The Experts below are selected from a list of 33498 Experts worldwide ranked by ideXlab platform
Jeffrey A. Abell - One of the best experts on this subject based on the ideXlab platform.
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Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries
Journal of Manufacturing Science and Engineering-transactions of The Asme, 2015Co-Authors: Chenhui Shao, S. Jack Hu, Jeffrey A. Abell, J. Patrick SpicerAbstract:This paper presents a tool wear monitoring framework for ultrasonic Metal Welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic Metal Welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a monitoring algorithm using a quadratic classifier and features that are extracted from space and frequency domains of cross-sectional profiles on tool surfaces. The developed algorithm is validated using tool measurement data from a battery plant.
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Tool wear monitoring for ultrasonic Metal Welding of lithium-ion batteries
Volume 2: Materials; Biomanufacturing; Properties Applications and Systems; Sustainable Manufacturing, 2015Co-Authors: Chenhui Shao, S. Jack Hu, Jeffrey A. Abell, J. Patrick SpicerAbstract:This paper presents a tool wear monitoring framework for ultrasonic Metal Welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic Metal Welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a tool condition classification algorithm to identify the state of wear. The developed algorithm is validated using tool measurement data from a battery plant.Copyright © 2015 by ASME and General Motors
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analysis of weld formation in multilayer ultrasonic Metal Welding using high speed images
ASME 2015 International Manufacturing Science and Engineering Conference MSEC 2015, 2015Co-Authors: Jack S Hu, Jeffrey A. AbellAbstract:One of the major challenges in manufacturing automotive lithium-ion batteries and battery packs is to achieve consistent weld quality in joining multiple layers of dissimilar materials. While most fusion Welding processes face difficulties in such joining, ultrasonic Welding stands out as the ideal method. However, inconsistency of weld quality still exists because of limited knowledge on the weld formation through the multiple interfaces. This study aims to establish real-time phenomenological observation on the multilayer ultrasonic Welding process by analyzing the vibration behavior of Metal layers. Such behavior is characterized by a direct measurement of the lateral displacement of each Metal layer using high-speed images. Two different weld tools are used in order to investigate the effect of tool geometry on the weld formation mechanism and the overall joint quality. A series of microscopies and bond density measurements is carried out to validate the observations and hypotheses of those phenomena in multilayer ultrasonic Welding. The results of this study enhance the understanding of the ultrasonic Welding process of multiple Metal sheets and provide insights for optimum tool design to improve the quality of multilayer joints.Copyright © 2015 by ASME and General Motors
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analysis of weld formation in multilayer ultrasonic Metal Welding using high speed images
Journal of Manufacturing Science and Engineering-transactions of The Asme, 2015Co-Authors: Jack S Hu, Jeffrey A. AbellAbstract:One of the major challenges in manufacturing automotive lithium-ion batteries and battery packs is to achieve consistent weld quality in joining multiple layers of dissimilar materials. While most fusion Welding processes face difficulties in such joining, ultrasonic Welding stands out as the ideal method. However, inconsistency of weld quality still exists because of limited knowledge on the weld formation through the multiple interfaces. This study aims to establish real-time phenomenological observation on the multilayer ultrasonic Welding process by analyzing the vibration behavior of Metal layers. Such behavior is characterized by a direct measurement of the lateral displacement of each Metal layer using high-speed images. Two different weld tools are used in order to investigate the effect of tool geometry on the weld formation mechanism and the overall joint quality. A series of microscopies and bond density measurements is carried out to validate the observations and hypotheses of those phenomena in multilayer ultrasonic Welding. The results of this study enhance the understanding of the ultrasonic Welding process of multiple Metal sheets and provide insights for optimum tool design to improve the quality of multilayer joints.
