Methods for optimizing the placement of weld points in resistance spot welding

Abstract

Method (100) for optimizing the placement of weld spots during resistance spot welding comprises several steps that enable precise analysis and adjustment of the welding parameters. First, welding process data is acquired (102). This data is used to monitor and optimize the welding process. In step (104), geometric design data is extracted from a CAD model, including the weld spot location, material thickness combinations (MCT), and geometric features such as edge distances. This data is necessary to analyze the weld spot placement. In step (106), a two-dimensional analysis is performed, calculating distances between weld spots and component features. In step (108), a three-dimensional analysis is carried out, taking into account the spot location in relation to the geometric properties of the surroundings.Step (110) links the geometric design data with the welding process data, including the quality score, enabling a detailed analysis. In step (112), correlations between the geometric location of the weld spots and the weld quality are determined. In step (114), alternative spot locations and / or material thickness combinations are identified to improve the weld quality. Finally, in step (116), optimization recommendations for the design are generated to increase the weld quality by adjusting the spot location or material thickness combination.

Description

The present invention relates to a method for data-based optimization of the positioning of weld points in resistance spot welding, in particular using welding process data in conjunction with geometric design data. Furthermore, the invention relates to a corresponding computer program product configured to carry out the method. Currently, when resistance spot welding body components, weld points are primarily defined based on general design principles, material requirements, and manufacturing constraints. As a result, welding defects such as spatter formation frequently occur, often due to unfavorable geometric placement of the weld points. Subsequent adjustments to the weld point positions are time-consuming and costly, as they require extensive changes to the design and production planning. US 2023 / 0 281 361 A1 , DE 10 2024 121 121 A1 , CN 1 06 126 849 A and DE 10 2018 123 833 A1 disclose methods for optimizing the placement of weld spots in resistance spot welding. The object of the invention is therefore to provide a method with which the weld point positions can be analyzed and optimized as early as the design phase, taking into account real welding process data. In this way, welding defects should be avoided at an early stage, rework reduced and production quality improved. The solution to this problem is achieved according to the teaching of the independent claims. Various embodiments and further developments of the invention are the subject of the dependent claims. According to one embodiment, a method for optimizing the placement of weld spots in resistance spot welding includes acquiring welding process data such as current, voltage, welding time, and a quality score for each weld spot. The quality score is a numerical evaluation of the weld spot quality based on parameters such as resistance or penetration depth. Additionally, geometric design data is extracted from a CAD model, including the location of the weld spots, material thickness combinations (MCTs), edge distances, overlap areas, local curvatures, and material thickness profiles. This data is used in a two-dimensional analysis to calculate spot spacing and in a three-dimensional analysis to determine the spot location in space. Based on these analyses, the geometric features are linked with the welding process data to determine correlations between the location of the weld spots and their quality.Based on these correlations, alternative point positions or material thicknesses are suggested to optimize the design. The process can also include subsequent welding of a component. This method allows for more precise placement of the weld points, resulting in improved weld quality and a reduction in potential errors. This increases the durability and strength of the welded joints and contributes to optimizing the manufacturing process. According to one embodiment, the quality score is derived from an existing algorithm that assesses weld spot quality based on real-time welding data. This automatic assessment of the quality score enables rapid feedback and targeted control of the welding process. This ensures consistent welding quality and allows the process to be continuously adjusted, increasing the efficiency and precision of the welding. According to another embodiment, the two-dimensional analysis involves normalizing and weighting the distances between the welding points and structural features such as component edges, flanges or overlaps. This consideration of the distances allows for a targeted adjustment of the weld point placement in order to maximize the structural integrity of the component and to avoid potential weak points due to insufficient spacing. According to one embodiment, the three-dimensional analysis includes considering sheet metal curvature, material thickness, and joining positions in spatial coordinates. This comprehensive three-dimensional analysis enables a more precise determination of the weld point location in relation to the component geometry. This allows for the consideration of complex geometries and material changes, leading to better accuracy of the weld points and increasing the overall weld quality. According to one embodiment, comparison groups of weld points with identical material thickness combination (MDK) are formed at different geometric positions in order to analyze the positional influences in isolation. This methodology makes it possible to identify the influence of the spot location on the weld quality and improves the understanding of the optimal weld spot placement for different component geometries. According to a further embodiment, a different material thickness combination is proposed for geometrically similar layers, enabling better weld quality. This improvement is based on the determined correlations and ensures that material combinations are used that optimize weld quality, resulting in a stronger and more stable joint. According to one implementation, design recommendations are automatically derived and fed into a CAD system as feedback. This enables rapid adjustments to the design based on welding process data and weld quality. Design errors can thus be identified and corrected early, making the entire manufacturing process more efficient and reducing production times. According to one embodiment, weld points with low quality scores are visually highlighted, and alternative point positions are automatically generated. This visual representation of welding defects allows for immediate correction and ensures that only high-quality weld points are used for the final production of a component. According to another embodiment, the optimization data obtained for the continuous improvement of component designs are stored in a set of design rules or a database. This ensures that optimizations are taken into account in future designs, leading to a long-term improvement in weld quality and manufacturing efficiency. According to one embodiment, the method comprises a computer program product that can be executed on a computer or data processing unit to perform the weld spot placement optimization process. The computer program is designed to link welding process data with geometric design data, analyze correlations between spot location and weld quality, determine quality scores, and provide weld spot placement optimization suggestions. This program optimizes the entire welding process and contributes to more efficient manufacturing. A system and / or means according to the present invention can be configured as hardware and / or software, in particular comprising at least one processing unit, preferably a microprocessor unit (CPU), graphics processing unit (GPU), or the like, preferably connected to a storage and / or bus system via data or signals, and / or comprising one or more programs or program modules. The processing unit can be configured to execute instructions implemented as a program stored in a storage system, to acquire input signals from a data bus, and / or to