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Thermal Optimization of Aluminium Fishing Sinker Mold Using Cooling Channel Design Arifin, Yahya Hafiizh; Putra, Akhri Ramadhan; hasibuan, fardin; Irsyam, Muhammad
METALOGRAM Metalogram Vol.2 No.2 (April, 2026)
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/mtlg.v2i2.8849

Abstract

Thermal performance of mold plays a critical role in determining the quality and productivity of aluminium casting products, including fishing sinkers. Improper temperature distribution within the mold can lead to casting defects, uneven solidification, and extended cooling time. This study focuses on the thermal optimization of an aluminium fishing sinker mold through the design and improvement of cooling channel configurations. Numerical simulations based on heat transfer analysis are conducted to evaluate temperature distribution, cooling efficiency, and solidification behavior within the mold. Several cooling channel designs are analyzed and compared to identify the most effective configuration for achieving uniform temperature distribution and enhanced heat dissipation. The results show that optimized cooling channel design significantly reduces temperature gradients, shortens cooling time, and improves overall casting quality. This study demonstrates that thermal optimization through proper cooling channel design is an effective approach to enhancing the performance and reliability of aluminium fishing sinker molds.
Effect of CO₂ and Argon Gas Shielding on GMAW Welding Joint Quality Ma'asya, Safira; Alfharizi, Muhammad; Manullang, Togu Julianman; Tawaris, Andrean Bastian; Hasibuan, Fardin; Irsyam, Muhammad
METALOGRAM Metalogram Vol.2 No.2 (April, 2026)
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/mtlg.v2i2.7866

Abstract

This study aims to evaluate the effect of shielding gas types, namely carbon dioxide (CO₂) and argon, on the quality of welded joints in the Gas Metal Arc Welding (GMAW) process with low carbon steel as the base material. The research method was carried out experimentally using a steel plate measuring 150 mm × 75 mm × 6 mm and an ER70S-6 electrode wire with a diameter of 1.0 mm. The welding process was carried out with an inverter-type GMAW machine using fixed parameters: 120 ampere current, 22 volt voltage, 4 mm/s welding speed, 12 mm stick-out distance, and 15 liters per minute shielding gas flow rate. The specimens were divided into two groups based on the shielding gas, namely pure CO₂ and pure argon. Evaluation of the joint quality was carried out through tensile tests, Vickers hardness tests on three main zones (weld metal, heat affected zone, and base metal), as well as microstructure and visual observations. The results showed that the specimens with argon gas had a higher average tensile strength (460 MPa) than CO₂ (420 MPa). The hardness values were also higher and more even in the argon specimens, with a finer and more uniform microstructure. In conclusion, the use of argon produces welds with better mechanical and metallurgical qualities than CO₂. Therefore, argon is more recommended for welding low carbon steels that require high strength and precision.
Pembuatan alat pendeteksi dan pengusir monyet secara otomatis di areal pertanian Desa Sugie Kabupaten Karimun Fernando, Wahyu; Hasibuan, Fardin; Irsyam, Muhammad; Kurniawan, Harry; Syaputra, Muhammad Lyan; Delpero, M Arif; Supriyadi, Supriyadi
Riau Journal of Empowerment Vol 8 No 1 (2026)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/raje.8.1.25-34

Abstract

An automatic monkey detection and repellent system based on a Convolutional Neural Network (CNN) and a Raspberry Pi was developed to address crop damage caused by monkeys in Sugie Village, Karimun district. The system uses a webcam to detect monkeys within a radius of up to 50 meters and emits gunshot sounds audible up to 200 meters to automatically repel them. Solar panels power the system because the area has access to electricity only at night. The implementation of this device yielded significant results, reducing crop damage from an average of 9 damaged plants per visit to only 3, equivalent to a 66.7% decrease. Additionally, the solar panels provided lighting for the agricultural area, improving security and accessibility at night by 100%. This technology offers an effective and efficient solution compared to manual methods, which require constant monitoring. The project leverages modern innovation relevant to local needs by integrating renewable energy with image-based detection technology. This project has the potential to be replicated in other regions facing similar issues, supporting food security and improving rural communities.