633 research outputs found

    Anvil Design and Experimental Investigation for Ultrasonic Welding of Thin Dissimilar Metals

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    Ultrasonic Welding (USW) is a solid-state bonding process that produces joints by allowing transfer of high frequency vibratory energy in to the work pieces which are brought together under pressure. The whole process is done without melting of any of the material. It can be used as a micro-welding technique which is being widely used for vehicles, shipbuilding, and the welding of electric and electronic parts. Ultrasonic tooling is one which greatly affects the performance of whole welding system. Anvil is an important part which includes in ultrasonic tooling. Design of anvil is peculiarly based on the geometry. Very few studies are done on the effect of welding process on the geometrical changes of the anvil. In this work, ultrasonic anvil was designed in two different geometrical shapes with same material SS 304, which was then fabricated by series of operations and investigated the effects of Tensile strength, T-peel strength and weld quality. The experimental design was done in Taguchi method using L9 orthogonal array and MOORA method was used to convert the multiobjective optimization problem to single one. Then, Taguchi method was further used to optimize the response parameters

    JOINING SEQUENCE ANALYSIS AND OPTIMIZATION FOR IMPROVED GEOMETRICAL QUALITY

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    Disturbances in the manufacturing and assembly processes cause geometrical variation from the ideal geometry. This variation eventually results in functional and aesthetic problems in the final product. Being able to control the disturbances is the desire of the manufacturing industry. \ua0 Joining sequences impact the final geometrical outcome in an assembly considerably. To optimize the sequence for improved geometrical outcome is both experimentally and computationally expensive. In the simulation-based approaches, based on the finite element method, a large number of sequences need to be evaluated.\ua0 In this thesis, the simulation-based joining sequence optimization using non-rigid variation simulation is studied. Initially, the limitation of the applied algorithms in the literature has been addressed. A rule-based optimization approach based on meta-heuristic algorithms and heuristic search methods is introduced to increase the previously applied algorithms\u27 time-efficiency and accuracy. Based on the identified rules and heuristics, a reduced formulation of the sequence optimization is introduced by identifying the critical points for geometrical quality. A subset of the sequence problem is identified and solved in this formulation.\ua0 For real-time optimization of the joining sequence problem, time-efficiency needs to be further enhanced by parallel computations. By identifying the sequence-deformation behavior in the assemblies, black-box surrogate models are introduced, enabling parallel evaluations and accurate approximation of the geometrical quality. Based on this finding, a deterministic stepwise search algorithm for rapid identification of the optimal sequence is introduced.\ua0 Furthermore, a numerical approach to identify the number, location from a set of alternatives, and sequence of the critical joining points for geometrical quality is introduced. Finally, the cause of the various deformations achieved by joining sequences is identified. A time-efficient non-rigid variation simulation approach for evaluating the geometrical quality with respect to the sequences is proposed. \ua0 The results achieved from the studies presented indicate that the simulation-based real-time optimization of the joining sequences is achievable through a parallelized search algorithm and a rapid evaluation of the sequences. The critical joining points for geometrical quality are identified while the sequence is optimized. The results help control the assembly process with respect to the joining operation, improve the geometrical quality, and save significant computational time

