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Jurnal Polimesin
Published by Politeknik Negeri Lhokseumawe
ISSN : 16935462     EISSN : 25491199     DOI : http://dx.doi.org/10.30811/jpl
Core Subject : Science, Engineering,
Automotive Engineering Control & Systems Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering
Polimesin mostly publishes studies in the core areas of mechanical engineering, such as energy conversion, machine and mechanism design, and manufacturing technology. As science and technology develop rapidly in combination with other disciplines such as electrical, Polimesin also adapts to new facts by accepting manuscripts in mechatronics. In Biomechanics, Mechanical study in musculoskeletal and bio-tissue has been widely recognized to help better life quality for disabled people and physical rehabilitation work. Such a wide range of Polimesin could be published, but it still has criteria to apply mechanical systems and principles. Exceeding the limitation has been a common reason for rejection by those outside the scope. Using chemical principles more than mechanical ones in material engineering has been a common reason for rejection after submission. Excessive exploration of the management within the discipline of Industrial Engineering in the manufacturing technology scope is also unacceptable. The sub-scope biomechanics that focuses on ergonomics and does not study movement involving applied force on the bio-tissue is also not suitable for submission.
Arjuna Subject : Teknik (semua kategori) - Teknik Mesin
Articles 553 Documents
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Multi-objective tribological and energy optimization of an automatic valve lapping machine using a hybrid RSM NSGA-II approach Setyawan, Reinaldi Teguh; Muthoriq, Ery; Syahrizal, Syahrizal
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.8454

Abstract

Optimizing valve seat reconditioning requires balancing sealing performance, surface integrity, energy consumption, and component wear within practical workshop constraints. This study presents the design, development, and multi-objective optimisation of a low-cost automatic valve lapping system using a hybrid Response Surface Methodology (RSM) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) framework. A prototype automatic valve lapping rig was developed by integrating a DC-motor-driven spindle with adjustable spring loading and an Arduino-based control and data-acquisition system, enabling controlled variation of spindle speed (300–600 rpm) and axial load (60–140 N). Leakage time, surface roughness (Ra), electrical energy consumption, and valve wear volume were measured using a three-level factorial design. Quadratic response surface models with satisfactory statistical adequacy were established for all responses. The RSM models were employed in NSGA-II to maximise leakage time and minimise surface roughness, energy consumption, and wear, subject to practical operational constraints. The optimisation results reveal clear trade-offs between sealing quality, energy efficiency, and component life, and identify an optimal operating window of approximately 430–470 rpm and 90–110 N, providing a robust compromise solution and a practical operating map for workshop valve seat reconditioning.
Effect of anode–cathode distance and anodizing time on hardcoat anodizing of AA7075 Endramawan, Tito; Haris, Emin; Rohmat, Yusup Nur; Irawan, Candra
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.6194

Abstract

Fishing activities in Indramayu ( a seaside city in West Java) typically use boats powered by propellers. These propellers often strike floating objects, resulting in damage such as cracked or broken blades. A survey revealed that the fractures are mainly caused by the poor quality of propellers produced using the gravity casting technique, which results in rough surfaces with pores and cracks that initiate during finishing. Therefore, surface repair is necessary, and one potential method is hardcoat anodizing. This study aims to investigate the effect of coating time and anode–cathode distance on the hardness of the oxide layer formed during the hardcoat anodizing process of AA7075 aluminum alloy. The anode–cathode distances were 5 cm, 10 cm, and 15 cm, with coating times of 40, 50, and 60 minutes. The process was conducted at 2 to 3°C, with a current of 5.12 A and a voltage of 31.5 V. The results of micro-Vickers hardness testing, conducted with a loading parameter of 200 gf and an indentation time of 15 seconds, indicated a hardness increase of 256% compared to the base material. The highest hardness value was achieved at a distance of 5 cm and a coating time of 60 minutes, measuring 322.9 VHN, with a resulting layer thickness of 67.16 µm.
Predictive modeling of surface roughness and resultant force in CNC turning of AISI H13 using optimized artificial neural networks Sunardi, Sunardi; Zain, Ananda Nur Daffa
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.7558