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characterization of ultrasonic Metal Welding by correlating online sensor signals with weld attributes
Journal of Manufacturing Science and Engineering-transactions of The Asme, 2014Co-Authors: Chenhui Shao, Elijah Kannateyasibu, Patrick J Spicer, Jack S Hu, Jeffrey A. AbellAbstract:Online process monitoring in ultrasonic Welding of automotive lithium-ion batteries is essential for robust and reliable battery pack assembly. Effective quality monitoring algorithms have been developed to identify out of control parts by applying purely statistical classification methods. However, such methods do not provide the deep physical understanding of the manufacturing process that is necessary to provide diagnostic capability when the process is out of control. The purpose of this study is to determine the physical correlation between ultrasonic Welding signal features and the ultrasonic Welding process conditions and ultimately joint performance. A deep understanding in these relationships will enable a significant reduction in production launch time and cost, improve process design for ultrasonic Welding, and reduce operational downtime through advanced diagnostic methods. In this study, the fundamental physics behind the ultrasonic Welding process is investigated using two process signals, weld power and horn displacement. Several online features are identified by examining those signals and their variations under abnormal process conditions. The joint quality is predicted by correlating such online features to weld attributes such as bond density and postweld thickness that directly impact the weld performance. This study provides a guideline for feature selection and advanced diagnostics to achieve a reliable online quality monitoring system in ultrasonic Metal Welding.
Chenhui Shao - One of the best experts on this subject based on the ideXlab platform.
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online tool condition monitoring for ultrasonic Metal Welding via sensor fusion and machine learning
Journal of Manufacturing Processes, 2021Co-Authors: Qasim Nazir, Chenhui ShaoAbstract:Abstract In ultrasonic Metal Welding (UMW), tool wear significantly affects the weld quality and tool maintenance constitutes a substantial part of production cost. Thus, tool condition monitoring (TCM) is crucial for UMW. Despite extensive literature focusing on TCM for other manufacturing processes, limited studies are available on TCM for UMW. Existing TCM methods for UMW require offline high-resolution measurement of tool surface profiles, which leads to undesirable production downtime and delayed decision-making. This paper proposes a completely online TCM system for UMW using sensor fusion and machine learning (ML) techniques. A data acquisition (DAQ) system is designed and implemented to obtain in-situ sensing signals during Welding processes. A large feature pool is then extracted from the sensing signals. A subset of features are selected and subsequently used by ML-based classification models. A variety of classification models are trained, validated, and tested using experimental data. The best-performing classification models can achieve close to 100% classification accuracy for both training and test datasets. The proposed TCM system not only provides real-time TCM for UMW but also can support optimal decision-making in tool maintenance. The TCM system can be extended to predict remaining useful life (RUL) of tools and integrated with a controller to adjust Welding parameters accordingly.
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multi task learning for data efficient spatiotemporal modeling of tool surface progression in ultrasonic Metal Welding
Journal of Manufacturing Systems, 2021Co-Authors: Haotian Chen, Yuhang Yang, Chenhui ShaoAbstract:Abstract Spatiotemporal processes commonly exist in manufacturing. Modeling and monitoring such processes are crucial for ensuring high-quality production. For example, ultrasonic Metal Welding is an important industrial-scale joining technique with wide applications. The surfaces of ultrasonic Welding tools evolve in both spatial and temporal domains, resulting in a spatiotemporal process. Close monitoring of tool surface progression is imperative since degraded tools often lead to low-quality joints. However, it is generally expensive and time-consuming to acquire fine-scale surface measurement data, which is not economically viable. This paper develops a multi-task learning method to enable data-efficient spatiotemporal modeling. A Gaussian process-based hierarchical Bayesian inference structure is constructed to transfer knowledge among multiple similar-but-not-identical measurement tasks. Meanwhile, a spatiotemporal kernel is developed based on squared sine exponential damping (SSED) function to characterize the periodic trend of anvil surfaces. The proposed method is able to improve interpolation accuracy using limited measurement data compared with state-of-the-art techniques. Data collected from lithium-ion battery production are employed to demonstrate the effectiveness of the proposed method. Additionally, the influence of training data size and hyperparameter selection on the modeling performance is systematically investigated.
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Improving process robustness in ultrasonic Metal Welding of lithium-ion batteries
Journal of Manufacturing Systems, 2018Co-Authors: Lihang Nong, Chenhui Shao, Tae Hyung KimAbstract:Abstract Ultrasonic Metal Welding is a solid-state joining method popularly adopted in the assembly of lithium-ion battery cells, modules, and packs for electrical vehicles due to its numerous advantages over traditional fusion Welding techniques. Ultrasonic Metal Welding process yields quality welds under optimal conditions, but can result in poor welds when there are disturbances, such as the presence of oil contamination. State-of-the-art controllers cannot detect those disturbances or control the Welding process accordingly. In this research, two methods are proposed to improve the process robustness, namely, a real-time controller and a new tool geometry design for the sonotrode. The developed controller monitors the on-line power signal and adjusts the weld clamping pressure through a calibrated step function accordingly. Experimental results show that with oil contaminated workpieces, the new controller yielded an average improvement of 14.5–440% in the T-peel strength over the current controller, depending on the level of oil contamination. Additionally, the process robustness was shown to be improved by the use of a spherical tool in place of a flat tool. Improvements are achieved for all tested clamping pressures, especially when the pressure is outside the optimal range for the flat tool.
