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All Journal Mechatronics, Electrical Power, and Vehicular Technology International Journal of Advances in Data and Information Systems Jurnal Polimesin Spektrum Industri
Tho, Nguyen Huu
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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An experimental investigation of an energy regeneration suspension Tho, Nguyen Huu; Danh, Le Thanh
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.811

Abstract

Energy absorbed from road bumps in traditional suspensions is dissipated as heat. An energy regeneration suspension (ERS) has the capability to capture and store this energy in batteries. It has the potential to be used in several categories of vehicles, encompassing cars, trucks, buses, and even trains. ERS technology shows significant promise in enhancing the fuel efficiency and environmental sustainability of vehicles. In this paper, the design of an ERS that converts kinetic energy into electrical energy is presented. The primary objective is to identify key design parameters that result in high magnetic intensity levels in the air gap of the ERS model. Optimizing these parameters is essential to maximize the advantages of ERS while minimizing any drawbacks. The study investigates the impact of different magnetic permeability materials in the ERS model using ANSYS software. A test rig is established based on the analysis results to assess the energy regeneration efficiency of the ERS model under various excitations. Experimental results demonstrate that ERS models with higher permeability inner sleeves exhibit superior energy regeneration efficiency.
Comparative Evaluation of Convolutional Neural Network Full Learning Model with Transfer Learning (VGG-16) for Coffee Bean Roasting Level Classification Tama, Mradipta Nindya; Saptomo, Amanat Bintang; Afrido; Baroroh, Dawi Karomati; Rifai, Achmad Pratama; Tho, Nguyen Huu
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1358

Abstract

Indonesia is the 3rd largest coffee producing country in the world in 2022-2023 with coffee production reaching 11.85 million bags per 60 kg of coffee. One of the important processes in coffee production is roasting because the roasting level of coffee beans can affect the taste and aroma of coffee. The problem faced is that the process of assessing the level of coffee roasting is traditionally carried out through visual observation by an expert (roaster). This method produces a subjective level of assessment and requires high skills and experience, making the assessment of the level of coffee roasting less efficient and prone to human error. Therefore, in this study the author aims to develop a Convolutional Neural Network (CNN) model for the classification of the level of coffee bean roasting that can achieve better and faster accuracy. In this study, the author compared two CNN architecture approaches for the classification of the level of coffee bean roasting. The first approach is full learning with an architecture consisting of three convolution layers. The second approach is transfer learning based on the VGG-16 model. From the results of the analysis, it is known that the full learning model has a better level of accuracy and a faster running time than the VGG-16 transfer learning. The CNN full learning model for coffee bean roasting level classification is able to classify the coffee bean roasting level, with an accuracy of 98.75% and a running time of 856 ms per step. The application of CNN for coffee roasting level classification can provide benefits such as improving quality control and reducing the level of subjectivity of a roaster in assessing the roasting level of coffee beans.
Effect of welding repair on mechanical properties of ASTM A36 carbon steel weld joints Azwinur, Azwinur; Syukran, Syukran; Akhyar, Akhyar; Tho, Nguyen Huu; Jaswir, Jaswir
Jurnal Polimesin Vol 20, No 2 (2022): August
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v20i2.3075

Abstract

The welding repair process greatly affects the procedure of a welding process to be able to obtain the results of a connection that is safe and in accordance with its provisions. The strength of the welded joint must be considered and ensured that its strength is at least close to the original strength of the material used. In a welding process, errors or omissions are often made accidentally by the welder or the work environment and the selection of welding variable parameters is not appropriate so that welding defects occur. Welding defects can affect the strength of the weld joint. The purpose of this study was to determine the effect of welding repair on the mechanical properties of ASTM A36 material. The material used in conducting this research and testing is ASTM A36 steel plate. Welding was carried out on 4 specimens with the method without repair, repair 1x, repair 2x and repair 3x. Based on the test results, the number of repairs greatly affects the strength of the material connection. The highest maximum tensile strength value in 1 repair specimen is 501.90 Mpa and the lowest is in unwelded material or base metal of 467.97 Mpa. The results of the highest hardness test on the repair material 1 time of 30.83 HRC in the weld metal area and the lowest hardness value on the repair specimen 3 times in the HAZ area of 21 HRC. The results of the macro photo test on each specimen did not detect any welding defects on the inside of the welded material. the largest HAZ width in the 3 times repair material is 21.5 mm and the smallest HAZ width in the specimen without repair is 18 mm
Facility Layout Planning of Sheet Metal Working Industry Using Metaheuristics Ludwika, Adinda Sekar; Shalehah, Mar’atus; Mohamad, Rakan Raihan Ali; Oktavia, Andiny Trie; Normasari, Nur Mayke Eka; Tho, Nguyen Huu; Rifai, Achmad Pratama
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.141

Abstract

The design of facility layout in a production floor determines the level of effectiveness and efficiency of the production process. Errors in arranging the layout in the production floor can disrupt the continuity of the production process and prevent optimal results. Production activities that occur over a long period of time make any inaccuracies in layout planning result in significant losses. In companies with Job Shop production type, which is characterized by identical products and varied processes, the production flow changes with each product made. Based on these issues, this research aims to optimize the layout in a company engaged in sheet metal working industry using metaheuristic algorithms such as Simulated Annealing (SA), Large Neighborhood Search (LNS), Adaptive Large Neighborhood Search (ALNS), and Ant Colony Optimization (ACO). The best total distance results were obtained by the SA, LNS, and ALNS algorithms, with a total travelled distance of 897,171 meters and a facility arrangement of 7-5-6-4-3-2-1 or 1-2-3-4-6-5-7. Additionally, considering computation time, the SA algorithm is the best choice as it has the fastest computation time compared to other algorithms.
Co-Authors Achmad Pratama Rifai Afrido Akhyar Akhyar Azwinur Azwinur Danh, Le Thanh Dawi Karomati Baroroh Jaswir, Jaswir Ludwika, Adinda Sekar Mohamad, Rakan Raihan Ali Nur Mayke Eka Normasari Oktavia, Andiny Trie Saptomo, Amanat Bintang Shalehah, Mar’atus Syukran Syukran Tama, Mradipta Nindya