Abstract

Artificial Neural Networks (ANNs) have gained increasing attention as effective tools for modeling nonlinear and multivariate relationships in complex manufacturing processes, where conventional predictive approaches often exhibit limited accuracy. In this study, an ANN-based predictive framework was developed to estimate surface roughness (Ra) and resultant force (F) in CNC turning of hardened AISI H13 steel. The framework was constructed using an experimental dataset comprising 324 machining records, with cutting speed (vc), feed rate (f), and depth of cut (ap) as input parameters, all normalized using the Min-Max scaling method to ensure stable and efficient model training. To identify the optimal training configuration, eight optimization algorithms: Adam, RMSprop, Nadam, Adagrad, Adadelta, Adamax, FTRL, and Stochastic Gradient Descent (SGD) are systematically evaluated, and Nadam was selected as the most effective optimizer with a learning rate of 0.0001 and a batch size of 16. Two dedicated feed forward ANN models are designed separately for Ra and F prediction and validated using the Leave-One-Out Cross-Validation (LOOCV) technique to enhance generalization and minimize overfitting. The resulting models achieved excellent predictive accuracy for resultant force (R² = 0.9939, MAE = 4.3313 N, RMSE = 7.5955 N) and moderate accuracy for surface roughness (R² = 0.6454, MAE = 0.1440 µm, RMSE = 0.1960 µm). These results demonstrate that the proposed ANN-based framework provides a reliable decision-support tool for process optimization, monitoring, and surface quality control in high-performance machining environments.
Experimental Investigation Of MQL Turning Parameters On Surface Quality And Tool Wear Toward Green Machining Practices Gobel, E'ep Fadil Abdilah; Rismanto, Muhammad; Selleng, Kristian; Sirajuddin, Awal Syahrani; Iskandar, Iskandar; Asmara, Anjar
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.8327

Abstract

This study aims to determine the effect of spindle speed and air pressure on surface roughness and tool wear in the turning process of S45C steel using the Minimum Quantity Lubrication (MQL) system with used cooking oil as an environmentally friendly alternative cutting fluid. The spindle speed was varied at 800, 1000, and 1200 rpm, while the air pressure was set at 1, 2, and 3 bar. The experiments were carried out on a conventional lathe machine with controlled variables including the S45C workpiece material, a feed rate of 0.017 mm/rev, a depth of cut of 0.5 mm, and the use of a carbide insert tool. The dependent variables observed were surface roughness and tool wear. The results show that the application of the MQL system significantly reduced surface roughness and slowed down tool wear compared to dry cutting. The lowest surface roughness value was obtained at a spindle speed of 800 rpm and an air pressure of 2 bar under MQL conditions, while the highest tool wear occurred at 800 rpm and 1 bar without MQL. An air pressure of 2 bar provided the best balance between lubrication and cooling effects, maintaining the stability of the lubricant in the cutting zone. The combination of MQL at 2 bar air pressure and 800 rpm spindle speed proved effective in producing a smoother surface finish, extending tool life, and supporting green manufacturing practices through the utilization of used cooking oil as an eco-friendly alternative cutting fluid.
Structural strength analysis of a tourist minicar knuckle using finite element analysis Hanafi, Agung Fauzi; Umar, Mega Lazuardi; Prasetya Dharma Yudha, I Gusti Ngurah Agung Satria; Siregar, Ansor Salim
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.8194

Abstract

The design of components for vehicles used in tourist areas must be efficient, safe, and economical. The steering knuckle is a vital component in the vehicle's suspension and steering systems, playing a crucial role in transferring loads, connecting the wheel to the steering mechanism, and supporting braking components. This research aims to design, analyze, and fabricate a steering knuckle for a mini tourist car with a total mass of 300 kg using plain carbon steel. The design and strength analysis were evaluated using the open-source Finite Element Analysis (FEA) software PrePoMax to investigate stress distribution, deformation, and the factor of safety. The FEA results showed a maximum Von Mises stress of 86.27 MPa, well below the material's yield strength, a maximum deformation of 0.126 mm, and a minimum safety factor of 2.72, confirming a robust design. The component was designed to accommodate a 30204 tapered roller bearing. The fabrication process, encompassing cutting, machining, and welding, successfully produced a functional prototype validated through direct installation and load testing on the vehicle. This study confirms that plain carbon steel is a reliable and economical material for structural components in lightweight vehicle applications and provides a pragmatic engineering framework for developing cost-effective automotive components.
Experimental study on the effect of coal composition on the activation energy of sponge iron reduction Sabuki, Sabuki; Khairil, Khairil; Sofyan, Sarwo Edhy
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.7540

