Experimental Investigation on Solid State Resistance Spot Welding

Resistance Spot Welding (RSW) is one of the most common and dominant technologies utilized in the automotive industry to join the thin sheet metals together, and expulsion is a common phenomenon during the operation. How to ensure the high quality nugget formation and joining performance is essential to ensure the quality and integrity of structures. In this study, solid state resistance spot welding is introduced in order to prevent expulsion. The effect of welding current and welding time on the mechanical performance of the solid state RSW in terms of nugget size, tensile performance and nugget formation will be investigated experimentally by using steel sheet metals. Microstructure and micro-hardness of the nugget cross-section will be evaluated as well.

Springback Analysis in Bilayer Material Bending

Exponential increase in the use of auto vehicles, and thus the fuel consumption, which relates to the air pollution, vehicle industry are in a strict environmental regulation from government. Due to which the innovation related to light-weighting is not only an option anymore but became a mandatory necessity to decrease the fuel consumption. To achieve this target, industry has been looking in fabricating components from high strength to ultra-high strength steels. With the usage of these material the lightweight was achieved by reducing a gage thickness. However due to their high strength property often challenges occurred are higher machine tonnage requirement, sudden fracture, geometric defect, etc. The geometric defect comes from elastic recovery of a material, which is also known as a springback. Springback is commonly known as a manufacturing defect due to the geometric error in the part, which would not be able to fit in the assembly without secondary operation or compensation in the forming process. Due to these many challenges, other research route involved is composite material, where light materials can be used with high strength material to reduce the overall vehicle weight. This generally includes, tailor welded blanks, multi-layer material, mechanical joining of dissimilar material, etc. Due to the substantial use of dissimilar materials, these parts are also called as hybrid components. It was noted that the part weight decreases with the use of hybrid components without compromising the integrity and safety. In this paper, a springback analysis was performed considering bilayer metal. For this two dissimilar materials aluminum and composite was considered as bonded material. This material was then bent in a channel forming set-up. The bilayer springback was compared in different condition like aluminum layer on punch side and then on die side. These results were then compared with the baseline springback of only aluminum thin and thick layer. It was found that the layer, which sees the punch side, matters due to the differences in elastic properties for both material and thus it directly influences the springback.

Comparison of Different Sensitivity Analysis Methods in the Context of Dimensional Management

Although mass production parts look the same, every manufactured part is unique, at least on a closer inspection. The reason for this is that every manufactured part is inevitable subjected to different scattering influencing factors and variation in the manufacturing process, such as varying temperatures or tool wear. All these factors inevitably lead to parts, which deviate from their ideal shape. Products, which are built from these deviation-afflicted parts consequently show deviations from their ideal properties. To ensure that every single product nevertheless meets its technical requirements, it is necessary to specify the permitted deviations. Furthermore it is necessary to estimate the consequences of the permitted deviations, which is done via tolerance analysis. During this process the imperfect parts are assembled virtually and the effects of the geometric deviations can be calculated during a variation simulation. Since the tolerance analysis is to enable engineers to identify weak points in an early design stage it is important to know which contribution every single tolerance has on a certain quality-relevant characteristic, to restrict or increase the correct tolerances. In this paper two different approaches are shown and compared to represent the statistical behavior and the strongly connected sensitivity analyses. In particular a newly developed approach, which is based on fuzzy arithmetic, is compared to the established EFAST-method. The exemplary application of both methods and the comparison of the results are illustrated on a case study.

Process Parameter Optimization of Friction Crush Welding (FCW) of AISI 304 Stainless Steel

AISI 304 stainless steel is one of the grades of steel widely used in engineering applications particularly in chemical equipments, food processing, pressure vessels and paper industry. Friction crush welding (FCW) is type of friction welding, where there is a relative motion between the tool and work-piece. In FCW process, the edges of the work-piece to be joined are prepared with flanged edges and then placed against each other. A non-consumable friction disc tool will transverse with a constant feed rate along the edges of the work-piece, which leads to welding. The joint is formed by the action of crushing a certain amount of additional flanged material into the gap formed by the contacting material. The novelty of present work is that FCW removes the limitations of friction stir welding and Steel work pieces can be economically welded by FCW. Taguchi method of Design of Experiments (DOE) is used to find optimal process parameters of Friction Crush Welding (FCW). A L9 Orthogonal Array, Signal to Noise ratio (S/N) and Analysis of Variance are applied to analyze the effect of welding parameters (welding speed, RPM, tool profile) on the weld properties like bond strength. Grain refinement takes place in friction crush welding as is seen in friction stir welding. Friction crush welding process also has added advantage in reducing distortion and residual stresses.

Effect of Temperature on the Evolved Microstructure During Laser Beam Forming of Sheet Steels

Laser Beam Forming (LBF) being a novel technique and non-contact manufacturing process, employs laser beam as the tool of shaping and bending metal sheets into different shapes and curvatures for various applications. LBF is a high-temperature process, where rapid heating and cooling occurs causing microstructural changes like dynamic recrystallization and phase changes. The study becomes necessary to ensure that the structural integrity of the processed material is not compromised. Hence, the investigation focuses on the effect of temperature on the developed microstructure during the LBF process. The design of experiment was considered, using three levels and five factors. The experimentally measured curvatures were validated with the predicted measured curvatures, which were found to be in agreement. The result shows that the developed ferrite and pearlite grains were due to the heating and cooling. Furthermore, the average grain sizes at a low energy density of about 355°C and high energy density of about 747°C were found to be about 10 μm and 6 μm respectively. It is implied that the high temperature from the high laser energy aided the deformation of the grains significantly. However, such high temperature must be closely monitored so to avoid metallurgical notches in the processed component.