output signals to a data bus. A storage system can comprise one or more, in particular different, storage media, in particular optical, magnetic, solid-state, and / or other non-volatile media. The program can be configured to embody the methods described herein.is capable of performing such processes, so that the processing unit can execute the steps of such procedures and thus, in particular, operate or monitor the machine. A computer program product may, in one embodiment, include a storage medium, in particular a computer-readable and / or non-volatile medium, for storing a program or instructions, or with a program or instructions stored thereon. In one embodiment, the execution of this program or these instructions by a system or a controller, in particular a computer or an arrangement of several computers, causes the system or the controller, in particular the computer(s), to execute a procedure described herein or one or more of its steps, or the program or instructions are configured for this purpose. In one implementation, one or more, in particular all, steps of the process are carried out fully or partially automatically, in particular by the control system or its means. Any terms used herein, such as "comprises," "includes," "features," "has," "with," or any other variant thereof, are intended to cover non-exclusive inclusion. For example, a method or apparatus that includes or features a list of elements is not necessarily limited to those elements but may include other elements not expressly listed or inherent in such method or apparatus. Furthermore, unless explicitly stated otherwise, "or" refers to an inclusive or and not an exclusive "or". For example, a condition A or B is satisfied by one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present). The terms "ein" or "eine," as used here, are defined as "one or more." The terms "ein anderer" and "ein Weitere," as well as any other variant thereof, are to be understood as "at least one more." The terms "configured" or "set up" to perform a specific function (and their respective variations), as used here, mean that a device or component thereof already exists in a configuration or setting capable of performing the function, or at least is adjustable—i.e., configurable—so that it can perform the function after appropriate adjustment. Configuration can be achieved, for example, by adjusting process parameters or by using switches or similar devices to activate or deactivate functionalities or settings. In particular, the device may have several predefined configurations or operating modes, allowing configuration by selecting one of these. Further advantages, features, and applications of the present invention will become apparent from the following detailed description in conjunction with the figures. Figure 1 schematically shows a flowchart of the process. Fig. 1 shows a flowchart of method 100 for optimizing the placement of weld spots in resistance spot welding, with the individual steps from 102 to 116 depicted schematically. Method 100 serves to optimize weld quality through precise adjustments of the weld spot placement and material thickness combinations (MCT). In the first step, 102, the welding process data generated during the welding process is recorded. This data includes important parameters such as current, voltage, welding time, and a quality score for each weld point. This information is crucial for evaluating the performance of the welding process and identifying potential problems in weld quality. In the next step, geometric design data is extracted from a CAD model. This data includes not only the location of the weld points, but also material thickness combinations (MCTs) and geometric features such as edge distances, overlap areas, curvatures, and material thickness profiles. Accurate recording of these parameters is essential for analyzing and optimizing the welding process, as they directly influence the effectiveness and quality of the weld. In step 106, a two-dimensional analysis is performed, calculating the distances between the weld points and their associated structural features. These calculations serve to evaluate the arrangement of the weld points in relation to the surrounding components and features. This allows the welding process to be optimized in terms of efficiency and quality with regard to the geometric arrangement of the weld points. In step 108, a three-dimensional analysis is performed. Here, the spot position is determined relative to the geometric properties of the surroundings, such as local sheet metal curvature or the spatial orientation of the components. This three-dimensional analysis is particularly important for understanding how the position of a weld spot in three-dimensional space affects weld quality and stability. In the next step, the previously extracted geometric design data is linked with the recorded welding process data. This linkage makes it possible to evaluate the quality of each weld point in relation to its geometric position and the associated process parameters. This is a crucial step for identifying specific correlations between geometry and weld quality. In step 112, the collected data is analyzed to identify correlations between the geometric location of the weld points and the weld quality. These correlations are crucial for determining how the position of the weld points in relation to geometric features affects weld quality and which areas of the component might be more susceptible to quality problems. In step 114, alternative spot locations and / or suitable material thickness combinations are identified. Based on the previous analyses, optimization options are proposed to further improve weld quality. This step helps to strategically place the welds in the best positions for the respective component geometries, thereby further increasing the efficiency and quality of the welding process. Finally, section 116 generates optimization recommendations for the design. These recommendations relate in particular to adjusting the spot location or material thickness combinations depending on the geometric conditions of the component. Applying these optimization recommendations leads to higher weld quality and ensures that the welding process is optimally adapted to the specific requirements of the component. The flowchart illustrates how each step in Process 100 works together to improve weld quality through the precise placement of weld points and the selection of optimal material thickness combinations. The acquisition of welding process data and the analysis of geometric design data lead to a sound assessment of weld quality and enable targeted adjustments to the welding process. Identifying correlations between geometric position and weld quality, and generating optimization recommendations, ensures continuous improvement of the welding process. This results in more stable, higher-quality welds and contributes to a reduction in scrap and rework. The automation and precision of this process significantly increase efficiency in the manufacturing process. In the figures, identical reference symbols denote identical, similar, or corresponding elements. Elements depicted in the figures are not necessarily shown to scale. Rather, the various elements depicted in the figures are represented in such a way that their function and general purpose are understandable to a person skilled in the art. Connections and couplings between functional units and elements shown in the figures can, unless expressly stated otherwise, also be implemented as indirect connections or couplings. Functional units can, in particular, be implemented as hardware, software, or a combination of hardware and software. While at least one exemplary embodiment has been described above, it should be noted that a large number of variations exist. It should also be noted that the described exemplary embodiments are merely non-limiting examples, and it is not intended to restrict the scope, applicability, or configuration of the devices and methods described herein. Rather, the preceding description will provide the person skilled in the art with guidance for implementing at least one exemplary embodiment. It is understood that various modifications to the function and arrangement of the elements described in an exemplary embodiment can be made without deviating from the subject matter defined in the appended claims and their legal equivalents.