Abstract

The increasing demand for steel in Indonesia necessitates the development of efficient and sustainable ironmaking technologies. Direct reduction has emerged as a promising alternative to conventional blast furnace processes due to its lower operating temperature and reduced carbon emissions. This study examines the effect of coal composition on the reduction kinetics and activation energy of iron ore briquettes produced from locally sourced raw materials. Briquettes were prepared using Lhoong iron ore (93.88 wt% Fe2O3), sub-bituminous coal from Nagan Raya, and natural rubber latex as a binder. Four composition ratios were investigated: 80:15:5, 75:20:5, 70:25:5, and 60:35:5 (iron ore:coal:binder), each with a total mass of 60 g. Reduction experiments were conducted at 800 °C, 900 °C, and 1000 °C in an LPG-fired furnace. Mass loss was continuously monitored at 2-minute intervals using a digital balance connected to data acquisition software.
Effectiveness of TiO2-coated stainless steel mesh reactor with UV-LED on the reduction of cigarette smoke pollutants in a closed room Dewi, Renita; Adhi, Pribadi Mumpuni; Nufus, Tatun Hayatun
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.7586

Abstract

Indoor air pollution, particularly from cigarette smoke, contains harmful Total Volatile Organic Compounds (TVOC) that poses significant health risks. This study aims to evaluate the effectiveness of a Photocatalytic Oxidation (PCO)-based air purification system utilizing a Titanium Dioxide (TiO2)-coated stainless steel mesh reactor and Ultraviolet Light Emitting Diode (UV-LED) sources at 365 nm and 390 nm wavelengths. The methodology involved synthesizing TiO2 sol and immobilizing it onto a stainless steel 304 mesh substrate via a dip-coating technique. Performance testing was conducted in a closed room (volume approx. 136 m³) where smoke from two cigarettes was introduced as the pollutant source. TVOC concentrations were monitored every 5 minutes at five distinct measurement points (center and corners) over a 2-hour period to assess spatial distribution and degradation performance. The results demonstrated that the PCO system with a 365 nm UV-LED reduced the average TVOC concentration from 0.78 ppm to 0.33 ppm, achieving a reduction rate of 57.69%. Meanwhile, the 390 nm UV-LED system decreased the concentration from 0.86 ppm to 0.32 ppm, corresponding to a 62.8% reduction. While the difference in UV-LED wavelength did not significantly alter the photocatalytic performance, light intensity and initial pollutant concentration were found to influence the degradation rate. Overall, the TiO2-coated stainless steel mesh reactor proved to be an effective solution for reducing indoor cigarette smoke pollutants.
Intelligent multi-model system for surface roughness prediction in CNC turning of multiple materials Rohmat, Rohmat; Aryntya Firia Ferlania, Dianda; Frediansah Mukminin, Donni
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.8185

Abstract

Surface roughness is a critical indicator of machining quality that directly affects product performance and service life. However, most existing prediction studies focus on single-material machining and rely on a single predictive model, limiting their effectiveness in real industrial environments where multiple materials are commonly processed. To address this gap, this study proposes an intelligent multimodel system for surface roughness prediction in CNC turning of multiple materials. The experimental investigation was carried out using two commonly applied steels, ST41 and S45C, with 81 machining trials performed for each material. Vibration signals were recorded using a three-axis accelerometer and combined with machining parameters consisting of feed rate, spindle speed, and depth of cut. The acquired signals were analyzed in both time and frequency domains through Fourier transformation, resulting in the extraction of eighteen vibration-related features that were normalized and used as model inputs. Three prediction techniques, namely Multiple Linear Regression, Support Vector Regression, and Artificial Neural Networks, were developed and integrated within the proposed system. System performance was evaluated using Mean Absolute Percentage Error (MAPE) and statistically analyzed through one-way ANOVA and Tukey post-hoc tests. The results demonstrate that the ANN model consistently achieved the highest prediction accuracy, with MAPE values of 2.81% for S45C, 4.72% for ST41, and 4.42% for the combined-material dataset, outperforming the Regression and SVR models. These results confirm that the proposed intelligent multimodel system provides a robust, accurate, and practical solution for vibration-based surface roughness prediction in CNC turning of multiple materials.
Integration of taguchi method and digital metrology for precision fused deposition modelling of PLA-based vibration-damping components Yudistiro, Danang; Junus, Salahuddin; Prasetiyo, Dani Hari Tunggal; Rahmawati, Istiqomah; Amini, Helda Wika; Rizkiana, Meta Fitri
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.8352

