Multi-Objective Parametric Optimization of Weld Strength of Metal Inert Gas (MIG) Welding by using Analysis of Variance, Taguchi, and VIKOR Techniques

Welding is an enormously essential manufacturing technique which allows the users to create permanent joints efficiently, due to its durability this process is extensively used in various industries like automotive, construction as well as in the aviation industry. The present study focuses on the optimization of the Metal Arc Welding using VIKOR method. Four input variables Current, Voltage, Wire Feed Rate and Gas Flow Rate are considered to study their effect on three responses tensile, bending and hardness on the weldments of AISI 1008 low carbon steel material. Experiments were planned as per Taguchi‘s L9 OA. As traditional Taguchi method is not adequate to solve multi responses problem, to overcome this limitation MCDM approach VIKOR analysis has been carried out for obtaining optimal parameters setting for multi-response optimization. Three specimens (for tensile, bending, and hardness) for each experimental run are fabricated for the measurement of respective strength and hardness. Investigation is done by following the steps of VIKOR method, and optimal parameter setting for multi quality response is obtained corresponding to the lower VIKOR index value. Keywords: Metal Inert Gas (MIG) Welding, VIKOR, S/N ratio, ANOVA

Dysbarism: An Overview of an Unusual Medical Emergency

Dysbarism is a general term which includes the signs and symptoms that can manifest when the body is subject to an increase or a decrease in the atmospheric pressure which occurs either at a rate or duration exceeding the capacity of the body to adapt safely. In the following review, we take dysbarisms into account for our analysis. Starting from the underlying physical laws, we will deal with the pathologies that can develop in the most frequently affected areas of the body, as the atmospheric pressure varies when acclimatization fails. Manifestations of dysbarism range from itching and minor pain to neurological symptoms, cardiac collapse, and death. Overall, four clinical pictures can occur: decompression illness, barotrauma, inert gas narcosis, and oxygen toxicity. We will then review the clinical manifestations and illustrate some hints of therapy. We will first introduce the two forms of decompression sickness. In the next part, we will review the barotrauma, compression, and decompression. The last three parts will be dedicated to gas embolism, inert gas narcosis, and oxygen toxicity. Such an approach is critical for the effective treatment of patients in a hostile environment, or treatment in the emergency room after exposure to extreme physical or environmental factors.

Real-time recognition of weld defects based on visible spectral image and machine learning

The quality of Tungsten Inert Gas welding is dependent on human supervision, which can’t suitable for automation. This study designed a model for assessing the tungsten inert gas welding quality with the potential of application in real-time. The model used the K-Nearest Neighborhood (KNN) algorithm, paired with images in the visible spectrum formed by high dynamic range camera. Firstly, projecting the image of weld defects in the training set into a two-dimensional space using multidimensional scaling (MDS), so similar weld defects was aggregated into blocks and distributed in hash, and among different weld defects has overlap. Secondly, establishing models including the KNN, CNN, SVM, CART and NB classification, to classify and recognize the weld defect images. The results show that the KNN model is the best, which has the recognition accuracy of 98%, and the average time of recognizing a single image of 33ms, and suitable for common hardware devices. It can be applied to the image recognition system of automatic welding robot to improve the intelligent level of welding robot.