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Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries
Journal of Manufacturing Science and Engineering-transactions of The Asme, 2015Co-Authors: Chenhui Shao, S. Jack Hu, Jeffrey A. Abell, J. Patrick SpicerAbstract:This paper presents a tool wear monitoring framework for ultrasonic Metal Welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic Metal Welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a monitoring algorithm using a quadratic classifier and features that are extracted from space and frequency domains of cross-sectional profiles on tool surfaces. The developed algorithm is validated using tool measurement data from a battery plant.
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Tool wear monitoring for ultrasonic Metal Welding of lithium-ion batteries
Volume 2: Materials; Biomanufacturing; Properties Applications and Systems; Sustainable Manufacturing, 2015Co-Authors: Chenhui Shao, S. Jack Hu, Jeffrey A. Abell, J. Patrick SpicerAbstract:This paper presents a tool wear monitoring framework for ultrasonic Metal Welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic Metal Welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a tool condition classification algorithm to identify the state of wear. The developed algorithm is validated using tool measurement data from a battery plant.Copyright © 2015 by ASME and General Motors
Frank Balle - One of the best experts on this subject based on the ideXlab platform.
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Orbital Ultrasonic Welding of Ti-Fittings to CFRP-Tubes
Journal of Manufacturing and Materials Processing, 2021Co-Authors: Moritz Liesegang, Sophie Arweiler, Tilmann Beck, Frank BalleAbstract:Hybrid structures are important for the automotive and aeronautical industry as they have the potential to reduce vehicle or aircraft weight and to improve fuel efficiency. Continuous ultrasonic Metal Welding is a promising technique for hydraulic applications in aircraft to realise tubular Metal/fiber reinforced polymer (FRP) hybrids. Fluid proof connections between dissimilar components can be joined by continuous Welding seams. Tubular Metal/FRP hybrids, produced by a new advanced variant of ultrasonic Metal Welding, are investigated as a potential substitute for Metallic hydraulic tubes. The oscillating Welding system moves around the tubular joining partners to generate a sealed orbital connection. Homogeneous joint quality is required to assure the requested component strength. Therefore, the amplitude of sonotrode displacement and the Welding force are controlled to keep the induced Welding energy constant and the joint quality uniform. High mechanical strength is required for a safe application in the 5000 psi hydraulic system of current and future aircraft concepts. For this study Metal injection molded (MIM) titanium fittings (TiAl6V4) and carbon fiber reinforced PEEK (CF-PEEK) tubes were investigated. Process parameters for Metal/FRP hybrid joining were evaluated considering their mechanical and technological properties, as well as the microstructure of the hybrid interfacial area. The entire joining area of tubular joining partners has to be in close contact before Welding to assure a continuous tight joint. Hence, the titanium fitting is thermally shrunk onto the CFRP tube before ultrasonic Welding. The presented orbital ultrasonic Welding technology was developed for prospective industrial use and future applications of ultrasonically welded tubular multi-material-components.
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Ultrasonic torsion Welding of ageing-resistant Al/CFRP joints: Properties, microstructure and joint formation.
Ultrasonics, 2018Co-Authors: Florian Staab, Frank BalleAbstract:Abstract Ultrasonic Metal Welding is a promising process for joining light Metals with fiber-reinforced thermoplastics. The technique is characterized by high reproducibility, short process times, low energy input, no additional filler materials and finally the possibility of extensive process data logging. With this process, dissimilar aerospace materials are ultrasonically welded and the applied process parameters are optimized by statistical methods. A prediction of ageing resistance is possible by the evaluation of the electrical resistivity of the multi-material-joints. With the help of detailed process parameter recording and microscopic investigations, the bonding mechanism of hybrid AA5024/(GF-)CF-PEEK joints is explained and the kinematics of bonding formation is presented in detail.