Claims

Method (100) for optimizing the placement of weld spots in resistance spot welding, comprising the steps of: - Acquiring (102) welding process data generated during the welding process, wherein the welding process data includes at least current, voltage, welding time and a quality score for each weld spot; - Extracting (104) geometric design data from a CAD model, wherein the design data includes at least the location of the weld spots, material thickness combinations (MCTs) and geometric features such as edge distances, overlap areas, curvatures and material thickness profiles; - Two-dimensional analysis (106) in which distances between individual weld spots and associated design features are calculated; - Three-dimensional analysis (108) in which a spot location is determined relative to geometric properties of the environment.- Linking (110) the analyzed geometric design data with the recorded welding process data, including a quality score; - Determining (112) correlations between the geometric location of the weld spots and the weld quality; - Identifying (114) alternative spot locations and / or more suitable material thickness combinations based on the analyzed data; - Generating (116) optimization recommendations for the design, in particular for adjusting the spot location or the material thickness combination depending on the geometric conditions to increase weld quality. Method (100) according to claim 1, characterized in that the quality score is derived from an existing algorithm which performs an evaluation of the weld point quality on the basis of real-time welding data. Method (100) according to one of the preceding claims, characterized in that in the two-dimensional analysis the distances of the welding points to structural features such as component edges, flanges and overlaps are normalized and weighted. Method (100) according to one of the preceding claims, characterized in that the local sheet curvatures, material thicknesses and joining positions are taken into account in spatial coordinates in the three-dimensional analysis. Method (100) according to one of the preceding claims, characterized in that comparison groups of weld points with identical material thickness combination (MDK) are formed at different geometric positions in order to analyze positional influences in isolation. Method (100) according to one of the preceding claims, characterized in that a different material thickness combination with better weld quality is proposed for geometrically similar layers. Method (100) according to one of the preceding claims, characterized in that design recommendations are automatically derived from the determined correlations and fed into a CAD system as feedback. Method (100) according to one of the preceding claims, characterized in that weld points with low quality scores are visually highlighted and alternative point positions are automatically generated. Method (100) according to one of the preceding claims, characterized in that the determined optimization data are stored in a set of design rules or a database for the continuous improvement of component designs. A computer program product with program code, characterized in that it is executable on a computer or a data processing unit to perform a method according to one of claims 1 to 9, wherein the computer program product is in particular configured to: - link recorded welding process data with geometric design data, - analyze correlations between geometric position and welding quality from this linkage, - determine quality scores, - evaluate geometric influencing factors, and - provide automated optimization suggestions for weld spot placement.

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