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A complete analysis of the wear profiles of brake discs on commuter trains was carried out to evaluate their performance based on the rate of wear on the wheels. Actual data on the thickness and wear height of the discs were obtained at different mileages using a laser measurement device. The data were plotted to analyse the relationship between the wear and position of the brake discs at different axles. The wear rate of the discs was established to investigate the wear pattern. It was observed that the wear of the discs increased with decreasing thickness of the wear material and increasing wear height. The different positions of the discs also produced different wear profiles. The discs at the front and rear axles, experienced significant wear compared to the ones at the centre axle. The wear rate of the discs on the transit commuter rail (TCR) was higher than on the express commuter rail (ECR). This was due to the number of stops made on each trip, where the TCR stops at six stations unlike the ECR, which stops only at three stations. The higher the number of stops, the higher the frequency at which the brake discs have to be applied to stop the commuter train; thereby resulting in higher wear. Nevertheless, at certain locations along the tracks, usually where the tracks curve, the commuter trains are required to operate at a slow speed

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This work is focusing on fused deposition modelling (FDM) 3D printing; this process principle is making the sample by adding melted materials for each layer. Therefore, this process has several advantages that can solve many manufacturing problems by the control of remodelling the output sample by setting the printing parameters such as printing temperature, speed, infill percentage and layer height. Finding the suitable setting parameters for the output sample can be a great challenge for the user, which can affect the mechanical characteristics of the produced printed sample. This paper examines the impacts of the printing angles and orientation on the mechanical characteristics of the acid of polylactic (PLA) and the particles of carbon in the output sample. To calculate this influence, a 3D printed sample for tensile strength and charpy was made at 0○, - 45○, /+45º, 60° and 90º. The orientation was different but, the other of the factors hold constant such as infill density and layer height. Four different results were analysed for the impact resistance of these tests.

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The concept of repair and restoration using additive manufacturing (AM) is to build new metal layers on a broken part. It is beneficial for complex parts that are no longer available in the market. Optimization methods are used to solve product design problems to produce efficient and highly sustainable products. Design optimization can improve the design of parts to improve the efficiency of the repair and restoration process using additive manufacturing during the end-of-life (EoL) phase. In this paper, the objective is to review the strategies for remanufacturing and restoration of products during or at the EoL phase and facilitate the process using AM. Design optimization for remanufacturing is important to reduce repair and restoration time. This review paper focuses on the main challenges and constraints of AM for repair and restoration. Various AI techniques, including the hybrid method that can be integrated into the design of AM, are analyzed and presented. This paper highlights the research gap and provides recommendations for future research directions. In conclusion, the combination of artificial neural network (ANN) algorithms with genetic algorithms as a hybrid method is a key solution in solving limitations and is the future for repair and restoration using additive manufacturing

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Abstract: The integration of artificial intelligence (AI) in additive manufacturing (AM) technology is currently a promising and leading area of research for component repair and restoration. The Issues of high cost and time consumption for AM repair have been a subject of discussion among researchers in this field of study. Moreover, the potential challenges in dealing with complex components for repair and restoration in the (AM) domain require the establishment of a critical technical platform based on hybrid (AI). At this point, the proposed optimization method must cover all important parameters for the complex configuration of structural components under restoration. For the purpose of this study, a design optimization framework was developed using a MATLAB-SIMULINK mathematical model for AM solution purposes by improving the functionality and integration of monitoring. This improvement is based on facilitating the real-time identification of failures with accuracy and giving a clear monitoring vision according to the intended targets like geometric distortions, residual stresses evaluation, and defect characterization. The improvement involves overcoming a number of challenges such as the pre-fabrication stage by expanding the data repository besides offering a theoretical set of algorithmic with some options that improve the current procedure. Also, this study will conclude and suggest a further framework and new knowledge for restoration and product life cycle extension. This developed ANN can be used at the real pace of modeling the MATLAB-Simulink system and merged with another suitable algorithm to form a hybrid ANN. This model development using a neural network has attained a good manipulation of AM. The predicted data from ANN model that was determined and achieved in this study can be used to facilitate and enhance any further study as base knowledge in merging the ANN with another AI to form a hybrid algorithm.

