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All Journal Journal of Materials Exploration and Findings (JMEF)
Federico, Andreas
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Investigating Features and Output Correlation Coefficient of Natural Fiber-Reinforced Poly(lactic acid) Biocomposites Federico, Andreas; Surip, Siti Norasmah; Wan Jaafar, Wan Nor Raihan; Fatriansyah, Jaka Fajar; Pradana, Agrin Febrian
Journal of Materials Exploration and Findings Vol. 1, No. 1
Publisher : UI Scholars Hub

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Abstract

Polylactic acid (PLA) material has the potential to be applied in various industrial fields, but this material has shortcomings in terms of mechanical properties, especially mechanical strength, due to brittleness nature of PLA. The manufacture of PLA composite material with the addition of natural fibers as a reinforcing phase is one of the methods to increase the impact strength and maintain the biodegradable properties of the material. However, in theory, there are many factors that affect the mechanical properties of composite materials, thus making the mechanical properties of composites more complex than monolithic materials. The mechanical properties of these composite materials can be predicted using deep learning by paying attention to the relationship between factors, and between factors and their mechanical properties. This relationship has an important role in creating a predictive model with good accuracy. Therefore, correlation analysis is an important thing to do. Correlation analysis was applied using Python programming language to determine the relationship between the impact strength of natural fiber-reinforced PLA biocomposites with its feature information: chemical composition, density, dimensions, surface chemical treatment of natural fibers, matrix-reinforcement volume fraction, and the type of processing used to manufacture the material.
Development of Dynamic Risk-Based Inspection Using Forward Difference Approach for Pipe Failure Due to Uniform Corrosion Fatriansyah, Jaka Fajar; Nurullia, Zahra Nadia; Federico, Andreas; Priadi, Dedi
Journal of Materials Exploration and Findings Vol. 2, No. 1
Publisher : UI Scholars Hub

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The oil and gas industry is one of the world's largest and most influential energy contributors. All aspects involved in the operation of this industry are fundamental to be reviewed and managed correctly, especially by preventing or minimizing the failures that could occur. Uniform corrosion is the most common component failure mechanism that can cause failure in the oil and gas industry. The company's actions in managing and preventing the risk of this type of failure have a major role in the sustainability of the company due to the possibility of more significant impacts if the risk cannot be handled well, such as high inspection and handling costs, environmental impacts, and threats to work safety. In this study, the Dynamic Risk-Based Inspection (DRBI) method, which is a development of Risk-Based Inspection (RBI), is implemented to handle and analyze risks that are managed in real-time at each inspection period. Risk level analysis was carried out through data processing related to pipe thickness from the risk profile from the inspection results in 5 months using Igor and Rstudio software and calculating corrosion rates using the forward difference approach. Based on the analysis results, five risk levels of pipeline failure at PT. X due to uniform corrosion using DRBI was obtained, consisting of two medium risks and three medium-high risks. In contrast, only one risk level was obtained from the RBI method, namely medium-high. The risk value fluctuates greatly every month, causing the DRBI method to have a higher level of accuracy and the ability to detect potential risks in more detail than the RBI method.
Co-Authors Dedi Supriadi Fatriansyah, Jaka Fajar Nurullia, Zahra Nadia Pradana, Agrin Febrian Surip, Siti Norasmah Wan Jaafar, Wan Nor Raihan