    Development of Friction Flash to Tube (F2T) and application to S355 grade steel

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    Friction Flash to Tube (F2T) is an innovative friction based manufacturing technique to produce seamless tubes based on open die forging, invented at Aalto University. These tubes can be produced economically in small sizes and batches, envisaging applications of high value materials that are not available in the market. The objective of this Master thesis was to develop the experimental condition of F2T as well as the proper parameters in F2T by approaching Taguchi method. The pre-defined parameters to investigate in Taguchi method were established as forging force, tool rotation and initial transient plunging depth and the investigating of geometrical and metallurgical characteristics were done. Cold rolled high strength and low alloy structural steel S355 is the material used in this research work. The parameters of the F2T process were developed based on design of experiments, with geometrical and hardness properties as performance parameters. The optimized conditions and parameters were applied to produce tubes for extensive evalua-tion of the mechanical and metallurgical material properties. The F2T process has specific components and control demands that cannot be met by the existing manufacturing systems. This challenge was overcome by developing one first version of a dedicated system based on an existent Friction Stir Welding equipment. One additional challenge was to produce tubes longer than 40 mm because of buckling. The buckling was prevented by implementing a lateral support system constraining the consumable rod during the initial transient plunging period. The test specimens for extensive mechanical test and metallurgical analysis were extracted from tubes produced with 80 mm in length. These longer tubes were manufactured using the support system to prevent buckling. The results on tensile test, flattening test and flare test of F2T tube reveal that the mechanical properties of produced tubes are as good as tube of similar material produced by another manufacturing technique. The temperature during the application of the F2T process was monitored with thermo-couples. The mechanical properties of produced tubes were evaluated by hardness meas-urement of cross and longitudinal sections. Tensile test were applied to sub-sections of wall of the tubes, and flare and flattening test to the whole tubes. The metallurgical analysis encompasses optical microscopic analysis, and SEM/EBSD with grain size evaluation. The research work demonstrate the feasibility of producing seamless tubes by F2T in structural steel. A correct design of a dedicated system to prevent the buckling, enables to produce long tubes

    Effect of process parameters on the mechanical properties and failure behavior of spot welded low carbon steel

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    In this research, the effect of spot welding parameters on weld quality was investigated. The main affecting welding parameters such as weld current, weld time, electrode force and holding time were determined as the basis for quality evaluation. The selected quality features were classified into mechanical properties and failure behavior, which were required for application with highly dynamic loading. The peak load as one of the important mechanical properties, as well as the two distinct failure modes which were cross-nugget and complete button pull, were observed using tensile-shear stress. To obtain detailed shear stress testing results and to determine the significance of parameters, a servo-hydraulic testing machine was run at a constant cross-head speed of 2mm/min followed by statistical analysis methods, which were Taguchi’s L16 orthogonal array and Analysis of Variance (ANOVA). Furthermore, the failure mode was to be observed based on the fracture surface used as reference for acceptance or rejection of the weld joint. Based on the results, the weld current was the significant factor affecting shear stress and the complete button pull was mostly found, which leads to the satisfactory condition of the joint. Cross-nugget and full button pull-out were the dominant failures observed in the lap-shear test. The cross-nugget failure leads to a low shear load, while complete button pull-out displays maximum shear load

    DIRECT METAL LASER SINTERING OF TI-6AL-4V ALLOY: PROCESS-PROPERTY-GEOMETRY EMPIRICAL MODELING AND OPTIMIZATION

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    DIRECT METAL LASER SINTERING OF TI-6AL-4V ALLOY: PROCESS-PROPERTY-GEOMETRY EMPIRICAL MODELING AND OPTIMIZATIO

    Laser dimpling process parameters selection and optimization using surrogate-driven process capability space

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    Remote laser welding technology offers opportunities for high production throughput at a competitive cost. However, the remote laser welding process of zinc-coated sheet metal parts in lap joint configuration poses a challenge due to the difference between the melting temperature of the steel (∼1500 C) and the vaporizing temperature of the zinc (~907 C). In fact, the zinc layer at the faying surface is vaporized and the vapour might be trapped within the melting pool leading to weld defects. Various solutions have been proposed to overcome this problem over the years. Among them, laser dimpling has been adopted by manufacturers because of its flexibility and effectiveness along with its cost advantages. In essence, the dimple works as a spacer between the two sheets in lap joint and allows the zinc vapour escape during welding process, thereby preventing weld defects. However, there is a lack of comprehensive characterization of dimpling process for effective implementation in real manufacturing system taking into consideration inherent changes in variability of process parameters. This paper introduces a methodology to develop (i) surrogate model for dimpling process characterization considering multiple–inputs (i.e. key control characteristics) and multiple–outputs (i.e. key performance indicators) system by conducting physical experimentation and using multivariate adaptive regression splines; (ii) process capability space (Cp–Space) based on the developed surrogate model that allows the estimation of a desired process fallout rate in the case of violation of process requirements in the presence of stochastic variation; and, (iii) selection and optimization of the process parameters based on the process capability space. The proposed methodology provides a unique capability to: (i) simulate the effect of process variation as generated by manufacturing process; (ii) model quality requirements with multiple and coupled quality requirements; and (iii) optimize process parameters under competing quality requirements such as maximizing the dimple height while minimizing the dimple lower surface area

