edges of the flat wire, i.e., the surface in the thickness direction, facing the plasma source. Through precise control, the argon-nitrogen mixed plasma is applied only to these specific edge regions, with a processing power of 800 watts and a processing time of 30 minutes. This process removes microscopic cutting burrs and defects at the edges with nanometer-level precision, while simultaneously injecting nitrogen ions into the surface to form a reinforcing layer. This greatly suppresses the initiation of fatigue cracks in the area of ​​maximum stress, while the other geometric parts of the spring remain completely unaffected.

[0085] Finally, a process feedback optimization step is implemented to achieve a closed-loop manufacturing process. At least five finished springs are randomly selected from each production batch as samples. Force-displacement curve tests are performed using an ultra-precision material testing machine to calculate stiffness values, and high-cycle fatigue tests are conducted until failure, recording the number of cycles. This performance data is automatically entered into the central process database. The system's built-in optimization algorithm compares the statistical average of the batch's performance data, such as average fatigue life, with the preset design target value. If the average fatigue life of two consecutive batches is found to be 5% lower than the target value, the system will automatically initiate a root cause analysis process. This process calls the historical database and, through correlation analysis, finds that the decrease in fatigue life has the highest statistical correlation with the plasma power parameters during the edge strengthening treatment stage. Based on this, the system decision module automatically generates a process parameter adjustment instruction: increasing the plasma treatment power of subsequent batches from 800 watts to 830 watts. The adjusted parameters are sent to the production execution system to guide the production of the next batch. Simultaneously, the parameter-effect mapping relationship of this adjustment is recorded and used for optimization analysis models, enabling the system to continuously learn. Through deep synergy and closed-loop optimization of the above four steps, this invention achieves a paradigm shift in the manufacturing of micro-stiffness flat wire springs from experience-driven to data and model-driven approaches. Examples show that springs produced using this method have a stiffness dispersion coefficient that can be reduced from over 15% in traditional processes to less than 5%, a median high-cycle fatigue life that is more than doubled, and batch-to-batch quality stability is fundamentally guaranteed, fully meeting the stringent application requirements of high-end precision equipment.

[0086] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method of co-manufacturing micro-stiffness flat wire springs, characterized by, The method comprises the following sequential steps: S1 material gradient pretreatment step: pretreating the flat wire raw material for making the micro-rigidity flat wire spring to improve its organizational uniformity and stability; the pretreatment comprises finish rolling the flat wire to improve its thickness uniformity, and pre-aging the flat wire after finish rolling to optimize its microstructure; S2 precise winding forming step: winding the flat wire after the material gradient pretreatment step into a spring blank by using a winding device; during the winding process, the actual feeding tension of the flat wire is dynamically monitored and feedback adjusted based on a preset tension model, so that the winding process parameters are kept within a predetermined range; S3 composite post-treatment step: sequentially performing stress relaxation setting treatment and edge strengthening treatment on the wound spring blank; the stress relaxation setting treatment comprises at least two heat treatments under different process conditions, and the edge strengthening treatment is performed on specific edge regions of the spring blank; S4 process feedback optimization step: based on the performance test data of the finished spring, at least one process parameter in the material gradient pretreatment step, the precise winding forming step and the composite post-treatment step is adaptively adjusted.

2. The method of co-manufacturing of micro-stiffness p-spring of claim 1, wherein, The material gradient pretreatment step specifically comprises: performing one-pass finish rolling on the purchased precision alloy flat wire to compress its thickness tolerance range; placing the flat wire after finish rolling in a preset low-temperature environment for aging treatment to form a dispersed distribution of strengthening phases in the material and release part of the internal stress.

3. The method of co-manufacturing of micro-stiffness p-spring of claim 1, wherein, The dynamic monitoring and feedback adjustment in the precise winding forming step specifically comprises: real-time acquisition of the feeding tension data of the flat wire during the winding process; real-time comparison of the acquired actual tension data with an ideal tension model established based on the performance of the pretreated flat wire material; when the actual tension data deviates from the preset tolerance range of the ideal tension model, dynamically adjusting the core speed of the winding device and / or the flat wire feeding speed.

4. The method of co-manufacturing of micro-stiffness p-spring of claim 1, wherein, The stress relaxation setting treatment in the composite post-treatment step comprises: first heat treatment stage: performing first heat treatment on the spring blank at a first temperature in a protective atmosphere to eliminate the main macroscopic internal stress introduced during winding; second heat treatment stage: performing long-time heat preservation treatment on the spring blank after the first heat treatment at a second temperature lower than the first temperature to homogenize the micro stress and promote the stability of the material organization.

5. The method of co-manufacturing of micro-stiffness p-spring of claim 1, wherein, The edge strengthening treatment in the composite post-treatment step is a selective treatment, which focuses on the side edges of the flat wire of the spring blank; The edge strengthening treatment adopts chemical polishing or plasma treatment to remove the micro defects of the side edges and form a surface strengthening layer.

6. The method of co-manufacturing of micro-stiffness p-spring of claim 1, wherein, The process feedback optimization step specifically comprises: extracting samples from the finished spring obtained after the composite post-treatment step, performing force-displacement curve test and fatigue property test to obtain the stiffness and fatigue life related data of the samples; comparing and analyzing the obtained test data with the preset design target value to determine the performance deviation; determine, based on the performance deviation and in combination with historical process data, a process parameter to be adjusted in the material gradient pre-processing step, the precision coiling forming step, or the composite post-processing step; fine-tune the corresponding process parameter in a subsequent production batch according to the determination result.

7. A system for the synergic manufacturing of micro-stiff flat wire springs, for implementing the synergic manufacturing method as claimed in any one of claims 1 to 6, characterized by, The system comprises: a pre-processing unit configured to sequentially perform finish rolling and pre-aging on the flat wire raw material; a coiling unit comprising a coiling machine, a tension sensing module, and a control module; the tension sensing module is used to monitor the flat wire tension in real time during the coiling process and output tension data; the control module is configured to receive the tension data and output dynamic adjustment instructions for the coiling parameters according to a preset tension model; a post-processing unit configured to sequentially perform multi-stage heat treatment and selective edge strengthening on the spring blank output by the coiling unit; a detection and feedback unit configured to perform sampling performance testing on the finished spring output by the post-processing unit, analyze the test data to output a test analysis result, and feed back the test analysis result to the control module or a central process management module for optimizing the process parameters of each unit.

8. The system for the co-manufacturing of micro-stiffness p-spring of claim 7, wherein, The control module of the coiling unit stores the ideal tension model and is configured with a feedback control algorithm; The feedback control algorithm is used to calculate and output adjustment instructions for the spindle speed of the coiling machine and / or the wire feeding speed according to the deviation between the tension data collected by the tension sensing module in real time and the ideal tension model.

9. A micro-stiffness flat wire spring characterized by, The micro-rigidity flat wire spring is made by the synergistic manufacturing method of any one of claims 1 to 6.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by a processor, implements the process feedback optimization step of claim 6. The computer program, when executed by a processor, implements the process feedback optimization step of claim 6.

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