An Analysis Model to Predict Rotation Accuracy of High-Precision Spindles Considering Part Errors and Deformation

High-precision spindles have significant influence on the machining precision and finishing quality largely due to their motion errors. However, the analysis of rotation accuracy is quite not easy in design stage because of the neglecting of geometric errors and deformations of parts in the traditional dimension chains. Hence, a theoretical analysis model is built in present study to do the prediction. The 3D error accumulation path is recognized by Datum Flow Chain (DFC) and the key tolerances are modeled by Small Displacement Torsor (SDT). Thereafter, the variation propagation is conducted by Homogeneous Transformation Matrices (HTM) and the geometric misalignment in the spindle is calculated. Then, an FEA model is built with Timoshenko beam elements and the deformation is calculated after the geometric misalignment is applied to the model. As spindle rotates, the trajectory of the spindle nose is obtained. Finally, the Monte Carlo (MC) method is used to get the distribution and the range of motion errors. To verify the feasibility and reliability of the analysis model, the radial and axial motion errors of a double supported high-precision spindle are analyzed.

A Numerical Study on the Redistribution of Residual Stress After Machining

Machining induced residual stresses have an important effect on the surface integrity. Effects of various factors on the distribution of residual stress profiles induced by different machining processes have been investigated by many researchers. However, the initial residual, as one of the important factor that affect the residual stress profile, is always been ignored. In this paper, the residual stress field induced by the quenching process is simulated by the FEM software as the initial condition. Then the initial residual stress field is used to study the residual stress redistribution after the machining process. The influence of initial stress on the stress formation is carried out illustrating with the mechanical and thermal loads during machining processes. The effects of cutting speed on the distribution of residual stress profile are also discussed. These results are helpful to understand how initial residual stresses are redistributed during machining better. Furthermore, the results in the numerical study can be used to explain the machining distortion problem caused by residual stress in the further work.

Validation of a Methodology to Implement Lean Production in Textile and Clothing Industry

Lean Production is considered a management methodology that has been implemented in many industries and services. Nevertheless, Lean experts know that this is not only a management methodology; it is more a philosophy and a new way of life. This is the reason why it is difficult to implement but, even worst, to be successful and to be sustainable. A continuous effort of improvement must always be kept in mind. Attending to these factors, it is important to have a methodology that helps to implement Lean Production effectively. This methodology could be different from industry to industry in order to model the differences between them and, most important, to assure its sustainability. This paper presents the validation of one such methodology for the Textile and Clothing Industry (TCI), based on three case studies (three Textile and Clothing companies located in North of Portugal). To validate it, different field procedures instruments such as interviews, questionnaires, and checklists were used. With these instruments, some validation results of the methodology were obtained, mainly, related with the diagnosis phase of Lean implementation. Results of two case studies were published in previous papers, being the results of a third case presented in this paper. Also, an analysis and discussion of the three case studies results, regarding their attitudes and difficulties are presented.

Characterization of 3D Surface Texture Directionality Using Multi-Scale Curvature Tensor Analysis

Anisotropy of surface texture can in many practical cases significantly affect the interaction between the surface and phenomena that influence or are influenced by the topography. Tribological contacts in sheet forming, wetting behavior or dental wear are good examples. This article introduces and exemplifies a method for quantification and visualization of anisotropy using the newly developed 3D multi-scale curvature tensor analysis. Examples of a milled steel surface, which exhibited an evident anisotropy, and a ruby contact probe surface, which was the example of isotropic surface, were measured by the confocal microscope. They were presented in the paper to support the proposed approach. In the method, the curvature tensor T is calculated using three proximate unit vectors normal to the surface. The multi-scale effect is achieved by changing the size of the sampling interval for the estimation of the normals. Normals are estimated from regular meshes by applying a covariance matrix method. Estimation of curvature tensor allows determination of two directions around which surface bends the most and the least (principal directions) and the bending radii (principal curvatures). The direction of the normal plane, where the curvature took its maximum, could be plotted for each analyzed region and scale. In addition, 2D and 3D distribution graphs could be provided to visualize anisotropic or isotropic characteristics. This helps to determine the dominant texture direction or directions for each scale. In contrast to commonly used surface isotropy/anisotropy determination techniques such as Fourier transform or autocorrelation, the presented method provides the analysis in 3D and for every region at each scale. Thus, different aspects of the studied surfaces could clearly be seen at different scales.

Thermal Modeling of 304L Stainless Steel for Selective Laser Melting: Laser Power Input Evaluation

Selective Laser Melting (SLM) process is a Powder Bed Fusion (PBF) technique, which has shown significantly growth in the recent years. The demand for this process is justified by the versatility and ease in manufacturing the parts from 3D models as well for the increased complexity of engineered parts generated from topology or shape optimization. Automotive, aerospace, medical and aviation industries are taking great advantage of this process due the unique geometry characteristics found in the components. To enhance the benefits of SLM, a vital task is to analyze the laser power input impact on the temperature distribution through the powder bed, important for posterior residual stresses analysis. The Finite Element Method proposed in this study is a transient thermal model, able to predict temperature distribution through different sections of the powder bed when performing a single track of the laser scanning. Furthermore, the impact of the laser power input is carried out utilizing SS 304L, a low cost Stainless Steel alloy that can be employed in the SLM process, in order to determine the influence on the temperature distribution along the different cross sections.