    Optimization of Activated Tungsten Inert Gas welding process parameters using heat transfer search algorithm: with experimental validation using case studies

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    The Activated Tungsten Inert Gas welding (A-TIG) technique is characterized by its capability to impart enhanced penetration in single pass welding. Weld bead shape achieved by A-TIG welding has a major part in deciding the final quality of the weld. Various machining variables influence the weld bead shape and hence an optimum combination of machining variables is of utmost importance. The current study has reported the optimization of machining variables of A-TIG welding technique by integrating Response Surface Methodology (RSM) with an innovative Heat Transfer Search (HTS) optimization algorithm, particularly for attaining full penetration in 6 mm thick carbon steels. Welding current, length of the arc and torch travel speed were selected as input process parameters, whereas penetration depth, depth-to-width ratio, heat input and width of the heat-affected zone were considered as output variables for the investigations. Using the experimental data, statistical models were generated for the response characteristics. Four different case studies, simulating the real-time fabrication problem, were considered and the optimization was carried out using HTS. Validation tests were also carried out for these case studies and 3D surface plots were generated to confirm the effectiveness of the HTS algorithm. It was found that the HTS algorithm effectively optimized the process parameters and negligible errors were observed when predicted and experimental values compared. HTS algorithm is a parameter-less optimization technique and hence it is easy to implement with higher effectiveness

    Design of experiments applied to lithium-ion batteries : a literature review

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    The statistical design of experiments methodology (DoE) has been a valuable tool since its conception for the understanding of the relationship between factors and responses. Although it has been employed successfully in different research fields and industries for years, its application to the evaluation of lithium-ion batteries (LIBs) is just getting recognition. LIBs are one of the most promising technologies for a complete transition to sustainable energies, are the main technology behind electric vehicles and are fundamental for the continual development of portable electronic devices. This paper presents a critical literature review of the available DoE works applied to the manufacturing and characterisation of LIBs. An overview of DoE and the most important available designs are first presented, followed by a general introduction of the statistical analysis required for the interpretation of the results including regression models. Several aspects of the LIBs such as ageing, capacity, electrode formulation, active material synthesis, thermal design, charging and parameterisation are discussed based on the main objective of the respective DoE studies found in the literature. A case study is presented to visualise the practical application of DoE to the LIBs field. Perspectives and future outlook are given to highlight opportunities and potential areas of research in the application of traditional and modern designs to the LIB’s field. This critical review contributes to a better understanding of the DoE methodology with a focus on LIBs or LIBs related aspects which will lead to faster developments in the field

    Development of a multi-objective optimization algorithm based on lichtenberg figures

