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The Integration of Supervisory Control and Data Acquisition (SCADA) on the Crushing and Barge Loading Conveyor Systems Imam Sutrisno; Ihza Anfasa Dua Nurhidta; Ii Munadhif; Edy Prasetyo Hidayat; Joko Endrasmono; Projek Priyonggo; Tri Mulyatno Budhi Hartanto
International Journal of Marine Engineering Innovation and Research Vol 8, No 1 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v8i1.15472

Abstract

The utilization of the Crushing and Barge Loading Conveyor (BLC) systems is important in coal processing. A crushing system is required as a tool for the process of crushing coal into smaller sizes and then transferring it to the stockpile. While a BLC system is needed to transport coal from the stockpile to the barge. In general, the control and supervision systems for crushing and BLC systems are carried out separately by two operators. However, the distance between two operators causes a time lag information. In this research, we create a Supervisory Control and Data Acquisition (SCADA) system with the type of Multiple Programmable Logic Controller (PLC) on the Crushing and BLC systems using Profinet communication integrated by two PLCs with one Human Machine Interface (HMI) and WinCC. The system is equipped with real-time data, automatic control, and online surveillance with smartphones via the S7APP application. The error resulting from the reading of each component by the HMI and smartphone reaches 0%, while for automatic control, the system works very well, having a success rate of 100%.
Performance Improvement Incremental Conductance Algorithm using Incremental Fuzzy to Reach GMPP under Partial Shading Conditions Imam Sutrisno; Joessianto Eko Poetro; Pranowo Sidi; Boedi Herijono; Antonius Edy Kristiyono; Monika Retno Gunarti
International Journal of Marine Engineering Innovation and Research Vol. 9 No. 1 (2024)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v9i1.5044

Abstract

This paper proposes an improved Maximum Power Point Tracking (MPPT) algorithm for photovoltaic (PV) systems under partial shading conditions. The proposed method enhances the widely used Incremental Conductance (IC) algorithm by incorporating an incremental fuzzy control technique. The conventional IC algorithm suffers from limitations in adapting to rapidly changing irradiation conditions due to its fixed step size. The proposed Inc-Fuzzy algorithm dynamically adjusts the step size based on the change in power and voltage, enabling it to better track the Global Maximum Power Point (GMPP) under partial shading. Simulation results demonstrate that the Inc-Fuzzy algorithm achieves an average accuracy of 98.29% under constant irradiation and outperforms the conventional IC algorithm by 1.69% in terms of captured power during sudden irradiation changes. This improvement highlights the effectiveness of the Inc-Fuzzy approach in enhancing the performance of MPPT for PV systems under challenging operating conditions.
Corrosion Detection on Ship Hull Using ROV Based on Convolutional Neural Network Yuning Widiarti; Edy Setiawan; Hendra Aldi Prasetiyo; Budianto Prasetiyo; Imam Sutrisno; Andianto; Mohammad Basuki Rahmat
International Journal of Marine Engineering Innovation and Research Vol. 9 No. 1 (2024)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v9i1.5071

Abstract

The Remotely Operated Underwater Vehicle (ROV) has several inspection functions. One of them is the inspection function for hull damage. The damage that often occurs in the hull is corrosion. The corrosion can cause a decrease in the strength of the hull plate, reduce the speed of the ship, and decrease the quality of the safety level of ships and passengers. This study aims to classify the level of corrosion intensity on ship hulls by implementing a Convolutional Neural Network (CNN). Identification is carried out on images taken by underwater cameras via a Remotely Operated Vehicle (ROV). The intensity of the area affected by corrosion is identified so that the level of corrosion intensity can be classified and it can be considered that the ship needs maintenance to prevent even greater losses due to corrosion. The dataset used is 240 image data divided into 3 classification categories: low, medium, and high corrosion intensity. The accuracy of the real-time testing of the CNN method on the dataset plate when conditions outside the water reached 91.1% and on the dataset plate when conditions underwater reached 86.6%.
The Integration of Supervisory Control and Data Acquisition (SCADA) on the Crushing and Barge Loading Conveyor Systems Imam Sutrisno; Ihza Anfasa Dua Nurhidta; Ii Munadhif; Edy Prasetyo Hidayat; Joko Endrasmono; Projek Priyonggo; Tri Mulyatno Budhi Hartanto
International Journal of Marine Engineering Innovation and Research Vol. 8 No. 1 (2023)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v8i1.5524

