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All Journal JMES The International Journal of Mechanical Engineering and Sciences Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) The Indonesian Journal of Computer Science
Juliarsyah, Mohammad Rizanto
Mechanical Engineering Departement, Politeknik Negeri Malang, Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mechanical Engineering

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Development of Corrosion Segmentation Using Deep Learning Double Architecture Method to Assist the Analysis and Evaluation Process of Corrosion Inspection Juliarsyah, Rizanto; Alief Wikarta
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3633

Abstract

Corrosion of pump unit components often occurs in coal mines and can lead to frequent failures of some components. As a result, a corrosion inspection needs to be performed on each component to minimize the possibility of damage. Currently, manual inspection methods are used for corrosion testing but there are still metal defects in the form of corrosion that are uninspected. Therefore, this study aimed to develop corrosion segmentation using computer vision with deep learning double architecture method for detection and evaluation of metal corrosion in order to reduce the loss due to manual inspections. To produce a faster and more accurate analysis method, deep learning double architecture algorithm, namely VGG16-UNET, can be applied with the help of computer vision technology. Consequently, the use of VGG16-UNET method achieved an accuracy of 98.42%. This is in contrast with the single UNET architecture, which produced an accuracy of 92.6%. Based on these findings, it was concluded that the development of this recommended inspection made the analysis and evaluation of corrosion inspection to be quick and easy.
Design of Mechanics and Locomotion System For Box Culverts Inspection Robot Anwar, Khoirul; Juliarsyah, Mohammad Rizanto; Pungkiarto, Irwanda Yuni; Mohammad Abdullah
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4907

Abstract

In Indonesia there is often a flood caused by continuous heavy rain, based on the observation of the condition of the culprit is the cause of flooding in Indonesia. One of the problems owned by the public Works office today is the presence of Dutch-made sewers with concrete materials that have a depth of 6 meters below the surface so that the workers are hard to reach. The following problems need to be developed a technology that does not require human presence to directly monitor the circumstances that occur in the drain pipes (sewers) by using a mobile robot to perform monitoring. The result of this study obtained output in the form of a mobile robot that can work in various terrain, and to get a good response in the control system used Ziegler-Nichols for Tunning.
Development of a System and Deep Learning Method for Metal Surface Corrosion Detection and Evaluation in Industrial Equipment Juliarsyah, Mohammad Rizanto; Yuni Pungkiarto, Irwanda; Risnawati, Faradilla Fauziyah; Anwar, Khoirul; Shabrina, Dhia Fairuz
JMES The International Journal of Mechanical Engineering and Sciences Vol 9, No 2 (2025)
Publisher : LPPM, Institut Teknologi Sepuluh Nopember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v9i2.23189

Abstract

Corrosion inspection of industrial assets is still dominated by subjective and inconsistent visual inspections. This study develops and validates a deep learning-based corrosion area detection system on metal surfaces in the context of heavy equipment through a binary segmentation task (corrosion vs. non-corrosion). Three architectures were compared: UNet, VGG16–Random Forest, and VGG16–UNet, using 600 annotated images measuring 512 × 512 pixels taken under lighting conditions of 50–150 lux. The workflow included preprocessing, augmentation, training for 30, 50, and 100 epochs, and evaluation of accuracy, precision, recall, IoU/Jaccard, Dice, and confusion matrix per pixel (positive = corrosion). The results show that VGG16–UNet provides the best performance; in the 150 lux test, it achieved 98.96% accuracy, 0.9934 precision, and 0.994 recall, with good consistency across lighting variations and data scales. These findings confirm the effectiveness of a pre-trained encoder combined with skip connections to recover fine corrosion boundaries and produce reliable corrosion maps. The proposed approach has the potential to standardize the inspection process and accelerate decision-making in reliability-based maintenance practices.
Analisis Modal dan Modifikasi Struktur Pompa Closed Drain 510-P9002 untuk Mitigasi Getaran di Lapangan Jambaran Tiung Biru Achmad Walid; Irwanda Yuni Pungkiarto; Mohammad Rizanto Juliarsyah; Khoirul Anwar
JURNAL RISET RUMPUN ILMU TEKNIK Vol. 4 No. 3 (2025): Desember : Jurnal Riset Rumpun Ilmu Teknik
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v4i3.6575

Abstract

This study presents a modal analysis of Pertamina EP Cepu’s closed drain pump 510-P9002, which operates in the condensate–water treatment unit of the Jambaran Tiung Biru field. Field vibration measurements conducted in August 2024 indicated a fundamental frequency of 25 Hz, corresponding to 1×RPM of the driving motor, with maximum amplitudes reaching 13.46 mm/s. Such excessive vibration poses risks of mechanical damage, reduced equipment service life, and potential operational failure. To address this issue, finite element analysis (FEA) was employed to examine the dynamic response of the pump, determine its natural frequencies, and identify possible resonance conditions. A CAD model of the pump–vessel assembly was developed, meshed, and analyzed under actual boundary conditions. The results showed several natural frequencies ranging between 23.16 and 26.65 Hz, which are close to the excitation frequency, suggesting a very high likelihood of resonance. Various structural modifications were then evaluated, including a half casing and two types of full casings. Among these, the full casing B design provided additional stiffness in the motor support area; however, none of the modifications effectively reduced vibration within the internal components. Based on these findings, the study recommends the implementation of a dynamic vibration absorber (DVA) tuned to the excitation frequency, along with the redesign of structural components to shift natural frequencies away from operating excitation. These solutions are expected to improve operational stability, extend equipment lifespan, and enhance overall system reliability. The outcomes of this research provide important insights for managing vibration issues in pump systems operating under similar conditions, particularly in the oil and gas industry where continuous, stable operation is critical.
Co-Authors Alief Wikarta Anwar, Khoirul Irwanda Yuni Pungkiarto KHOIRUL ANWAR Khoirul Anwar Mohammad Abdullah Pungkiarto, Irwanda Yuni Risnawati, Faradilla Fauziyah Shabrina, Dhia Fairuz Walid, Achmad Yuni Pungkiarto, Irwanda