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    This doctoral dissertation presents the most important concepts of multi-objective optimization and a systematic review of the most cited articles in the last years of this subject in mechanical engineering. The State of the Art shows a trend towards the use of metaheuristics and the use of a posteriori decision-making techniques to solve engineering problems. This fact increases the demand for algorithms, which compete to deliver the most accurate answers at the lowest possible computational cost. In this context, a new hybrid multi-objective metaheuristic inspired by lightning and Linchtenberg Figures is proposed. The Multi-objective Lichtenberg Algorithm (MOLA) is tested using complex test functions and explicit contrainted engineering problems and compared with other metaheuristics. MOLA outperformed the most used algorithms in the literature: NSGA-II, MOPSO, MOEA/D, MOGWO, and MOGOA. After initial validation, it was applied to two complex and impossible to be analytically evaluated problems. The first was a design case: the multi-objective optimization of CFRP isogrid tubes using the finite element method. The optimizations were made considering two methodologies: i) using a metamodel, and ii) the finite element updating. The last proved to be the best methodology, finding solutions that reduced at least 45.69% of the mass, 18.4% of the instability coefficient, 61.76% of the Tsai-Wu failure index and increased by at least 52.57% the natural frequency. In the second application, MOLA was internally modified and associated with feature selection techniques to become the Multi-objective Sensor Selection and Placement Optimization based on the Lichtenberg Algorithm (MOSSPOLA), an unprecedented Sensor Placement Optimization (SPO) algorithm that maximizes the acquired modal response and minimizes the number of sensors for any structure. Although this is a structural health monitoring principle, it has never been done before. MOSSPOLA was applied to a real helicopter’s main rotor blade using the 7 best-known metrics in SPO. Pareto fronts and sensor configurations were unprecedentedly generated and compared. Better sensor distributions were associated with higher hypervolume and the algorithm found a sensor configuration for each sensor number and metric, including one with 100% accuracy in identifying delamination considering triaxial modal displacements, minimum number of sensors, and noise for all blade sections.Esta tese de doutorado traz os conceitos mais importantes de otimização multi-objetivo e uma revisão sistemática dos artigos mais citados nos últimos anos deste tema em engenharia mecânica. O estado da arte mostra uma tendência no uso de meta-heurísticas e de técnicas de tomada de decisão a posteriori para resolver problemas de engenharia. Este fato aumenta a demanda sobre os algoritmos, que competem para entregar respostas mais precisas com o menor custo computacional possível. Nesse contexto, é proposta uma nova meta-heurística híbrida multi-objetivo inspirada em raios e Figuras de Lichtenberg. O Algoritmo de Lichtenberg Multi-objetivo (MOLA) é testado e comparado com outras metaheurísticas usando funções de teste complexas e problemas restritos e explícitos de engenharia. Ele superou os algoritmos mais utilizados na literatura: NSGA-II, MOPSO, MOEA/D, MOGWO e MOGOA. Após validação, foi aplicado em dois problemas complexos e impossíveis de serem analiticamente otimizados. O primeiro foi um caso de projeto: otimização multi-objetivo de tubos isogrid CFRP usando o método dos elementos finitos. As otimizações foram feitas considerando duas metodologias: i) usando um meta-modelo, e ii) atualização por elementos finitos. A última provou ser a melhor metodologia, encontrando soluções que reduziram pelo menos 45,69% da massa, 18,4% do coeficiente de instabilidade, 61,76% do TW e aumentaram em pelo menos 52,57% a frequência natural. Na segunda aplicação, MOLA foi modificado internamente e associado a técnicas de feature selection para se tornar o Seleção e Alocação ótima de Sensores Multi-objetivo baseado no Algoritmo de Lichtenberg (MOSSPOLA), um algoritmo inédito de Otimização de Posicionamento de Sensores (SPO) que maximiza a resposta modal adquirida e minimiza o número de sensores para qualquer estrutura. Embora isto seja um princípio de Monitoramento da Saúde Estrutural, nunca foi feito antes. O MOSSPOLA foi aplicado na pá do rotor principal de um helicóptero real usando as 7 métricas mais conhecidas em SPO. Frentes de Pareto e configurações de sensores foram ineditamente geradas e comparadas. Melhores distribuições de sensores foram associadas a um alto hipervolume e o algoritmo encontrou uma configuração de sensor para cada número de sensores e métrica, incluindo uma com 100% de precisão na identificação de delaminação considerando deslocamentos modais triaxiais, número mínimo de sensores e ruído para todas as seções da lâmina

    Data Analysis and Modeling Techniques of Welding Processes: The State-of-the-Art

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    Information contributes to the improvement of decision-making, process improvement, error detection, and prevention. The new requirements of the coming Industry 4.0 will make these new information technologies help in the improvement and decision-making of industrial processes. In case of the welding processes, several techniques have been used. Welding processes can be analyzed as a stochastic system with several inputs and outputs. This allows a study with a data analysis perspective. Data mining processes, machine learning, deep learning, and reinforcement learning techniques have had good results in the analysis and control of systems as complex as the welding process. The increase of information acquisition and information quality by sensors developed at present, allows a large volume of data that benefits the analysis of these techniques. This research aims to make a bibliographic analysis of the techniques used in the welding area, the advantages that these new techniques can provide, and how some researchers are already using them. The chapter is organized according to some stages of the data mining process. This was defined with the objective of highlighting evolution and potential for each stage for welding processes
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