Forming-based geometric correction methods for thin-walled metallic components:a selective review

Geometric correction processes contribute to zero-defect manufacturing for improved product quality. Thin-walled metallic components are widely used in numerous applications such as electric vehicles and aircraft due to the lightweight feature, facilitating to achieve zero-emission goals. However, many components suffer geometric imperfections and inaccuracies such as undesired curvatures and twists, seriously affecting subsequent manufacturing operations, for example, automatic welding and assembly. Geometric correction techniques have been established to address these issues, but they have drawn little attention in the scientific community despite their wide applications and urgent demands in the industry. Due to the strict geometric tolerances demanded in high-volume automated production, it is urgent to increase the knowledge needed to develop new techniques to address future industrial challenges. This review paper presents an overview of typical geometric defects in thin-walled components and clarifies the associated underlying generation mechanisms. Attempts have also been made to discuss and categorize geometric correction techniques based on different forming mechanisms. The challenges in correcting complex thin-walled products are discussed. This review paper also provides researchers and engineers with directions to find and select appropriate geometric correction methods to achieve high geometric accuracy for thin-walled metallic components.</p

Aluminum Alloys Behavior during Forming

Industrial revolution toward weight reduction and fuel efficiency of the automotive and aerospace vehicles is the major concern to replace heavy metals with light weight metals without affecting much strength. For this, aluminum alloys are the major contributors to those industries. Moreover, aluminum alloys are majorly categorized as 1xxx, 2xxx, 3xxx, 4xxx, 5xxx, 6xxx, 7xxx, and 8xxx based on major alloying elements. Among all, 2xxx, 5xxx, 6xxx, and 7xxx are having majority of applications in the abovementioned industries. For manufacturing any engineering deformable components, forming characteristics are must. Forming behavior of aluminum alloys has been evaluated through different processes including deep drawing, stretching, incremental forming, bending, hydro forming etc., under different process conditions (cold, warm, and hot conditions) and process parameters. Each process has its own process feasibility to evaluate the formability without any forming defects in products. The present chapter discusses a few important processes and their parameter effect on the aluminum alloys through the experimentations and simulation works

EXPERIMENTS AND ANALYSIS OF ALUMINUM TUBE HYDROFORMING

This is a thesis on the development of an experimental table-top sized tube hydroforming machine at the University of New Hampshire. This thesis documents the design of the machine and the exploration of the forming envelope of the device via finite element modeling of the forming process. Several experiments on Al-6061-T4 tubes were used to evaluate the plastic behavior and strain limits of the tube in the axial and circumferential (hoop) directions. Two of these material tests, the uniaxial tension test and the ring hoop tension tests, were simulated with finite element models to refine the Al-6061-T4 plasticity curve, including the extrapolation of the hardening curve beyond the point of ultimate tensile stress. 2D and 3D finite element models of the hydroforming process were also used to evaluate potential tube materials, outer diameters, and wall-thickness for future experiments and research efforts

Generation and quality control of lipidomics data for the alzheimers disease neuroimaging initiative cohort.

Alzheimers disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/

Simulation of Pipe Hydroforming

The importance of investigating the formation of a torsion beam and understanding how it can be manipulated to perform at an optimum condition is crucial to car manufacturers. Developing and remodelling the torsion beam can allow both a simpler structure and quicker assembly while reducing the space required for a car suspension’s system, thus saving time and costs for manufacturers. Nowadays, the use of hydroforming technology has become widespread because it is able to obtain complex hollow parts more easily and has been continually developed to become a globally applied technology in the formation of a torsion beam of a vehicle. With regards to the current issues in academic research and real-world production, this research uses a finite element analysis (FEA) method-based software tool DYNAFORM, to simulate the pipe hydroforming process in order to show the overall manufacturing process, thus providing a precise FEA simulation model of a torsion beam suspension for the automotive manufacturing. This will also provide a math model (a regression equation) for further research and the further application of this technology in the future