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Additive manufacturing (AM) is an effective technology for repairing and restoring automotive components. However, the effectiveness of additive manufacturing technology in repair and restoration is highly influenced by several factors related to components and process. The objective of this paper is to improve the decision-making in repair and restoration of a turbocharger with AM. In this article, a Fuzzy-Genetic approach was presented as a decision-making tool for repairing a remanufacturable component. Fuzzy logic (FL) is deployed as the method to model the design parameters of a turbocharger, such as design complexity, failure mode, damage size, disassembleability, preprocessing, temperature, durability, pressure ratio and mass flow rate to model the relationship between the inputs and outputs using Mamdani model with their membership functions. Genetic algorithm optimization method was used to optimize the cost of the repairing process once the decision on whether the turbocharger was repairable was determined by the Fuzzy system. The FL approach applied rules affecting the process, the robustness and accuracy of the model increases with a higher number of rules. The work focuses on the dataset related to design information, which represents as a knowledge base for decision parameters on design optimization to automate repair process during remanufacturing. The results showed the effects of the design parameters on repairing and replacement decisions, and how the fuzzy model related the inputs to the outputs based on the generated rules. In conclusion, FGA method can be used to improve the repair and restoration process of a turbocharger through AM technology.

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The high frequency of operation of commuter trains, due to passenger demand as well as the selection of railway as the mode of daily transportation for commuting on weekdays, increases the usage of on-board power, especially for a train’s traction system. As maintenance is rarely performed on transformer oil, it deteriorates and negatively affects transformer performance, increases heat, and may damage the transformer as well. This will result in significantly costly maintenance expenses for train operators. Therefore, this paper proposes a predictive maintenance schedule for transformer oil. The recommendations are based upon an analysis of transformer oil contents and its properties over a 90-month period of operation. A linear correlation between the properties of the oil and the train’s period of operation yielded a predictive maintenance schedule, primarily reclamation and filtration, for the oil at the threshold of each property. Major oil changes are to be considered when all properties are approaching their thresholds. As oil deterioration increases over time, a specific maintenance schedule was suggested. This was tested and observed on several transformer units. The content analysis of each oil is also discussed. Based on the results, this predictive maintenance schedule can be used on other trains with the same transformer model or other trains using the same type of insulating oil.

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A turbocharger performance of exhaust gas turbine on the diesel engines are studied the turbine driven compressor that is used for increasing air flow rate into internal combustion engine the angle of Blade effect on the flow field of turbine wheel. Angle of Blade of turbine wheel analyzed Based on the theory Computational Fluid Dynamics (CFD). How the various blade angle of turbine wheel due to optimization on flow field along the blade and leads to optimization in the pressure and velocity. Blade angle studied is conducted for understand the flow behavior in order to minimize the effects blade angle. in this paper dealing The Analyses the flow field along the blade passage of the turbine wheel for the turbocharger and study the effect flow field at different blade angle for turbine wheel outlet blade angle, β = 650, 450 and 350.

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The design of high performance aircraft structures frequently includes various shape and size discontinuities for various purposes. The zones near to these notches become critical regions under various working loading. The stress concentration factor (SCF) and tensile strength degradation of poly lactic acid (PLA) plates are addressed in the current study through a combination of experimental and numerical studies using finite element (FE) modeling techniques. The present work performs stress concentration factor (SCF) of rectangular plates with two symmetrical circular holes under uniaxial tension load of two various types (PLA, PLA/15%carbon), which were determined in the current work experimentally and numerically using finite element method with help of Ansys software. The results of experimental test showed decay in tensile modulus and tensile strength is less than that of using plates without holes by (10%, 22.1%) for (PLA, PLA/15%carbon) respectively, and the apparent stress concentration factor is (3.33, 3.61) respectively. And showed decay in tensile strength is less than that of using plates without holes by (28.35%, 27.77%) for (PLA, PLA/15%carbon) respectively, due to the concentration of stresses around the holes. A finite element analysis is carried out and the outcomes have been estimated with experimental results for checking the efficient use of this article. The numerical results show the Von Mises stress distribution and stress concentration factor is (2.16, 2.35) for (PLA, PLA/15%carbon) respectively