Abstract

The utilization of the Crushing and Barge Loading Conveyor (BLC) systems is important in coal processing. A crushing system is required as a tool for the process of crushing coal into smaller sizes and then transferring it to the stockpile. While a BLC system is needed to transport coal from the stockpile to the barge. In general, the control and supervision systems for crushing and BLC systems are carried out separately by two operators. However, the distance between two operators causes a time lag information. In this research, we create a Supervisory Control and Data Acquisition (SCADA) system with the type of Multiple Programmable Logic Controller (PLC) on the Crushing and BLC systems using Profinet communication integrated by two PLCs with one Human Machine Interface (HMI) and WinCC. The system is equipped with real-time data, automatic control, and online surveillance with smartphones via the S7APP application. The error resulting from the reading of each component by the HMI and smartphone reaches 0%, while for automatic control, the system works very well, having a success rate of 100%.
Prototype of Bridge Navigational Watch Alarm System Equipped Obstacle Warning System Based on Image Processing and Real-Time Tracking Iskandar; Dewa Pamungkas; Imam Sutrisno; Afif Zuhri Arfianto; Ari Wibawa Budi Santosa; Iie Suwondo
International Journal of Marine Engineering Innovation and Research Vol. 7 No. 1 (2022)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v7i1.5637

Abstract

Ships are sea transportation that is often used in Indonesia. However, who would have thought that the transportation would become a case because of the frequent occurrence of accidents. This has been proven from data from the KNKT (National Transportation Safety Committee) which noted that from 2012 to 2017 there had been an increase in accidents in the waters. In fact, according to the National Search and Rescue Agency (Basarnas) in 2020 there have been 878 incidents with victims reaching 4658 people. In this final project, the author makes a prototype of BNWAS (Bridge Navigational Watch Alarm System) equipped with obstacle warning using image processing with the otsu method strengthened by thresholding-based segmentation with inverse technique (TsTN), distance detection using the triangle similarity method, real-time tracking with GPS (Global Positioning System) and the entire system can be observed on the Android application. The Final Project performs several analyzes including performance analysis by calculating the accuracy of the BNWAS alarm system, image detection accuracy, distance detection accuracy, GPS accuracy, overall system testing accuracy and packet loss. The accuracy of each system is very good because the error is below 2%, while for overall system testing has a very good performance with a delay of 179.8 ms and 0% packet loss.
Analysis of Causes of Starting Failure on Auxiliary Engine MT Green Stars with HAZOP Method Ardiansyah Nur Rahman; Shofa Dai Robbi; Akhmad Kasan Gupron; Azis Nugroho; Nasri; Rama Syahputra Simatupang; Imam Sutrisno
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 2 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i2.6431

Abstract

Air motor starter is a component that functions to rotate the engine auxiliary flywheel to move the piston for the first combustion to occur. In this system, high-pressure air from a compressor or air tank is used to drive a starter motor that is directly connected to the engine crankshaft. As the starter motor operates, pressurized air is channeled into the starter motor cylinders, creating a rotational movement on the shaft that eventually rotates the auxiliary engine crankshaft. Air motor starters on MT Green Stars are essential for the auxiliary engine starting system on board MT Green Stars. This study aims to analyze the factors that cause the failure of auxiliary engine start failure caused by the rupture of the starter motor water bearing and the impact on the auxiliary engine. This research uses a descriptive analysis method using HAZOP data analysis techniques and data collection from observations, logbooks, journals, manual books, and interviews The research was conducted on the MT Green Stars ship which has three auxiliary engines and is experiencing problems with the starting system. Based on the research, failure factors in auxiliary engines are caused by several factors, namely starter motor water, injectors, starter motor water, and fuel filters. The impact of auxiliary engine start failure causes failure of the electrical system, system, pump, hydraulic and pneumatic system disorders, work efficiency disorders, risk of damage to the main engine, and safety and regulatory disorders. To handle it, maintenance needs to be carried out, both preventive maintenance and breakdown maintenance. The suggestions that researchers make are to routinely carry out maintenance according to PMS (Planned Maintenance System), carry out toolbox meetings, check especially auxiliary engines.
Load Cell Failure Risk in Tandem Mobile Crane Lifting: A Fuzzy Fault Tree Analysis Approach Fatich Pradana Putra; Priyambodo Nur Ardi Nugroho; Imam Sutrisno
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 2 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i2.6471

Abstract

Mobile crane lifting activities carry a significant accident risk, especially when performed in tandem configurations. The main risk comes from the possibility of failure of the load cell component which plays an important role in actual load measurement. This research aims to analyze the potential failure of the load cell function in tandem lifting operations using the Fuzzy Fault Tree Analysis (FFTA) method. Data were collected through literature studies, field observations, and interviews. The FFTA method is used to identify factors that cause failure and calculate the probability of failure quantitatively. The investigation identified that the primary variables leading to load cell failure include overload situations, internal component damage, and external impacts. The highest probability of failure was recorded in the material fatigue scenario due to damage to the cable. These findings highlight the need of instituting preventative maintenance programs and conducting frequent inspections of load cell components to reduce the risk of workplace accidents.