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Sianipar, Stiven Ewin
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Aerospace Engineering Automotive Engineering Control & Systems Engineering Engineering Industrial & Manufacturing Engineering Other

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Toughness and Structural Analysis of Welds and HAZ of Sumerged Arc Welding on SM 490 Steel Sianipar, Stiven Ewin; hasibuan, fardin; Syaputra, Muhammad Lyan
METALOGRAM Metalogram Vol.01 No.03 (August,2025)
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/mtlg.v1i03.8144

Abstract

The welding process is a metal joining method that utilizes high heat energy, which can trigger changes in the microstructure, deformation, and the emergence of residual stress in the area around the joint. This study aims to examine the impact of variations in heat input in the Submerged Arc Welding (SAW) process on the microstructure and toughness of SM 490 steel, especially in the weld area and heat-affected zone (HAZ). The SAW method was chosen because it has high efficiency, is easy to automate, and is able to produce good quality joints. This study used three levels of heat input, namely 2.1 kJ/mm, 3.16 kJ/mm, and 4.3 kJ/mm. Based on the test results, increasing heat input causes slower cooling, which affects the formation of microstructures such as ferrite at the grain boundary, acicular ferrite, Widmanstätten ferrite, bainite, and martensite. Acicular ferrite with fine size and interlocking pattern is known to contribute to increasing the toughness of welded joints. The maximum toughness in the weld zone, amounting to 117 Joules, was achieved at a heat input of 3.16 kJ/mm with a test temperature of 0°C. Meanwhile, the best toughness value in the HAZ of 17.5 Joules was recorded at a heat input of 2.1 kJ/mm at a temperature of -20°C. The results of this study confirm that appropriate heat input settings are very important to obtain optimal microstructure and toughness in welding SM 490 steel using the SAW method
PENERAPAN ALAT OTOMATIS PENDETEKSI DAN PENGUSIR MONYET UNTUK MENINGKATKAN PRODUKSI PERTANIAN DI AREAL PERTANIAN REMPANG CATE BATAM Hasibuan ST.MT, Fardin; Irsyam, Muhammad; Wijaya, Toni Kusuma; Sianipar, Stiven Ewin; ardiansyah, Edo; Ratuloli, Jumiati; Parendi, Yoga
MINDA BAHARU Vol 9, No 2 (2025): Minda Baharu
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/jmb.v9i2.8342

Abstract

Alat pendeteksi dan pengusir monyet otomatis berbasis Convolutional Neural Network (CNN) dengan mikrokontroler Raspberry Pi dikembangkan untuk mengatasi permasalahan hama monyet yang kerap merusak tanaman di perkebunan kelompok Tani Tunas Baru. Sistem ini menggunakan kamera webcam untuk mendeteksi keberadaan monyet dalam radius hingga 35 meter dan menghasilkan suara tembakan yang terdengar hingga 250 meter guna mengusir hama secara otomatis. Energi listrik untuk alat ini diperoleh dari panel surya karena areal pertanian tersebut belum terjangkau oleh jaringan listrik. Implementasi alat menunjukkan hasil yang signifikan, yaitu penurunan kerusakan tanaman dari rata-rata sembilan pohon menjadi hanya tiga pohon per serangan monyet, atau setara dengan penurunan sebesar 67%. Teknologi ini menjadi solusi yang lebih efektif dan efisien dibandingkan metode manual yang membutuhkan penjagaan secara terus-menerus. Proyek ini mengusung inovasi modern yang relevan dengan kebutuhan lokal, dengan mengintegrasikan sumber energi terbarukan dan teknologi deteksi berbasis citra. Selain itu, sistem ini berpotensi untuk direplikasi di wilayah lain yang menghadapi permasalahan serupa, guna mendukung ketahanan pangan dan meningkatkan kesejahteraan masyarakat pedesaan melalui solusi yang inovatif dan berkelanjutan.
Co-Authors ardiansyah, Edo Fardin Hasibuan Hasibuan ST.MT, Fardin Muhammad Irsyam, Muhammad Parendi, Yoga Ratuloli, Jumiati Syaputra, Muhammad Lyan Toni Kusuma Wijaya, Toni Kusuma