Abstract

This study integrates the Taguchi method and 3D digital metrology to improve dimensional accuracy in the Polylactic Acid (PLA)-based Fused Deposition Modelling (FDM) process. The research focuses on the fabrication of vibration-damping roller components in a Continuously Variable Transmission (CVT) system that demands high geometric precision. A Taguchi L9 experimental design was used to analyze the effects of layer height, extrusion temperature, and filling density on the volume deviation of the printed product. The evaluation was conducted using 3D scanning and analyzed using the Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA). The optimal parameter combination was obtained at a layer height of 0.25 mm and an extrusion temperature of 220 °C, resulting in the minimum volume deviation and the highest process stability. The ANOVA results identified layer height as the most dominant factor, followed by extrusion temperature, while filling density had a relatively small effect. Validation tests showed good agreement between the predictions and the experimental results. These findings confirm the effectiveness of integrating the Taguchi method with digital metrology in supporting the development of PLA-based precision additive manufacturing for sustainable automotive component applications.This study integrates the Taguchi method and 3D digital metrology to improve dimensional accuracy in the Polylactic Acid (PLA)-based Fused Deposition Modelling (FDM) process. The research focuses on the fabrication of vibration-damping roller components in a Continuously Variable Transmission (CVT) system that demands high geometric precision. A Taguchi L9 experimental design was used to analyze the effects of layer height, extrusion temperature, and filling density on the volume deviation of the printed product. The evaluation was conducted using 3D scanning and analyzed using the Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA). The optimal parameter combination was obtained at a layer height of 0.25 mm and an extrusion temperature of 220 °C, resulting in the minimum volume deviation and the highest process stability. The ANOVA results identified layer height as the most dominant factor, followed by extrusion temperature, while filling density had a relatively small effect. Validation tests showed good agreement between the predictions and the experimental results. These findings confirm the effectiveness of integrating the Taguchi method with digital metrology in supporting the development of PLA-based precision additive manufacturing for sustainable automotive component applications.
Anthropometry–Kansei for ergonomic assistive device design Andriani, Meri; Dewiyana, Dewiyana; Adlie, Taufan Arif; Nurmalawati, Nurmalawati; Nadya, Yusri; Sari, Leni Putma; Revanza, Bayu; Novianda, Novianda; Yusnawati, Yusnawati
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.8345

Abstract

Manual work using non-ergonomic tools at the packaging station causes workers to bend over for long periods. This condition can increase the risk of Musculoskeletal Disorders (MSDs), thereby reducing worker productivity. The objectives of this study were to determine the greatest pain complaints from workers, design ergonomic aids to reduce MSDs complaints, and analyze worker responses to the ergonomic aids created. The methods used included worker anthropometric measurements, percentile determination, statistical tests to ensure data usability, and Kansei Engineering to identify worker interest in the tool. Results and discussion, popliteal length, popliteal height, and hip width are the dimensions used to design the tool. All dimensions were tested statistically. In the data sufficiency test, all data were declared valid, the data reliability test was declared reliable, and the data normality test stated that the data were normally distributed. The percentile used was the 50th percentile. Worker responses to the tool were evaluated using Kansei Engineering using nine Kansei words. All Kansei words were declared valid with values (0.407- 0.850) exceeding the r-table value, and the reliability test (0.707- 0.791) was declared greater than the Cronbach Alpha limit (5%), so all Kansei words were reliable. In conclusion, the ergonomic aids for packaging workers have a length of 43.65 cm, a height of 44.40 cm, and a width of 33.35 cm, while the evaluation of the aids produced seven descriptors with the highest scores, namely comfortable to use (0.940), safe to use (0.935), light (0.911), easy to use and move (0.913), simple design (0.920), flexible to use (0.951), and very functional when used in the workplace (0.938).

Page 54 of 56 | Total Record : 553

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