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Ultrasonic torsion Welding of ageing-resistant Al/CFRP joints: Properties, microstructure and joint formation.
Ultrasonics, 2018Co-Authors: Florian Staab, Frank BalleAbstract:Abstract Ultrasonic Metal Welding is a promising process for joining light Metals with fiber-reinforced thermoplastics. The technique is characterized by high reproducibility, short process times, low energy input, no additional filler materials and finally the possibility of extensive process data logging. With this process, dissimilar aerospace materials are ultrasonically welded and the applied process parameters are optimized by statistical methods. A prediction of ageing resistance is possible by the evaluation of the electrical resistivity of the multi-material-joints. With the help of detailed process parameter recording and microscopic investigations, the bonding mechanism of hybrid AA5024/(GF-)CF-PEEK joints is explained and the kinematics of bonding formation is presented in detail.
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ultrasonic Metal Welding of aluminium sheets to carbon fibre reinforced thermoplastic composites
Advanced Engineering Materials, 2009Co-Authors: Frank Balle, Guntram Wagner, Dietmar EiflerAbstract:The ultrasonic Welding technology is an innovative method to produce hybrid joints for multi-material components. The investigations described in this paper were carried out using the ultrasonic Metal Welding technique for joining carbon fibre reinforced thermoplastic composites (CFRP) with sheet Metals like aluminium alloys or aluminium-plated steels. The achievable mechanical properties as a function of the process parameters are presented. Additionally, microscopic investigations of the bonding zone are discussed. One important advantage of ultrasonic Metal Welding is the possibility to realise a direct contact between the load bearing fibres of the reinforced composite and the Metallic surface without destroying the carbon fibres.
Kalakkath Prakasan - One of the best experts on this subject based on the ideXlab platform.
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temperature and stress distribution in ultrasonic Metal Welding an fea based study
Journal of Materials Processing Technology, 2009Co-Authors: Satheesh Elangovan, S Semeer, Kalakkath PrakasanAbstract:In ultrasonic Welding, high frequency vibrations are combined with pressure to join two materials together quickly and securely, without producing significant amount of heat. During ultrasonic Welding of sheet Metal, normal and shear forces act on the parts to be welded and the weld interface. These forces are the result of ultrasonic vibrations of the tool, pressed onto the parts to be welded. In this study a model for the temperature distribution during Welding and stress distribution in the horn and welded joints are presented. With the knowledge of the forces that act at the interface it is possible to control weld strength and avoid sonotrode Welding (sticking of the sonotrode to the parts). The presented finite element model is capable of predicting the interface temperature and stress distribution during Welding and their influences in the work piece, sonotrode and anvil. The study also included the effect of clamping forces, material thickness and coefficient of friction during heat generation at the weld interface.
Chin-an Tan - One of the best experts on this subject based on the ideXlab platform.
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Dynamic Response of Battery Tabs Under Ultrasonic Welding
Journal of Manufacturing Science and Engineering, 2013Co-Authors: Bongsu Kang, Wayne Cai, Chin-an TanAbstract:Ultrasonic Metal Welding (USMW) for battery tabs must be performed with 100% reliability in battery pack manufacturing as the failure of a single weld essentially results in a battery that is inoperative or cannot deliver the required power due to the electrical short caused by the failed weld. In ultrasonic Metal Welding processes, high-frequency ultrasonic energy is used to generate an oscillating shear force (sonotrode force) at the interface between a sonotrode and few Metal sheets to produce solid-state bonds between the sheets clamped under a normal force. These forces, which influence the power needed to produce the weld and the weld quality, strongly depend on the mechanical and structural properties of the weld parts and fixtures in addition to various Welding process parameters, such as weld frequencies and amplitudes. In this work, the effect of structural vibration of the battery tab on the required sonotrode force during ultrasonic Welding is studied by applying a longitudinal vibration model for the battery tab. It is found that the sonotrode force is greatly influenced by the kinetic properties, quantified by the equivalent mass, equivalent stiffness, and equivalent viscous damping, of the battery tab and cell pouch interface. This study provides a fundamental understanding of battery tab dynamics during ultrasonic Welding and its effect on weld quality, and thus provides a guideline for design and Welding of battery tabs from tab dynamics point of view. © 2014 by ASME.