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INDONESIA
METALOGRAM
Published by Universitas Riau Kepulauan Batam
ISSN : -     EISSN : 30902460     DOI : https://doi.org/10.33373/mtlg.v2i1
Core Subject : Engineering,
Aerospace Engineering Automotive Engineering Control & Systems Engineering Engineering Industrial & Manufacturing Engineering
Metalogram is published by Program Studi Teknik Mesin, Fakultas Teknik, Universitas Riau Kepulauan, Batam, Indonesia. Metalogram is an open-access peer reviewed journal that mediates the dissemination of academicians, researchers, and practitioners in mechanical engineering. Metalogram accepts submission from all over the world. Metalogram aims to provide a forum for national and international academicians, researchers and practitioners on mechanical engineering to publish the original articles. All accepted articles will be published and will be freely available to all readers with worldwide visibility and coverage. The scope of Metalogram is in engineering such as design, energy conversion, manufacture, and metallurgy, asset management engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik Mesin
Articles 42 Documents
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Non-Destructive Tecnhnique That Uses Sound Waves To Detect Flaws in Materials Kiki Dwi Putra; Lindo Rivaldi Butar-Butar; Brandon Brandon; Fardin Hasibuan
METALOGRAM Metalogram Vol.02 No.3 (August,2026)
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/mtlg.v2i3.7452

Abstract

Non-destructive testing (NDT) is a crucial method for assessing the structural integrity of materials without causing damage. Among the various NDT techniques, the use of sound waves—such as ultrasonic testing—stands out for its precision and flexibility. This technique utilizes high-frequency sound waves to penetrate materials and detect defects such as cracks, voids, and inclusions. The method operates based on the interaction of sound waves with material boundaries, where imperfections reflect the waves, generating distinct signals. Advanced ultrasonic testing can provide detailed information on the size, location, and orientation of defects, enabling accurate material condition assessment. This abstract highlights the significance of sound wave-based NDT in industries such as aerospace, construction, and manufacturing to ensure safety, reliability, and cost efficiency. Further advancements in this technique can enhance accuracy and maintain structural integrity in critical applications.
AI-Based Material Selection Evaluation for Heavy Construction Machinery Components Yuki Alvandi; Beny Gusnal; Muhamad Adriansyah
METALOGRAM Metalogram Vol.02 No.3 (August,2026)
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/mtlg.v2i3.7456

Abstract

Selecting the right material for heavy construction machinery components is a crucial step in ensuring operational performance, efficiency, and sustainability. Artificial intelligence (AI) technology offers a new approach to this selection process with its fast and high-precision data analysis capabilities. This study aims to evaluate the effectiveness of AI implementation in material selection for heavy construction machinery components. The study utilized machine learning algorithms, such as random forest and artificial neural networks, to analyze material parameters including strength, wear resistance, density, and production cost. The results showed that the AI-based method can improve material selection efficiency by up to 35% compared to conventional methods. In addition, this method is also able to reduce selection errors that often occur in manual approaches. By utilizing AI, the selection process becomes faster, more accurate, and more sustainable, supporting the development of more modern and environmentally friendly construction technologies.

Page 5 of 5 | Total Record : 42

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